using this preferential information. The sample is composed of a middle point and a set of non-dominated points from its neighborhood. MA shows these points to the decision-making agent.

<figure><img src="image_18.png" /><figcaption>Figure 2.3 : Light Beam Projection</figcaption></figure>

Private light beam search preserves the privacy of individual preferential parameters of the decision making agents about the target goal in terms of aspiration point (P<sub>A</sub>), reservation point (P<sub>R</sub>), indifferent threshold (I<sub>th</sub>), strong preference threshold (S<sub>th</sub>), weak preference threshold (W<sub>th</sub>), veto threshold (V<sub>th</sub>), middle point (MP) and preferred solutions resulted from the search process. The mediator agent preserves the privacy of the search problem. The value of an objective function which is desirable or satisfactory to the decision maker is called *aspiration point*. The value of an objective function that the decision maker wants to avoid is called *reservation point*. A decision vector x*∈S is pareto optimal if there does not exist another decision vector x∈S such that f<sub>i</sub>(x) ≤ f<sub>i</sub>(x*) for all i=1,...,k and f<sub>j</sub>(x) < f<sub>j</sub>(x*) for at least one index j; f<sub>i</sub> is objective function and S is feasible space. An objective vector z*∈Z is pareto optimal if there does not exist another objective vector z∈Z such that z<sub>i</sub> ≤ z<sub>i</sub>* for all i=1,...,k and z<sub>j</sub> < z<sub>j</sub>* for at least one index j.

The decision maker should inform the mediator various *preference thresholds* in order to compare alternatives and to define outranking relations. There is an interval of preference wherein it is not possible for the decision-making agent to distinguish between different alternatives due to imprecision and uncertainty of measurements and this corresponds to *indifference threshold*. *Strict preference threshold* is defined as minimal increase/decrease of any objective that makes the new alternative strictly preferred with respect to this objective. There exists an intermediate region between indifference and strict preference threshold where the decision-making agent hesitates to compare alternatives. This corresponds to *weak preference threshold*. *Veto threshold* It indicates that what is the minimal increase/decrease of any objective that makes the new alternative unacceptable regardless of the value of other objectives. In each computation phase of search, a finite sample of non-dominated points is generated by the mediator agent. The sample is composed of a middle point and a set of points within its neighborhood. The starting middle point is obtained by projecting aspiration point on the non-dominated set in the direction of reservation point. For a middle point, the
neighborhood is defined as a set of non-dominated points that are not worse than the middle point. The neighborhood points from the sample indicate to what extent the values of particular objectives can be improved in relation to the *middle point*.

## Test case: Private real-time moving target search algorithm for robotic navigation

The goal state of private search algorithm may be fixed or may change during the course of search. The goal may be a target which actively avoids the searching agent or object. In case of robot navigation In a moving target search algorithm, if the average speed of target robot is slower than that of the problem solving search agent, the later is guaranteed to eventually reach the target in a connected problem space. The algorithm is expected to be efficient in terms of minimum operations necessary to guarantee its completeness, commitment to reach the target goal and deliberation for selecting plan as per the principle of resource based planning. The target robot may be reaching the problem solving robot cooperatively or avoiding the same. The target robot may not stop eventually. The goal is achieved when the position of the problem solving robot and target robot coincide. If the problem solving robot moves faster than the target robot, the goal may be achieved. Otherwise, the target robot could evade the problem solving robot infinitely even in a finite problem solving space by avoiding in a dead end path.

## Private Real-time Moving Target Search Mechanism

Agents / Objects : Problem solving agent(s), Target agent(s);

Scope :

* Goal / Changing goal of moving target(s)

* Constraints : Space complexity, Time complexity, uncertainty in movement of target(s);

System :

* ✓ Input: x – current position of search agent; y – current position of target; z – current speed of search agent;

* ✓ Output : Adaptive search plan;

* ✓ Procedure

* Case 1 : When problem solving search agent moves

* Calculate $h(x',y)$ for each neighbor $x'$ of x;

* Update the value of $h(x,y)$; $h(x,y) \leftarrow \max(h(x,y), \min_x[h(x',y)+1])$;

* Move to the neighbor $x'$ with minimum $h(x',y)$; assign the value of $x'$ to x; ties are broken randomly.

* Case 2 : When the target agent moves

* Calculate $h(x,y')$ for new position $y'$ of target;

* Update the value of $h(x,y)$ : $h(x,y) \leftarrow \max[h(x,y), \{h(x, y') - 1\}]$;

* Set the new goal of the searching agent as the new position of the target; assign the value of $y'$ to $y$.
**Structure**: The search space consists of a set of nodes connected through edges.

**Security**: Verify security intelligence of searching mechanism,

* Access control: A or a set of authorized problem solving search agent(s) should be able to communicate and exchange data through authenticated channel and correctly identify target agent(s) in time.

* Privacy in revelation principle: The problem solving agent(s) hide own speed and position from the target(s).

* Audit rationality, commitment of trust of searching agents.

* Verify fairness and correctness of heuristics estimate of distance, speed and position of the targets).

* Assess the risks of corruption of searching agent(s) (e.g. problem solving robot).

* Verify reliability, consistency, deadlock-freeness, reachability and resiliency of the search process.

* Assess the risks of malicious attacks: Denial of service, false data injection and Sybil attack.

**Strategy**: Adaptive real-time private moving target search – depth first search, breadth first search or a combination of the two;

**Resources**: Allocate adequate resources for search and private communication.

**Skill-style-support**: Ensure transparency, accountability, collaboration, coordination and resource based planning in private search.

***Analysis of Private Search Algorithm***: The efficiency of private moving target search is evaluated n terms of space complexity and time complexity. The upper bound on the space complexity of private moving target search is $n^2$ where n is the number of states in the problem space. The overall space complexity is the minimum of $n^2$ and the total number of moves of the problem solving search agent and target. The worst-case time complexity of private search is $n^3$ where n is the number of states in the problem space. It can be obtained based on maximum heuristic disparity. The total heuristic error is upper bounded by $n^3$ and the maximum heuristic value of each state is n. If no updates of heuristic values occur, the maximum number of moves of the problem solver to reach the target is n = w where w is fraction of moves skipped by the target. Over the course of a single problem solving episode, the searching agent gradually learns more accurate heuristic values until the target is reached. Next issue is the speed of the search agent and the target. There are two possibilities. The search agent can move faster than the target but it is not strictly necessary. A weaker condition is that the target may move as fast as the search agent, but occasionally makes errors in avoiding the problem solver. Finally, the complexity of private search depends on available information about the target by the search agent. Is it really valid that the search agent always knows the position of the target. The search agent must try to know the position of the target at some point before it reaches the last known position of the target.

The basic building block of private search algorithms is *adaptive secure multi-party computation*. Let us first discuss the traditional concept of secure multi-party computation. Two or more agents want to conduct a computation based on their private inputs but neither of them wants to share its proprietary data set to other. The objective of secure multiparty computation (SMC) is to compute with each
party's private input such that in the end only the output is known and the private inputs are not disclosed except those which can be logically or mathematically derived from the output. In case of secure multi-party computation, a single building block may not be sufficient to do a task; a series of steps should be executed to solve the given problem. Such a well-defined series of steps is called a SMC protocol.

In the study of SMC problems, two models are commonly assumed: semi-honest model and malicious model. A semi-honest party follows the protocol properly with correct input. But after the execution of the protocol, it is free to use all its intermediate computations to compromise privacy. A malicious party does not need to follow the protocol properly with correct input; it can enter the protocol with an incorrect input. Adaptive secure multi-party computation deals with adaptive adversaries that may choose the corrupted parties during the course of computation in a setting of insecure communication channels. In case of Non-adaptive secure multi-party computation, the set of corrupted parties is arbitrary but fixed before the computation starts.

A search protocol preserves privacy if no agent learns anything more than its output; the only information that should be disclosed about other agent's inputs is what can be derived from the output itself. Secure multi-party computation preserves privacy of data in different ways such as adding random noise to data, splitting a message into multiple parts randomly and sending each part to a DMA through a number of parties hiding the identity of the source, controlling the sequence of passing selected messages from an agent to others through serial or parallel mode of communication, dynamically modifying the sequence of events and agents through random selection and permuting the sequence of messages randomly. Security and privacy of critical data is an important concern in any search procedure. Existing literature on private search is highly focused on the construction of various types of cryptographic tools (e.g. encryption and decryption, signcryption) and query processing on encrypted data as per the needs of revelation principle, information disclosure and privacy policy and risks of corruption of a mechanism. But it is not the only serious concern in a probabilistic search procedure. Let us define the private search on the basis of adaptive secure multi-party computation from a new outlook.

The security intelligence of the private probabilistic search procedure is a multi-dimensional parameter which is defined in terms of rationality, fairness, correctness, resiliency, adaptation, transparency, accountability, trust, reliability, consistency, commitment; safety, liveness, synchronization, reachability, deadlock freeness; authentication, authorization, correct identification, non-repudiation, integrity, audit and privacy. The search procedure addresses the issues of authentication, authorization, correct identification, privacy and audit through cryptographic solutions. For private search, the system should ask the identity and authentication of one or more agents involved in the mechanism. The agents of the same trust zone may skip authentication but it is essential for all sensitive communication across different trust boundaries. After the identification and authentication, the procedure should address the issue of authorization. The system should be configured in such a way that an unauthorized agent cannot perform any
searching task out of scope. The system should ask the credentials of the requester; validate the credentials and authorize the agents to perform a specific task as per agreed protocol. Each agent should be assigned an explicit set of access rights according to role. Privacy is another important issue; a searching agent can view only the information according to authorized access rights. The search procedure preserves privacy if no agent learns anything more than its output; the only information that should be disclosed about other agent's inputs is what can be derived from the output itself. The agents must commit the confidentiality of data exchange associated with private communication. Privacy is the primary concern of the revelation principle of a private search; the issue can be addressed through the concept of cryptography to provide confidentiality, data integrity, authentication and non-repudiation.

Traditionally, cryptographic solutions are focused to ensure information security and privacy. But there are other different types of cryptographic concerns since the security intelligence is evaluated in terms of fairness, correctness, transparency, accountability, confidentiality and trust. The search mechanism is expected to ensure correctness in correct detection of target objects through adaptive real-time data mining and secure communication among the searching agents free from any false data injection attack; each recipient must receive the same correct data in time without any change and modification done by any malicious agent. Fairness is associated with the commitment, honesty and rational reasoning and trust. Fairness ensures that something will or will not occur infinitely often under certain conditions; it is important from the perspective of fair resource allocation in a search procedure. The search procedure must ensure the accountability and responsibility of the searching agents in access control and data mining. In fact, accountability is associated with collective intelligence. The transparency of the procedure is associated with communication protocols, revelation principle and automated system verification procedures (e.g. group testing). For example, a procedure should clearly state its goal state.

The performance and quality of search is expected to be consistent and reliable; it should be validated through *audit* of probabilistic search procedure. *Reachability* ensures that some particular state or situation can be reached. *Safety* indicates that under certain conditions, an event never occurs. *Liveness* ensures that under certain conditions an event will ultimately occur. Deadlock freeness indicates that a system can never be in a state in which no progress is possible; this indicates the correctness of a real-time dynamic system. The effectiveness of probabilistic search procedure is expected to be verified adaptively on the basis of correctness, privacy, transparency, reliability and consistency. *Adaptability* is about responding to change effectively and decisively through real-time search: the ability to identify the change in search space for the moving targets, understanding the probable impacts of the hit by the targets, rapid quantification what is under its control to compensate, identification what modifications to the environment are necessary and adoption of risk mitigation measures in time without any hesitation. The aforesaid discussion gives a complete definition of ‘private search’ based on adaptive secure multiparty-computation.
# 4. STRUCTURE

## *Structure Analytics*

**Agents**: System analysts, business analysts;

**Moves**: Design and configure

* **Organization structure**: Technology forums; National level: Government, NGOs, research organizations; International level: strategic alliance among global organizations;

* **System architecture**; Innovate a set of emerging technologies;

* **Level 1**: earth science, information technology, electrical, electronics, chemical, mechanical, civil, biotechnology, pharmaceutical engineering;

* **Level 2**:

* **Earth Science**

* Receiving antenna, satellite, laser pulse transmission unit, automated data processing unit; / * for artificial rainfall) */

* Astronomical hazards: telescopes, search agents, sensors,;

* **Information technology**:

* Define computing, data, networking, security and application schema of artificial immune system, e-governance, real-time data tracking system.

Mr. Lin and Dr. S. Chakraborty are giving the basic overview of the structure on emerging technologies against natural disaster. The laser induced artificial rainfall system consists of a receiver unit, processor unit and transmission unit. These components communicate with each other through satellites. The receiver unit receives the data about the clouds (e.g. temperature, humidity, height from earth surface, pressure) and the data of demand of rain for a zone. The processor unit processes the transmitted data, computes the intensity and pulse duration of plasma laser and selects the right transmission unit to trigger laser induced artificial rainfall. A particular zone may be assigned to more than one transmission units as per demand. The transmission unit sends a laser pulse in the given direction of the intensity computed by the processor. This unit is connected to processor unit through satellites. More than none transmission units may be connected to a centrally located receiver and processor unit. It cuts cost of the laser induced rainfall system and may cover larger region.

The transmitter could be a terawatt femtosecond Ti sapphire pulse laser; fundamental wavelength may be ~800nm; pulse energy ~400mJ, duration 100fs and repetition frequency of 10-100Hz. The laser pulse propagates with almost high peak intensity over a distance of ~500m. The transmitter unit should be mounted on a moving platform to cover large area as per demand. This nonlinear phenomenon is caused by the subtle interplay between self-focusing induced by optical Kerr effect and the defocusing by the self-generated plasma. It is essential to compute the power
and wavelength of laser for bond breaking and ionization at the cloud height of 500m. The system is controlled by a Micro Controller remote unit having data acquisition and processing system, fast transient digitizer and computer controlled stepper motors. The laser beam energy is adjusted by the stepper motor. The system is operated by a MV power supply. Initially the beam will be of 15 cm arc and the beam expander vary the width of the beam to get significant amount of rain. A movable mirror directs the beam in the larger area of the atmosphere. It is also required to compute the cross-section of the beam for rainfall to cover a reasonably wider area.

The next element of the deep analytics is structure which should be analyzed from the perspective of organization structure and system architecture. The technological innovation related to the artificial rainfall and multi-agent resource sharing mechanism is suitable for a collaborative enterprise model. The system architecture is shown in figure at an abstract level. Let us also consider the structure of an information system to be used in allocation and sharing of water. The information system should monitor a set of entities such as various water bodies, rivers, canals, lakes and dams; demand of water in agriculture, industrial plants and domestic uses, supply of water, rainfall data, water level in rivers, lakes and storage systems, pollution levels and water sharing data (Reference: Table 2.1). It may be integrated with GIS. The information system is expected to support the decision making process associated with artificial rainfall i.e. what initiatives are essential to fulfill the demand-supply gap. The resource sharing system should be able to interact with various types of sensors and measuring instruments like water level indicator, inflow and outflow measuring instruments physically for real-time supply chain optimization in water resource management. The resource sharing mechanism may also require an intelligent negotiation support system (NSS) for multi-party negotiation in water sharing; it is basically a group decision support system; it permits collection of different views of the negotiating agents; defines the structure of the problem, generates alternatives for compromise and improves the quality and the acceptability of a negotiated agreement.

<table><thead><tr><td>Entities</td><td>Demand of water</td><td>Supply of water</td><td>Rainfall data</td><td>Water level</td><td>Pollution level</td><td>Water sharing</td></tr></thead><tbody><tr><td>Water bodies</td><td>Agriculture</td><td>Rainfall</td><td>Natural rainfall</td><td>Water bodies : rivers, lakes</td><td>Pollutants, plastic, paper</td><td>Inflow</td></tr><tr><td>Canals</td><td>Industry</td><td>Sharing from other sources</td><td>Artificial rainfall</td><td>Dams</td><td>Drainage system</td><td>Outflow</td></tr><tr><td>Rivers</td><td>Domestic use of population</td><td>Capacity utilization</td><td></td><td>Storag e system</td><td>Congestion</td><td>Shared data</td></tr><tr><td>Lakes</td><td>Drinking, cooking</td><td>Loss or wastage</td><td></td><td></td><td>Encroachme nt statistics</td><td>Surplus</td></tr></tbody></table>
<table><caption>Table 2.1: Analytics for resource allocation and sharing</caption><tr><td>Dams</td><td>Washing and cleaning</td><td></td><td></td><td></td><td></td><td>Shortage</td></tr><tr><td>Lock gates</td><td>Natural activities and bathing</td><td></td><td></td><td></td><td></td><td></td></tr></table>

## 4. SECURITY

### Security Analytics

**Organization**: global earth science organizations;

**Verification mechanism**: audit security intelligence.

* **security policy**: verify rationality, fairness, correctness, transparency, accountability, trust and commitment;

* **system performance**: verify reliability, consistency, scalability, resiliency, liveness, deadlock freeness, reachability, synchronization, safety;

* **multi-party corruption**: do surveillance through security council of global organization, police, army, detectives, journalists;

* Safety from natural disaster

* Safety from war, bioterrorism and acts of terrorisms

* **access control**: verify authentication, authorization, correct identification, privacy, audit confidentiality, data integrity and non-repudiation;

* **malicious attacks**: verify the risk of false data injection, denial of service (DoS) and fault injection attack;

call threat analytics and assess risks of emerging technologies:

* what is corrupted or compromised (agents, computing schema, communication schema, data schema, application schema)?

* time: what occurred? what is occurring? what will occur? assess probability of occurrence and impact.

* insights: how and why did it occur? do cause-effect analysis on performance, sensitivity, trends, exception and alerts.

* recommend: what is the next best action?

* predict: what is the best or worst that can happen?

**Output**: security intelligence

Dr. Kalin Croft and Dr. Han are debating on the security intelligence of emerging technologies against natural disasters. The security of the technological innovation related to artificial rainfall and multi-agent collaborative resource sharing mechanism should be analyzed from the perspectives of fairness, correctness, transparency, accountability, reliability, consistency, resiliency, authorization and authentication in access control, trust and commitment. It is really a hard task to estimate the resource to be allocated and shared fairly and correctly in time. The resource sharing mechanism should be transparent to all the stakeholders through intelligent broadcast communication. The operators and the administrators of the system should be accountable for any mishap due to the natural disaster such as timely release of water from the dam during heavy rainfall in the rainy season or
proper storage of water in the dam during the summer and the winter for proper irrigation to the fields of agriculture. The performance of the system is expected to be evaluated in terms of reliability and consistency. Who will take the decision of artificial rain? The system should be operated by the authenticated and authorized decision making agents only since it is a very sensitive issue, which is related to the safety and security of a large number of human beings, plants and animals over a specific zone (e.g. it may be a district or a state or even a country).

A group of authorized agents should be able to access the technology of artificial rainfall. They should be able to communicate through authenticated channels for taking important decisions on artificial rainfall. They should be able to identify correctly the demand of artificial rainfall based on evaluation of drought and flood in a country. The decisions should be evaluated and justified based on fairness, correctness, transparency of resource sharing policy, accountability of DMA, rationality, trust and commitment. Rationality is the most important decision making factor of artificial rainfall. There are threats of multi-party corruptions and various types of malicious attacks on the technology of artificial rainfall and cloud seeding technology. The system should be free of denial of service attack, false data injection, Sybil, shilling and fault attack. The system performance should be verified in terms of reliability, consistency, resiliency, liveness, safety, deadlock freeness and reachability. Flaws in rational decision making may result in flood or drought in critical zones globally.

### Test case: Water Riot

Prof. Hariharan is presenting a case of water sharing conflict between two states U (upstream state) and D (downstream state) associated with a river (R). There is lack of mutual cooperation and trust between two states in the context of water sharing of river R. Initially, the Supreme Court (SC) orders the state government of U to release water of 15000 cusec / day; then 12000 cusec / day; then 6000 cusec water / day to the state D. There was a water riot in state U; the mob torched 42 buses; a leader was killed. Inflow from U was 15000 cusecs/ day last week. 12000 cusecs was being released everyday from Dam X from 20.9.2016. Release amounts to 1 tmcft; paddy raised in 14.9 L acres. Then, the inflow from U was reduced to 3000 cusecs on Wednesday evening; 21.9.2016. SC orders U to release 6000 cusec water / day for rest of September'2016. The State Govt. of U called all party meeting and had taken decision collectively; a legislative resolution was taken to defy SC order; stop release of water for agriculture (e.g. samba cropping) and water to be released only for drinking purpose.

The State Govt. of D did not call any all party meeting. This is a fresh controversy. Defiant U triggers a constitutional crisis since it is defying SC order to release 6000 cusecs per day to TN. The special legislature session is expected to adopt a resolution that SC order cannot be implemented as it is contrary to the public interest in the state U. U does not have adequate drinking water. By projecting it a legislature-judiciary confrontation, the state Govt. of U hopes to escape the charge of commitment to the court.

Many in U are concerned with the silence of the central government. The centre can not be a bystander since the issue is with the Supreme Court (SC). The PM should
take initiatives to prevent a constitutional crisis. It is his duty to protect the federal structure. The decision of the Govt. of U cannot be seen as an act of defiance but as the helplessness of a state ravaged by a court order that cannot be implemented. If U defies SC order, then there are serious risks for river sharing agreements. The tension between U and D will grow since both states are feeling pressure. Outright defiance of SC may boomerang and set an extremely dangerous precedent. SC directs to form river R board having representatives from four neighboring states U,D, Y and Z. Even in the absence of state representative, the board can take decisions by majority option. So, it is in the interest of the riparian states to nominate the members otherwise they will lose the opportunity to protect their rights.

The output of the analytics is as follows: Irrigation in state D is more than 20L acres which is now 18L acres; the same in state U is 6.5L acres which is now 15 L acres. About 80% of the annual yield from river R is utilized by the farmers of D. It has now come down to 57%. The state U was using 16% now gets 37%. The water received from U by D is 4.57 tmcft during 2010-11; 28.06 during 2011-2012; 135.77 during 2013-2014 and 76.31 during 2014-15. The major cities of U consume drinking water as 26 tmcft by city B; 6 tmcft by city E; the city C of state D consumes 7 tmcft. Present water level at X Dam : 86.94 ft; storage now 44.21 tmcft. Sharp increase in irrigated farm acreage and drinking water use in the state U has deprived D of what it considers its right share. Rainfall in D in September'2016 is high. What should be the water sharing mechanism among states U, D, Y and Z?

<figure><img src="image_19.png" /><figcaption>Figure 2.4 : Deep Barringer Crater, Winslow, Arizona; Meteriotes</figcaption></figure>

<figure><img src="image_20.png" /><figcaption>Figure 2.5 : Asteroids, Comets</figcaption></figure>

### Test Case: Astronomical Hazards

Prof. Nancy Regon is presenting a test case of astronomical hazards and explores the scope of the aforesaid probabilistic search mechanism (RPSM) to assess and mitigate those threats. The universe is basically a computer, its history is being
computed continuously (Zuse,1967). It is not possible to restrict the occurrence of
astronomical hazards; but we have try to protect our earth from total destruction.
The astronomical hazards may be really dangerous threats against the sustainability
of today's human civilization and the existence of a safe earth. This type of
probabilistic search problem is really hard to solve, it is not a trivial problem. Let us
discuss the motivation of this threat in details based on the information and images
given in figures (2.4,2.5).

*Asteroids* are the largest of space rocks; most of them circle the Sun in the asteroid belt. Many of 3000 known asteroids are only a few miles across and all of them together would weigh much less than the Moon. Ceres, the largest asteroid, is about 600 miles across; Pallas and Vesta are about 350 miles in diameter. Bright *comets* are visible in the sky only once or twice in a century and stay for many days or weeks. *Meteors* flash in the sky every night or day. Meteor flashes are known as *shooting stars*. But meteors are not stars. Meteors begin as meteoroids in the form of rock or metal that orbit around the Sun. But, sometimes meteoroids plunge into Earth's atmosphere at speeds faster than a bullet. The friction with air particles makes them glow red hot and is called *meteors*. The bright flash is seen for only a few seconds. Perhaps as many as 100 million meteoroids enter the Earth's atmosphere every day. Most are just small pieces of rock and burn in an instant; some become dazzling fireballs and fall to the earth surface called *meteorite*.

<figure><img src="image_21.png" /><figcaption>Figure 2.6 : Structure - Astronomical Hazards Detection System</figcaption></figure>

*Problem of astronomical hazards* : Will an or large number of asteroids or a large meteorites ever hit Earth? Many large objects had hit our earth in the past and resulted huge hollows in the ground known as *impact craters*. The largest is the 4150 foot wide and 600 foot deep Barringer Crater near Winslow, Arizona. Is there any probability of mass destruction of human civilization and the earth due to the strike of a comet or the shower of numerous large meteorite or asteroids in future? How to protect our earth from the threat of such type of astronomical hazards? One
possible solution may be the real-time probabilistic search. The basic objective of the search is to detect the motion of the asteroids, meteors and comet moving dangerously towards the earth in terms of distance, time and size of the objects. The target's position may be uncertain or there may be incomplete information about its size and location. The automated light beam search is expected to be conducted with various types of sensors such as telescopes and satellites. The detection function gives the probability of detection for a search as a function of effort (e.g. search area, distance, time) and evaluates the effectiveness of search efforts in terms of probability of detecting the incoming objects.

**Real-time Probabilistic Search Mechanism (RPSM<sub>ah</sub>) :**

**Agents:** System administrator (Space Research Organization), Human agents;

**Input:** Data stream sensed by the sensors, Rough definition of target, Detection function;

**Output:** Identify objects or moving targets such as asteroids and meteors coming very near to the earth within threshold distance;

**Moves:** Real-time search, group testing, adaptive secure multi-party computation, automated data stream mining by intelligent threat analytics;

**Procedure:**

Divide the search space into a set of private blocks;

Assign resources (sensors, satellites, earth station) to each private block; each block is monitored independently; /* the resources of different blocks interact with each other through coordination mechanism and secure broadcast communication protocol (Internet) */;

Project light beam from the sensors on private search space → move forward and backward repeatedly;

Filter data stream;

Detect target → verify correctness to avoid false alarm → call threat analytics → give alert.

**Risk Mitigation Strategies:**

* **Proactive security** (Before astronomical hazards):

* Learn drop-cover-hold

* Have an emergency kit ready and always carry (if possible).

* Build a disaster proof house as per the advice of structural or civil engineering consultant; repair deep cracks on ceilings and walls of the house; fix shelves securely to the walls, avoid heavy loading of the rooms.

* Safe shelter : (a) build artificial caves at critical locations in urban and rural zone; (b) build robust shed on the roof made of steel (Fe) / Al / Tin (Sn) structure;

* Wear robust helmets and jackets

* Give alert through broadcast communication → take safe shelter in time;

* **Adaptive security:**

* Laser beam projection for object decomposition after detection of incoming objects through probabilistic real-time search;
* Artificial *collision* of asteroids and meteors, network *traffic congestion* or *traffic diversion* in space

* Activate *Antenna* for blocking and throttling (i.e. slowing speed) of incoming objects entered into the earth based on the principle of electromagnetic induction;

* Divert the traffic to the desert or remote zone to minimize the negative impact of astronomical hazards.

* During astronomical hazard

* Remain calm and do not panic.

* Take shelter under a table, cover head with hands and hold the table till the hazards last;

* If you are outside, move towards buildings, trees, walls and poles and take shelter;

* If you are inside a vehicle; pull over in a covered place and remain inside.

* After astronomical hazards

* Avoid entering damaged civil infrastructure (residential flats, office buildings, industrial plants).

* Use stairs instead of lifts and elevators.

* If trapped in rubble or damaged infrastructure, sound whistle, clap or shout, avoid lighting matchstick, turn on search lights of mobile phones, tap on a pipe or a wall safely.

**Adaptive security & dynamic data management**: Our earth may face various types of threats from both external and internal environments but it should be vigilant and protected through a set of intelligent security policies, protocols and mechanisms. An emerging technology demands the support of an adaptive security architecture so that the associated system can continuously assess and mitigate risks intelligently. Adaptive security is a critical feature of a technology that monitors the space in real-time to detect any anomalies, vulnerabilities or malicious traffic congestion. If a threat is detected, the technology should be able to mitigate the risks through a set of preventive, detective, retrospective and predictive capabilities and measures. Adaptive security analyzes the behaviors and events of the space to protect against and adapt to specific threats before the occurrence of known or unknown types of astronomical hazards. Adaptive security monitors the space in real time to detect anomalies, malicious traffic and vulnerabilities. If a threat is detected, it is essential to counter the threat in various ways. Preventative capabilities allow to create infrastructure, products, processes and policies that can mitigate the astronomical hazards. The detective capabilities should identify those threats in time at minimum impact and not detected by preventative capabilities. Retrospective capabilities should perform in-depth analysis of threats not detected by the detective layer to avoid such types of attacks in future. Predictive capabilities provide alerts about external events and anticipates new types of threats.

Let us consider the technology associated with adaptive security and dynamic data management for the protection of our earth. Today, it is essential to deploy adaptive security architecture for real-time moving target search. A smart grid
demands continuous monitoring and remediation; traditional ‘prevent and detect’ and incident response mindsets may be not sufficient to prevent astronomical hazards. Adaptive security is an essential part of solar computing. It is required to assess as-is system administration strategies, investment and competencies; identify the gaps and deficiencies and adopt a continuous, contextual and coordinated approach. For example, prevention and detection are traditional approaches to the security of our earth. In today’s universe of expanding threats and risks, real-time system monitoring is essential to predict new threats and automate routine responses and practices. Advanced analytics is the basic building block of next generation security protection which should be to manage an enormous volume, velocity and variety of data through AI and machine learning techniques for the protection against astronomical hazards.

Dynamic data management is an effective way to move towards adaptive security architecture. DDM surfaces anomalies and adjusts security controls proactively in near real-time to protect our earth. Adaptive Security with dynamic data management is expected to offer many benefits over traditional security platforms : real-time monitoring of events and traffic; autonomous and dynamic resolutions; prioritization and filtering of security breaches; reduction of attack surface and impact or damage of a threat and reduction of resolution time. This technology is expected to adapt to the needs of the system irrespective of the size of network, nature of operation or exposure of threats. It can assess the requirements of the security of our earth with greater accuracy through a set of intelligent policies and procedures and can ensure better understanding of strength, weakness, opportunities and threats of the security architecture.

# 5. STRATEGY

## Strategy Analytics

Agents: System analysts, business analysts, scientist, engineers, technology management consultants;

Strategic moves

* Call deep analytics ‘7-S’ model; explore how to ensure a perfect fit among 7-S elements (scope, system, structure, security, strategy, staff-resources, skill-style-support);

* Define a set of security goals and emerging technologies accordingly.

* Do technology life-cycle analysis on ‘S’ curve : presently at emergence phase of ‘S’ curve.

* Explore technology innovation-adoption-diffusion strategy.

* Explore innovation model and knowledge management system for creation, storage, sharing and application of knowledge.

* Adopt ‘4E’ approach: envision, explore, exercise and extend.

Prof. Gramy Woods and Prof. Helen Fisher are presenting on strategy of technology innovation, adoption and diffusion of emerging technologies against natural disaster. The expert panel have explored a set of interesting strategic moves for the innovation, adoption and diffusion of emerging technologies to tackle various types
of natural disaster. It is essential to innovate dominant design of intelligent systems, machines and tools at optimal cost. Most of the technologies are at emergence phase of S-curve. The expertpanel are analyzing strategy of emerging technology innovation in terms of R&D policy, learning curve, SWOT analysis, technology life-cycle analysis and knowledge management. An intelligent R&D policy should be defined in terms of shared vision, goal, strategic alliance, collaborative, collective and business intelligence. Top technological innovations are closely associated with various strategies of learning and knowledge management, more specifically creation, storage, transfer and intelligent application of knowledge. It is essential to analyze strength, weakness, opportunities, threats, technological trajectories, technology diffusion and dominant design of this innovation today.

Rain plays an important role in global economy and the yield of agriculture. But, it is a natural phenomenon and it does not fall as and when we need it. Triggering rain on demand is an old dream of mankind, with a huge potential socio-economical benefit. It is an interesting research agenda to do SWOT analysis on various methods of artificial rainfall. Traditionally, artificial rainfall is created through cloud seeding method by spraying different chemicals such as silver iodide, calcium chloride or sodium chloride from the aircrafts in the cloud region. Nucleation starts on these chemicals, which lead to the precipitation and then rain. This process has been experimented in South Africa, Thailand, Japan, Mexico, Brazil and some parts of India. The reliability and consistency of the method is low; the risk of failure is high; the cost is also high; it may have negative impact on human society, plants, animals and nature from the perspective of environmental pollution since sprayed chemicals come to the earth along with the rain. Laser induced rainfall is comparatively more economical and reliable method having less pollution and applicable to both white and black clouds. But it is a new method based on the research that self-guided ionized filaments generated by ultra-short laser pulses are able to induce water-cloud condensation in the free, sub-saturated atmosphere at altitude between 45 and 75 m. In this method, a high power pulse laser creates a bunch of filaments or low resistance path between lightning cloud and the earth.

The fifth element of deep analytics is strategy. This element can be analyzed from different dimensions such as R&D policy, shared vision and goal, learning curve, technology life-cycle analysis, technology diffusion and knowledge management strategy. At present, the technology of artificial rainfall is at emergence phase of S-curve. We need fast diffusion of this technology globally to fight against flood and droughts. It is possible to explore different strategic moves for efficient water management; this is basically a natural resource planning (NRP).

* Natural rainfall control through green plantation, conservation of forests and rational rural and urban development planning against building of concrete jungles by cutting trees and plants at mass scale;

* Artificial rainfall such as weather modification, rain enhancement through cloud seeding, glaciogenic seeding, hygroscopic seeding and laser induced rainfall;

* Transportation of water by rail and truck to the zone with water scarcity;

* Save water bodies through pollution control;

* Develop smart water grid and irrigation system;
* Rational storage, distribution, recycling and reuse of water;

* Demand and supply management through capacity utilization, drainage system, water irrigation system and smart water grid;

* Collaborative intelligence in water sharing among multiple entities (e.g. districts, states, countries).

* Intrusion and migration control of refugees

* Restrict wastage of water in swimming pools, water parks, luxurious use of air conditioners and air coolers, by the rich and super rich classes; tap at roadside, leakage from pipelines and construction works.

**Save water bodies**: It is essential to adopt multi-dimensional strategies to save existing water bodies such as intelligent and rational capacity utilization of water from both artificial and natural rainfall; efficient water storage in lakes, ponds, reservoirs, water distribution channels and canals; desalination of sea water; restrict wastage of water in swimming pools, water parks, luxurious use of air conditioners and air coolers, by the rich and super rich classes; tap at roadside and leakage from pipelines; conservation of water to tackle flood and drought, water pollution control (e.g. tube well equipped with water purifier, filter at pumping stations), cleaning of drainage system and riverbed deepening, mutual agreement and dialogue, restriction of illegal encroachment of water bodies, dredging of rivers or canals, collaborative planning, forecasting and replenishment and banning restriction on natural flow of water in river, canals, seas and ocean across borders or boundaries.

**Demand & supply management**: It is essential to estimate the gap between demand and supply of water for a specific zone (e.g. district, state, country). The demand plan is estimated considering various application domains such as agriculture, industries (e.g. manufacturing plants, retail outlets, life-science industry), construction projects, energy (e.g. power plants), drinking water consumption (e.g. mineral water, fruit juice, beverages, soft drinks), cooking food, washing and cleaning of bodies, garments and cars, religious and cultural events (e.g. marriage, parties), entertainment (e.g. swimming pool, sports and games events, infrastructure and ground maintenance), service sector (e.g. education institutes, student's hostels, healthcare institutes, hospitals, offices of private and public sectors, banks and financial services, communication, IT firms, travel and hospitalities, hotels, restaurants) and miscellaneous purposes like transport and logistics services, workshops, seminars, conferences, administration and governance. The supply plan is estimated based on real-time data on natural and artificial rainfall, inflow and outflow of water in a river, availability of water in the reservoirs, wastage or loss due to pollution and disposal of water through drainage system.

**Collaborative intelligence**: Let us first explain the problem of resource allocation and sharing among multiple entities. It is basically a problem of supply chain management. Let us first consider the concept of supply chain in manufacturing sector. Then, the concept can be extended to river water sharing mechanism. Typically, a supply chain is a network of organizations that satisfies the demand of
ultimate customers by producing values in the form of products and services. Supply chain management is a novel management paradigm; the basic objective is to improve the competitiveness of the supply chain and to fulfill ultimate customer demands by integrating a network of organizational units through systematic coordination of material, information and financial flows. A supply chain includes all the stages involved directly or indirectly in a business process - suppliers, manufacturers, distributors and customers. Each stage performs different processes and interacts with other stages of the supply chain; there is a flow of material, information and funds between different stages. The ultimate objective is to maximize the value, which is measured in terms of the difference between revenue generated from the customer and the overall cost across the supply chain. In case of river water sharing, a supply chain is a network of upstream and downstream states or countries that satisfies the demand of water of consumers (e.g. agriculture, industrial plants, common people). It is essential to integrate and coordinate the flow of water among various entities through appropriate infrastructure such as distribution channels, irrigation system, dams, storage and drainage system.

Integration of organizational units and coordination of flows of material, information and funds are the basic building blocks of supply chain management. A lack of coordination occurs if information is distorted as it moves across the supply chain or if different stages of the supply chain focus on optimizing their local objectives. The phenomenon in which demand variability is amplified as one moves up the supply chain is known as Bullwhip effect. There are five main causes of Bullwhip effect – error in demand forecasting, high lead-time, batch ordering, supply shortage and price variations. This problem moves the partners of the supply chain away from the efficient frontier and results in a decrease of profitability and quality of service. It is essential to define frameworks for tighter integration and improved coordination of business processes along the supply chain. Successful integration depends on three factors - choice of partners, inter-organizational collaboration and leadership. Effective use of information and communication technology, integration of advanced planning system and enterprise resource planning (ERP) system and process orientation ensure improved coordination of flows in the supply chain. There are various domains of resource allocation in real world such as river water sharing among various states or countries, bandwidth allocation in communication sector, energy flow in a smart grid, budget allocation and typical supply chain management in manufacturing and retail industry. Let us explore how to extend the aforesaid concept of supply chain management to river water sharing between upstream and downstream states. In case of river water sharing, a lack of coordination and disputes occur if information is distorted as it moves across the supply chain or if different stages of the supply chain focus on optimizing their local objectives of demand and capacity utilization. For example, an upstream state may be reluctant to share water with the downstream state.

Collaborative intelligence is an emerging field of artificial intelligence which is focused on human computer collaboration. It is the basic building block of the proposed resource sharing mechanism. Let us first define collaborative intelligence. It supports supply chain collaboration. Collaborative planning, forecasting and replenishment (CPFR) is a strategic tool for comprehensive value chain
management of an organization; this is an initiative among all the stakeholders of
the supply chain in order to improve their relationship through jointly managed
planning, process and shared information [4]. The ultimate goal is to improve a
firm's position in the competitive market and the optimization of its own value
chain in terms of optimal inventory, improved sales, higher precision of forecast,
reduced cost and improved reaction time to customer demands. Information
technology allows supply chain partners to interconnect, but trust is also important.
The interplay between trust and technology encourages the commitment of
collaboration among the organizations. The partners of a supply chain are often
reluctant to share their private information. What has remained the open issue is
how privacy can be ensured in exchange of strategic information for collaborative
supply chain planning. In case of river water sharing, supply chain collaboration is
essential for efficient demand and supply management.

Collaborative intelligence is achieved through multi-party negotiation. Negotiation
is a means for a group of decision-making agents to reach mutually beneficial
agreements through communication and compromise. It is an important conflict
management and group decision-making technique by which a joint decision is
made by the agents who cannot achieve their objectives through unilateral actions.
They exchange information in the form of offers, counter-offers and arguments and
search for a consensus. A wise agreement resolves the conflicting interests of the
community fairly and is durable. Negotiation methodology has two key components
– negotiation process and negotiation protocol. Multi-party negotiation is a group
decision-making process having five distinct phases. The negotiation process starts
with the planning phase. The agents initiate several joint activities by specifying
their objectives, preference, aspiration and reservation levels and communication
mode. Next, they set various agenda such as negotiation protocol, the timing of
exchange, deadline, priorities and constraints. Then, they exchange offers and
arguments; learn about the limitations of other agents; identify the areas of
agreement and disagreement and modify negotiation strategies. Next, they develop
joint proposals by relaxing their individual limitations and reach an agreement.
Finally, the agents analyze the compromise proposals at conclusion phase and may
explore the scope of possible improvements.

The negotiation protocol is a formal model which defines a set of rules to govern the
processing of a negotiation support system and related communication and specifies
permissible inputs, assumptions, actions and constraints. A protocol can be
evaluated on the basis of different perspectives such as computational efficiency,
communication efficiency, individual rationality, distribution of computation and
pareto efficiency. Distribution of computation is necessary to avoid the problem of a
single point of failure. An efficient negotiation mechanism enables the agents to
reach a Pareto optimal solution by decreasing the cost of negotiation.

Negotiators are the decision-making agents involved in the negotiation process; the
other interveners are mediator, arbitrator, facilitator and rules manipulators. The
mediator acts as an impartial agent and guides the negotiators to reach an
agreement. The arbitrator may generate a solution on the basis of facts and
arguments; the rules manipulator can alter the rules of the negotiation.
Collaborative intelligence in resource allocation is associated with efficient collaborative supply chain planning. Planning is defined as a rational, structured decision making process which aims to find the best choice of objectives and measures to a decision situation and its environmental setting. The coordination of operations along the supply chain requires well structured planning processes. In case of collaborative supply chain planning, two or more local planning domains collaborate through sharing of relevant information in order to create a common and mutually agreed upon plan. It has five strategic moves - domain planning, data exchange, negotiation & exception handling, execution and performance measurement.

Collaborative intelligence is associated with efficient and intelligent supply chain contract such as swing option. Swing option is a specific type of supply contract in trading of stochastic demand of a resource. It gives the owner of the swing option the right to change the required delivery of resources through short time notice. It gives the owner of the swing option multiple exercise rights at many different time horizons with exercise amounts on a continuous scale. A typical swing option is defined by a set of characteristics and constraints. There are predefined exercise times $t_i$, $i \in [1, 2, ..., n]$, $1 \le t_1 < t_2 < ... < t_n \le T$ at which a fixed volume of $d_0$ units of computational resources may be obtained. With a notice of specific short period, the owner of the option may use swing right to receive more (up-swing) or less (down-swing) than $d_0$ at any of $n$ moments. The scheme permits swing only at $g$ out of possible $n$ time moments where $g \le n$ is swing number constraint. A freeze time constraint forbids swings within short interval of the moments. The local constraints up-swing [$\alpha$] and down-swing limits [$\beta$] define how much the requested demand $d_i$ at time $t_i$ may differ from $d_0$. There are two global constraints which restrict the total requested volume $D$ within the contract period by maximum total demand ($\gamma$) and minimum total demand ($\lambda$). The option holder must pay penalty determined by a function $\rho$ for violating local or global constraints. The next section outlines Resource Sharing Mechanism (RSM) based on collaborative intelligence and then applies the concept to a test case of river water sharing dispute.

## 5.1 Case Study – Wild Bushfire

Prof. Bush and Prof. Alan Border are discussing the following case study. Is it possible to validate the rationality of various strategic moves to control wild bushfire globally? Is it possible to extend this study to tackle the disaster of volcano also?

There was a wild bushfire in Australia in December’2019 - 28 people dead; 3000 animals dead; is it not a natural disaster and emergency catastrophe? Is it possible to exercise a crazy, wild brainstorming session on the above globally and adopt a multi-objective set of moves to tackle the fire so hot so big so dangerous so awful?

* Artificial rainfall i.e. slow, steady, substantial shower to extinguish wild bushfire

* Laser induced rainfall

* Cloud seeding using the concept of cloud physics

* Artificial increase of humidity of air
* Is it possible to divert direction of strong wind causing fast spreading of bushfire?

* Is it possible to deploy real-time sense-and-respond system for automated smoke detection?

* Prediction of wild bushfire: is it possible through broadcast, satellite and mobile communication system (e.g. RFID, GPS)?

* Collaborative intelligence in technology and operations management

* Multi-party collaborative resource sharing in terms of man, machine, material, method and money for automated fire extinguishing system (e.g. spraying CO2, foam etc.)

* Design of fire-proof houses having sufficient distance from forests, storage facilities for harvesting rain and ground water, avoiding combustible building materials such as wood, coal and paper, equipped with effective fire extinguishing system, use of solar water pumps, emergency exit passage.....

* Call Threat Analytics :

* Cause-effect analysis on wild bushfire:

* Is it a natural disaster caused by the friction between branches of trees and strong wind?

* Lightning strike – lightning arrester, cactus plants;

* Is it a manmade disaster due to use of fossil fuel by tribal people (e.g. coal, diesel, petrol, fireworks) beside forest, bushes and wood?

* Is it an act of bio-terrorism (refer: Amazon forest fire in 2019 for exploration of oil and gas)?

* Effects :

* Fall of air quality causing health hazards and quality of life

* Damage of assets, properties

* Death of life

* Environmental pollution

* Negative impact on farming, travel and tourism, events (e.g. sports)

* Risk assessment and risk mitigation through evacuation or migration of human civilization from wild bush fire prone zone

* Collective intelligence in timely rescue operation and total evacuation from risky zone through deployment of forest workforce, natural disaster management workforce, security work force and army;

* Development of wild-life sanctuaries and national parks in existing forests; re-engineering of forests; eliminate the concept of 'zero forest' i.e. 'no bushes, no bushfire';

* Distribution of food, water and beverage to the victims and fire affected animals through mobile patrols;

* Strategic alliance in sharing of manpower and brain power trough UN climate change council, World economic forum and innovation councils (e.g. NASA);
* Countermeasures against climate change, extreme weather conditions and global warming (1°C increase each year) by adoption of solar power and electrical and hybrid vehicles; organized movement and public campaign;

* Common sense public awareness development through intelligent knowledge management system such as broadcast (free from fake news, lies and conspiracy theory, disinformation campaign);

* Ensure a perfect fit among scope, system, structure, security, strategy, staff-resources and skill-style-support.

## 5.2 Case Study – Epidemic & Pandemic

Dr. Han and Dr. Gatting are analyzing the following case study. Is it possible to adopt a set of intelligent strategic moves rationally to fight against epidemic and pandemic outbreak globally? The basic objective is to develop an *artificial immune system*. The objective of the strategic moves is not to create any unnecessary panic. Rather, we need a rational, optimal mix of proactive and reactive or adaptive approaches for epidemic control in time. It is essential to formulate an intelligent and rational global security policy.

* Use *alternative workplace* and work from home.

* Block supply chain (e.g. food chain, retail chain);

* Block HR chain

* Inflow of agents (e.g. students, researchers, traders, tourists) from foreign countries to the centre of epidemic

* Outflow of agents from the centre of epidemic to foreign countries

* Social distancing : which is correct practice – social distancing or physical distancing?

* Contact isolation (e.g. man to man, man to animals), pressure isolation, use of masks, /* use of masks for long duration may result respiratory problems as individuals intake CO2, the byproduct of their own respiration */

* Socially responsible initiatives: socially etiquette and responsible behavior: hand shaking, coughing and sneezing, use of handkerchiefs and shoes; Precautions in washing raw meat and cooking meat (e.g. beef, chicken, pork, mutton, cockroaches, snakes, pangolins); restrict spitting on roadside, use of UV light inside room;

* Quarantine of virus infected agents in special camps;

* Border seal between neighboring countries;

* Restriction on logistics i.e. transport through surface (e.g. car, bus, truck, train, metro rail), water (e.g. ship, steamer, boat) and air (e.g. plane, chopper, helicopter);

* Flaws in scanning and detection of infection by *thermal scanners* at ports and air ports:

* False positive and false negative errors;

* Lock down infected cities;

* Develop AIS (*Artificial Immune System*) based on

* Danger signal sensing
* Self-nonself classification

* Clonal selection :

* Hotspot

* Containment area /* Home delivery of medicine, food and essential items; shop and market shut down, total lockdown */

* Cluster: red, orange and green zone; /* based on spread of infection rate, number of testing, feedback of inspectors and high population density in slum area */

* Micro-planning

* Medical precautions :

* What is the method of diagnosis and trial at mass scale!

* Use of mask (e.g. normal, N95, N97), hand gloves, gowns, jackets; cleaning agents to wash hands and faces frequently, /* Is use of mask safe for human health? An agent may inhale CO and CO₂ which are byproductcts of own respiration blocked by mask. */

* Pathological test of saliva, nasal secretion, blood, urine, stool of suspected agents,

* PCR (Polymerised Chain Reaction) : Step 1 - Pan Corona PCR; Step 2- N Covid test /* Severe acute respiratory illness, fever, cold cough or influenza*/

* Pool Polymerize Chain Reaction (PPCR) /*To test the spread of infection in orange and green zone*/

* Rapid Antibody Test : Influenza infected agents in Hotspot zone;

* Nonavailability of good quality test kits and masks; quality problems of masks;

* Overpopulation and high population density in urban slum areas;

* Comorbidity : High risk of death of patients of critical diseases (e.g. cancer, kidney failure), accidents and other mishaps;

* Is there death audit committee during epidemic outbreak?

* Precaution against mental depression (e.g. domestic violence, boring feeling and psychological tension) through yoga, free hand exercises and meditation, positive thinking, collaboration and social works;

* Nonavailability of special care for critical patients (e.g. cancer, kidney failure, dialysis, diabetes) : Assign top priority to critical care; defer plan of surgical operation of non-critical patients.

* Denial-of-Service in healthcare service due to panic of infectious epidemic and out-of-stock situation of essential medicines at retail outlets.

* Fast innovation of vaccines through collaborative R&D by skilled agents; how to ensure security and safety of healthcare professionals;
* Artificial climate change in terms of temperature, pressure and humidity for controlling spread of infection;

* Intelligent broadcast communication through radio and TV channels; caution: exaggeration and overreaction, rumors, propaganda;

* Collaborative intelligence in global scientific research and innovation, technology and operations management

* Multi-party collaborative resource sharing in terms of man, machine (e.g. use of drones for spraying disinfecting agents, medicines, food and beverages), materials (e.g. shortage of beds, medicine disinfection and cleaning agents), method and money for epidemic control;

* Call *Threat Analytics* → do cause-effect analysis on epidemic;

* Effects

* Fall of air quality causing health hazards and quality of life,

* Death of life;

* Rapid infection; uncertainty in direction of epidemic spread,

* Environmental pollution; Negative impact on industries (e.g. travel, logistics, education, retail, event mgmt.),

* Recession;

* Risk assessment and risk mitigation through evacuation or migration of human civilization from epidemic prone zone

* Collective intelligence in timely rescue operation and total evacuation from risky zone through deployment of healthcare workforce, security and transport work force and army;

* Development of quarantine camps, speciality hospitals for epidemic and infectious diseases;

* Distribution of food, water and beverage to the victims through mobile patrols;

* Strategic alliance in sharing of manpower and brain power through WHO, UN, Red cross, UNICEF and UNESCO;

* Countermeasures against climate change, extreme weather conditions and global warming (1°C increase each year) by adoption of solar power and electrical and hybrid vehicles; organized movement and public campaign;

* Common sense public awareness development through intelligent knowledge management system such as broadcast (free from fake news, rumors, lies and conspiracy theory, disinformation campaign);

* Secure multi-party interaction in G2C communication:

* Level 1 [goal setting]: Fairness, correctness, rationality, sustainability, stability, transparency (regulatory compliance vs. freedom of expression), accountability, trust, commitment;

* Who are the customers? What should be the products and service offerings? How to add real positive values in products or service offerings? How to ensure quality assurance in offerings?

* Level 2 [Multi-party corruption]: in business model innovation, goal setting, governance, policy formulation on economic affairs, budgeting and system administration, racism, conspiracy theory;

* Level 3 [System performance audit]: Reliability, consistency, stability, liveness, safety, deadlock freeness, reachability, resiliency;
* Level 4 [Malicious attacks]: Sybil, false data injection, shilling, coremelt, DoS (Denial of Service) attack, bioterrorism, medical ragging; is the corona panic really outcome of genetic engineering? /* DoS : nonavailability of beds in general hospitals and speciality clinics for epidemic patients.*/

* Level 5 [Access control]: authentication, authorization, correct identification, privacy, audit, data integrity, confidentiality and nonrepudiation;

* Ensure a perfect fit among scope, system, structure, security, strategy, staff-resources and skill-style-support in corporate governance and law and order control; coordination and integration among foreign affairs, home affairs, health and family welfare, defense and logistics ministries of all countries.

# 6. STAFF-RESOURCES

## Staff-resources Analytics

do estimation, planning, capacity utilization, allocation and distribution of '5M' resources.

* Man (human capital management [scientists, business analysts, system analysts, project managers, engineers]): talent acquisition, talent retention, training, reward and recognition;

* Machine (tools, computer hardware, software, internet);

* Material (steel, almunium, copper, building materials - cement, sand, stone, glass, wood);

* Method (process innovation for disaster management);

* Money (optimal fund allocation, project management, resource allocation, resource distribution).

Mr. Hansie Rabada and Prof. Rina Bell are presenting the need of staff and other various types of resources for the innovation of emerging technologies. Optimal planning and capacity utilization of various types of resources is essential for promoting best practice in disaster management. The expert panel have identified five critical resources for the innovation of emerging technologies for disaster management - man, machine, materials, method and money. The technologies should support process innovation in disaster operation management. It is essential to train and educate the staff on new technologies - how to operate intelligent automated machines, how to install intelligent systems in cost effective ways. The most critical issue is management of financial resources for the innovation and promotion of new technologies. It is rational to use ERP system for optimal planning and capacity utilization of resources; it is an interesting option to explore ERP system for materials management, HR management, financial and cost control for the innovation of emerging technologies.

The technological innovation related to artificial rainfall demands the commitment of creative talent from the domains of earth science, cloud physics, space research organization and ministry of water resource management. It is crucial to analyze dynamics of the technological innovation in terms of sources of innovation and roles of organizations, government and collaborative networks; fair and correct resources
allocation for effective technological evolution and diffusion, dominant design factors and commitment of creative people. Prof. Pal has recommended an intelligent resource sharing mechanism.

## Water Sharing Mechanism (WSM)

Agents: Country or state - B and S; /* There may be multiple parties i.e. countries or states involved in water treaties*/

### Input:

* Analytics for exception handling: Real-time online data on rainfall, inflow and outflow of water in a river;

* Availability of water in the reservoirs;

* Demand plan of water for agriculture, drinking and other purposes;

Output: Collaborative water resource sharing plan or delivery plan ($P^d$);

### AI Moves:

* ✓ collaborative intelligence through domain planning, data exchange among planning domains, multi-party negotiation, exception handling, delivery execution and performance measurement.

* ✓ The agents negotiate a swing option contract in terms of

- fixed base demand (d), local constraints: up-swing ($\alpha$) and down-swing limits ($\beta$);

- global constraints: maximum total demand ($\gamma$) and minimum total demand ($\lambda$);

- penalty ($\rho$) for violating local or global constraints and

- swing number constraint ($g$)

* ✓ Intelligent and rational resource capacity utilization [ Reference : section 2.3]

### Protocol:

* Develop front end agreement by forming association.

* Define joint water sharing plan.

Negotiation issues:

* primary: delivery plan;

* secondary: swing option ($d, \alpha, \beta, \gamma, \lambda, \rho, g$);

S bids its optimal delivery plan $P_o$ to B.

Set $i = 0$. Reference plan = $P_o$;

Repeat until the stopping criteria is satisfied:

Set $i = i + 1$;

B counter bids $P_i^B$ to S or S counter bids $P_i^S$ to B;

$$ N^S(t, P_{i,B \to S}^t) = \begin{cases} \text{quit} & \text{if } t > T^S \\ \text{accept offer} & \text{if } u^S(t, P_{i,B \to S}^t) \ge u^S(t', P_{i,S \to B}^t) \\ \text{counter offer} & P_{i,S \to B}^t \end{cases} $$

If both parties agree, output plan $P_f = P_i$.

B and S jointly settle the compensation plan to be given to the victim or losing party through negotiation based on final plan $P_f$ in terms of artificial rainfall, cloud seeding, glaciogenic seeding, hygroscopic seeding, rain enhancement, weather modification and water transportation by rail or truck / tanker
<figure><img src="image_22.png" /></figure>

Create demand forecast plan.

<figure><img src="image_23.png" /></figure>

Identify exceptions for demand forecast of water. Call analytics for exception handling.

* demand plan of water

* supply plan of water

<figure><img src="image_24.png" /></figure>

Collaborate and resolve demand forecast exception items.

<figure><img src="image_25.png" /></figure>

Create the replenishment of order forecast.

<figure><img src="image_26.png" /></figure>

Identify exceptions to the order replenishment forecast.

<figure><img src="image_27.png" /></figure>

Collaborate and resolve exceptions to the order replenishment forecast.

<figure><img src="image_28.png" /></figure>

Create the replenishment order.

<figure><img src="image_29.png" /></figure>

Execute delivery plan : allocate and share water.

Verification principle:

* verify security intelligence of water allocation and sharing system of the association in terms of

o rationality, fairness, correctness, resiliency, adaptation, transparency, accountability, trust, commitment, reliability and consistency;

o Revelation principle :

* authentication, authorization, correct identification, non-repudiation and integrity,

* audit quality, pollution level and volume of shared water;

* verify machine intelligence ($M_p$) in terms of safety, liveness, concurrency, reachability, deadlock freeness, scalability and accuracy.

Payment function: verify business intelligence ($B_p$) in terms of cost sharing, incentive and compensation policy.

Dr. Pal is explaining the water sharing mechanism in depth. Three different classes of agents are involved in the resource sharing mechanism: B, S and mediator (M). B and S have well-defined objective function and a set of constraints that represent their preferences over the possible outputs of the mechanism. These agents act rationally to optimize their objective functions and follow the coordination mechanisms correctly. B and S disclose their negotiated data to M. The primary responsibility of M is to ensure fairness and correctness of resource allocation and sharing.

Planning domains (Local and Global): In case of water sharing, it is hard to define a planning domain based on single or multi-objective optimization; it may be based on a valuation model. Here, B and S hold individual planning domains which are derived from their optimization models; B has a budget constraint and S has a capacity constraint. The agents try to minimize the cost of transaction. The local planning domain of B is defined through the constrained optimization problem: $\max (o^B)^T x^B$, s.t. $M^B x^B \le b^B$ where $x^B, o^B, b^B$ and $M^B$ are the vector of decision variables, the cost vector, the constraint lower bound vector and the constraint matrix for B, respectively (T: matrix transpose operation). Similarly, the lpd of S is: $\max (o^S)^T x^S$, s.t. $M^S x^S \le b^S$. Combining these two one can obtain the joint optimization problem: $\max o^T x$, s.t. $M x \le b$ where $x = x^B \oplus x^S$, $o = o^B \oplus o^S$, $M=M^B \oplus M^S$ and $b = b^B \oplus b^S$ for the entire system referred as the global planning domain. Here, x, o, M and b represent the set of decision variables, the cost or objective
function vector, the constraint matrix and constraint upper bound vector for the
global plan.

**Plan:** The plan in water sharing is basically a delivery plan of river water. It is a multi-issue negotiation. The bi-party negotiation starts with B bidding a plan P to S. S evaluates P and counter bids an alternative plan P'. B in turn evaluates P' and counter proposes yet another P" and so on. Finally, if the negotiation ends successfully, B and S accept the commonly accepted agreed plan. The negotiation for a plan consists of successive bidding cycles. In each bidding round, a plan P is bid by either B or S. A successful negotiation process consists of an initial plan followed by a series of compromise plans which culminates in a finally accepted plan.

**Plan utility:** For any plan P, the utility components of B and S are denoted by $u^B(P)$ and $u^S(P)$ respectively. These are private to the agents and will not be disclosed to the opponent, i.e. what is revealed in the negotiation process is the proposal for B and the proposal for S without any utility implications. The total utility for a plan P, $u(P) = u^B(P) + u^S(P)$, is also not revealed to either agent. The concept of utility is also used as plan cost or revenue in artificial intelligence and operations research literature.

**Local and global utility effects:** Since $P_0$ is optimal for B, $u^S(P_0) < u^S(P_i)$ for all $i \ge 1$, i.e. the utility effect for B(S) for $P_i$, $\Delta u^B(P_i) = u^B(P_0) - u^B(P_i)$. $\Delta u^S(P_i) = u^S(P_i) - u^S(P_0)$. Utility effect of B or S is also referred as local utility effect, whereas the global utility effect or total utility effect for $P_i$ is sum of the local utility effects of all the agents. This is because the objective of the coordination process is to increase the total utility, not the individual utility. However, B is entitled to ask for suitable compensation from S to compensate for the reduced utility it has to incur in $P_i$. Individual utility effects are treated as private information.

**Compensation and utility sharing:** The losing party will always ask for a compensation amount, which is at least the utility effect. The compensation negotiation has basically two purposes: i) to determine whether the current plan $P_i$ is a feasible one, i.e. whether total utility of $P_i$ has increased over the previous plan $P_{i-1}$ (or any other past plan $P_j$, $j<i-1$); and ii) to determine how the increased utility to be shared between B and S. This is known as utility sharing.

**Utility implication:** Utility Implication of B for a plan P denoted $u^B(P)$ is the utility component of P, $u^B(P)$ plus the compensation settled $u_m(P)$. Similarly, the utility implication for S agent $u^S(P)$ is determined. The total of utility implications for B and S is same as the total utility for the plan, $u(P)$. Thus, $u^B(P) = u^S(P) + u_m(P)$; $u^S(P) = u^B(P) - u_m(P)$; $u(P) = u^B(P) + u^S(P) = u^B(P) + u^S(P)$.

**Compensation negotiation and rational behaviors of the agents:** Incentive or compensation negotiations are realistic. The agents behave rationally. If the total utility increases, compensation will always be settled such that no agent loses compared to the previous round. In other words, the utility implications for both parties improve. Further, if the compensation negotiation fails, it only means that the total utility for the current bid is less than that for the previous bid. When the negotiation ends successfully in the final plan $P_f$, the total utility achieved is nothing but $u(P_f)$. The total improvement of utility through the negotiation will be $u(P_f) - u(P_0)$, which is apportioned as $u_m(P_f)$ for B and $u(P_f) - u(P_0) - u_m(P_f)$ for S. Both
B and S are assumed to be rational in exchange of truthful communication and are interested in reducing total plan utility. If none of parties respond then there will be a deadlock. That means that neither B nor S is interested in utility improvement, which violates our assumption. Privacy preservation of individual agents is an important concern for this cooperative game. For this purpose, the utility effects are compared privately. Because the utility effects are kept secret from the respective opponents, the compensation negotiation becomes relevant and the parties feel encouraged to participate in this negotiation. It may be a single or multi-issue negotiation.

*Payment*: The buying and selling agents disclose the pricing, compensation and delivery plans to the mediator. The mediator checks the authenticity of the identities of the agents and regulatory constraints such as ceiling, consent and sustainability clauses; verifies fairness and correctness of valuation and announces penalty clauses against malafide behavior. The mediator computes payment based on disclosed data; collects payment. S collects payment from B.

*Stopping criteria*: Stopping the mechanism is possible on various counts such as stable preference matching, total negotiation time deadline, total number of plan bidding rounds and number of successive failed biddings. If any agent withdraws prematurely the mechanism ends unsuccessfully.

*Compensation*: The agents may settle compensation in various ways such as financial budget allocation or incentive sharing or unconventional ways. Let us consider the case of water sharing between two countries or states. B and S jointly settle the compensation plan to be given to the victim or losing party through negotiation based on final plan in terms of artificial rainfall, cloud seeding, glaciogenic seeding, hygroscopic seeding, rain enhancement, weather modification and water transportation by rail or truck / tanker. The upstream state requires additional amount of water for the growth and development in agriculture, industries, power plants and urban and rural planning. Its demand for water has increased and so the inflow of river water to the downstream state has reduced significantly. On the other side, the downstream state requires more water for the growth and development of urban and rural zones, agriculture and industries. The problem is severe during drought in the summer. So, how is it possible to supply more water to the downstream state – the option is artificial rainfall through cloud seeding. In this case, the compensation may not be directly related to fund allocation or financial support from the upstream to the downstream state. Actually, it is expected to be technological support for artificial rainfall. Can we think of cloud computing in the context of artificial rainfall and cloud seeding – how to control the generation and movement of cloud as per the demand of water of a specific zone?

There are several critical factors associated with fair, correct and rational resource sharing mechanism like river water: good governance, trust, positive mindset, commitment, political will, power play, corporate social responsibilities, cancer of mind, selfish ego, identity crisis and conspiracy for war. Malicious agents always try to sustain the conflict of resource sharing among multiple entities to gain political mileage, incentives from enhanced defense budget and other financial opportunities. War or terrorism may start due to conflict in water sharing. The Supreme Court is expected to act as a Trusted Third Party. A supervisory panel should be set up to
decide quantum of water release after studying online data of rainfall and flow in the river. Central Water Commission (CWC) should define a new protocol of online collection of data related to rainfall and flow of water on real-time basis. The meteorological department's rainfall data and flow into reservoirs of upstream state should match with inspected or verified data. The inflow may be artificially reduced due to unauthorized diversions by a state through various lift irrigation schemes in violation of the final order of the tribunal. It is the duty of the state government to maintain law and order.

The panel have discussed the role of staff-resources for disaster management such as epidemic and pandemic outbreak. The technological innovation on vaccines to fight against new viruses demands the commitment of creative talent from the domains of medical science operations management, managent information systems, healthcare administration and biomedical engineering. It is crucial to analyze the dynamics of technological innovation in terms of sources of innovation and roles of individuals, firms, organizations, government and collaborative networks; various resources required for effective technological evolution and diffusion, dominant design factors, effects of timing and mode of entry. Innovation demands the commitment of creative people. Creativity is the underlying process for technological innovation which promotes new ideas through intellectual abilities, thinking style, knowledge, personality, motivation, commitment and interaction with environment.

The expert panel have identified five critical resources for epidemic and pandemic control : man (e.g. healthcare staff, nurses, doctors, testing staff, government staff of ministry of healthcare and family welfare, scientists and research staffs of innovation lab), machine (e.g. testing kit, thermal scanner, healthcare infrastructure, camps, hospitals) material (e.g. cleaning agents, sanitizers, masks, gloves, medicine, jacket), method (e.g. process innovation in registration, consulting, testing, broadcasting, governance) and money (e.g. budget allocation for healthcare infrastructure development such as hospitals and quarantine camps, disaster relief fund). ‘Man’ analyzes various aspects of human capital management of technological innovations such as talent acquisition and retention strategy, training, payment function, compensation, reward, incentive, health insurance of staff and performance evaluation. ‘Machine’ analyzes the basic aspects of required test kits and medicine of optimal stock. ‘Method’ explores various aspects of process innovation, intelligent mechanism and procedure. Finally, ‘money’ highlights optimal fund allocation for R&D, rational investment analytics, intelligent project analytics and portfolio rationalization.

The technological innovation against astronomical hazards demands the commitment of creative talent from the domains of earth science, space research organization and ministry of science and technology. It is crucial to analyze the dynamics of technological innovation in terms of sources of innovation and roles of individuals, firms, organizations, government and collaborative networks; various resources required for effective technological evolution and diffusion, dominant design factors, effects of timing and mode of entry. Innovation demands the commitment of creative people. Creativity is the underlying process for technological innovation which promotes new ideas through intellectual abilities,
thinking style, knowledge, personality, motivation, commitment and interaction with environment. Natural disaster is not a trivial problem; it needs useful and novel support of creative, skilled, experienced and knowledgeable talent. Creative talent can look at the problems in unconventional ways; can generate new ideas and articulate shared vision through their intellectual abilities, knowledge, novel thinking style, personality, motivation, confidence, commitment and group dynamics.

# 7. SKILL-STYLE-SUPPORT

## Skill-style-support Analytics

* **Skill:** knowledge of operation and best practices of engineering, technical, system administration, strategic management, governance and disaster operation management;

* **Style:** leadership, shared vision, goal setting, intelligent communication, risk assessment and mitigation, innovation project management;

* **Support:** proactive, preventive and reactive support of systems, machines and tools used for disaster operation management.

Finally, Prof. Nick Jones, Prof. Gramy Woods and Dr. Hariharan are concluding the session by exploring skill, style and support as required for the innovation of emerging technologies and operation management against natural disaster. The workforces involved in such technological innovation are expected to develop different types of skills in technical, management and system administration. The workforces involved in technological innovation for epidemic and pandemic control are expected to develop different types of skills in medical science, immunology, disaster operation management and system administration, innovation on life-science, pharmacy and biotechnology, research and development, testing, tracing, tracking, benchmarked and standardized medical practice.

The workforce can develop skills through effective knowledge management programmes. An effective knowledge management system supports creation, storage, sharing and application of knowledge in a transparent, collaborative and innovative way. The diffusion of top technology innovation requires the support of great leadership style; they are not only industry leaders but also political one. The style is basically the quality of leadership; the great leaders must have passion, motivation and commitment. The leaders must be able to share a rational vision, mission and values related to the innovation among all the stakeholders honestly and appropriately in time. A traditional functionally centered organization model may not be suitable for supporting end-to-end water resource management process. The technology needs the support of a collaborative enterprise model. The stakeholders are expected to develop skills in collaborative planning, forecasting and replenishment (CPFR) practice as follows.

A) Develop front end agreement: The objective is to establish rules and guidelines for a collaborative relationship. The process steps may be as follows : develop
mission statement, determine goals and objectives; discuss competencies, resources and systems; define collaboration points and responsible business functions; determine information sharing needs (what information, frequency, technology), determine service and order commitments; determine resource involvement and commitments; define conflict resolution process; determine process for reviewing the collaborative arrangement and publish front-end arrangement;

B) Joint resource sharing plan: The basic objective is to understand each partner needs and capabilities in creating and influencing demand, manufacturing and replenishment. The process steps may be as follows: identify partner strategies; develop category roles, objectives and goals; develop joint category strategies and tactics; develop item management profiles; develop joint resource sharing plans; agree to joint resource sharing plans.

C) Demand forecast creation: The basic objectives are to create a demand forecast that will lead to the creation of the replenishment order. The process steps may be as follows: analyze joint resource sharing plan; analyze causal factors (e.g. seasonality) on demand; collect and analyze point of history or time series data; identify planned events; identify exceptions or forecast disagreements and generate the demand forecast.

D) Identify exceptions for forecast: The basic objective is to using predefined tolerances and metrics, identify exceptions in the demand forecast for collaborative resolutions. The process steps may be as follows: understand and retrieve exception criteria. identify changes and updates; update the system with constrained demand forecast; compare item values to exception criteria and identify exceptions for collaborations.

E) Collaborate and resolve demand forecast exception items. : The basic objective is to resolve exceptions to the demand forecast through collaboration. The process steps may be as follows : identify desired adjustments to the demand forecast; recommend forecast adjustments and agree on the forecast adjustments.

F) Create the replenishment of order forecast: The basic objective is to develop and communicate a time-phased projection of replenishment orders based on demand forecast. The process steps may be as follows : communicate the demand forecast, consider inventory strategies and current inventory levels, analyze manufacturer's historical replenishment performance, analyze and communicate manufacturing capacity limitations, evaluate factors affecting replenishment planning decisions, review execution performance and create order replenishment forecast.

G) Identify exceptions to the order replenishment forecast: The basic objective is to identify replenishment orders based on predefined tolerances and criteria. The process steps may be as follows : understand and retrieve exception criteria; utilize the replenishment order forecast in the sales and operational planning processes; compare the proposed replenishment order forecasts to supply and capacity; apply constraints and capacity optimization factors to the order replenishment forecast; identify exceptions items based on predefined tolerances.

H) Collaborate and resolve exceptions to the order replenishment forecast : The process steps may be as follows - identify and communicate exceptions, recommend order replenishment forecast adjustments and agree on the forecasts.
I) Create the replenishment order: The process steps may be as follows: utilize the planning system to generate and communicate replenishment orders internally and to the trading partners; the final output is the replenishment orders that are in synchronization with the demand forecast and are aligned with the joint resource sharing plan.

J) Delivery execution : Start sharing resources.

8. CONCLUSION

This session has outlined an interesting project for critical resources (e.g. river water) sharing among multiple entities rationally with fairness, correctness, transparency and accountability. It is also essential to control heavy rainfall which often results flood, landslide and soil erosion in urban and rural zone. Such type of project requires the support of deep analytics of river and irrigation engineering, water resource management and cloud physics. Rational resource sharing is basically the problem of real-time supply chain optimization.

It is also a critical research agenda to explore efficient risk mitigation strategies against heavy rainfall and flood. How can we fight against natural calamities like flood due to heavy rainfall? We need an optimal mix of proactive and reactive approaches. Intelligent urban and rural development planning is essential in terms of reliable infrastructures (e.g. houses, roads, bridges, flyover, drainage system etc.). Can we explore the concept of a 'smart water grid' to divert surplus water through pipelines, canals, rivers and drains to neighboring districts or states from flooded zone? It is rational to monitor timely release of water from various dams sequentially during rainy season; simultaneous release of water from all the dams of a state may aggravate the flood situation; it may be a conspiracy to draw flood relief fund by creating chaos through malicious artificial intelligence. Sufficient number of water storage or harvesting systems (e.g. dams) is required.

Modern, well designed networks of drainage systems should be built along with filters. Regular cleaning of drains is essential to remove mud, sand, plastic goods, polythene packets, haggis and pads to avoid congestion or jamming in rainy season. It is also required to open manholes during rain carefully monitored by municipal and cleaning staff so that there should not be water logging problems on the roads and streets. It is an interesting and feasible option to increase level of residential plots at low land using soil and bricks. Intelligent evacuation plan should be ready during natural disaster. Migration of human civilization from risky zone and fair rehabilitation is also essential. The problem should be tackled scientifically; there may be threats of false data injection attacks and rumors such as superstitions, narrow prejudices and religious curses through various broadcast communication channels. The system administrators should be alert of the readiness of natural disaster relief workforce (NDRF) and army with helicopters, choppers, life-boats and other relief equipments during rainy season. It is rational to exercise capital budgeting based on fair and correct valuation by the experts, surveys, audit and demand plan of reliable infrastructure (e.g. road, bridges, flyovers and nano-housing scheme). How can we tackle cloudbursts artificially applying the concept of cloud physics? It is an open research agenda.
It is possible to construct similar type of search mechanism like RPSM and risk mitigation strategies against the threats of geological hazards such as earthquake. For example, the risk mitigation strategies should include rational approaches in urban and rural development planning, public policy making, cautious approach and regulatory compliance on mining of earth's soil (e.g. coal, minerals, sand, gas pipeline) and construction activities (e.g. saturation in metropolitan cities, building high storied buildings without soil testing, tunnels, metro rails, irrigation projects, dams etc.), monitoring of volcanoes and landslides in hilly zones. The aforesaid type of probabilistic search problem is really hard to solve and it is also challenging to deploy RPSM in reality and seeks extensive support, coordination, planning and corporate social responsibilities from various space research organizations and earth science institutes globally. The most critical challenges involve the innovation of automated real-time search algorithm, intelligent sensors and predictive analytics, resource planning and deployment, system administration and coordination both locally and globally. Artificial intelligence is basically simulation of human intelligence. A rational reasoning system often needs the support of an intelligent analytics. An intelligent reasoning system demands new solution methodology beyond traditional knowledge base with imagination, envision, perception and proper assessment of a hard problem like the aforesaid probabilistic search.

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* A. Stenz. 1994. Optimal and Efficient Path Planning for Partially-Known Environments. IEEE International Conference on Robotics and Automation, San Diego, CA, USA, vol. 4, 3310–3317.

* A.Jaszkiewicz and R.Slowinski. 1999. The light beam search approach an overview of methodology and applications. European Journal of Operational Research, 113, 300-314.

* S.Simon. 1998. Comets, meteors and asteroids. Scholastic Inc.

* W.Du and M. J. Atallah. 2001. Secure multi-party computation problems and their applications: a review and open problems. In 2001 workshop on new security paradigms (pp. 13 - 22). ACM Press.
* Y. Lindell. 2003. Composition of secure multi-party protocols a comprehensive study. Springer.

* R.Canetti, U.Feige, O.Goldreich and M.Naor. 1996. Adaptively secure multi-party computation.

* S. Chakraborty. 2007. A study of several privacy preserving multi-party negotiation problems with applications to supply chain management. IIMC.

## Quiz

* What are various types of natural disasters? What are the negative impacts of such disasters on poverty and humanity, plants, animals and nature? What is the scope of technology for global security against various types of disaster such as flood, drought, storm, earthquake, volcano, woodfire, snowfall, epidemic and pandemic outbreak, astronomical hazards, environmental pollution and attack of malicious pastes and wild animals?

/* Hints :

**Flood** : Smart water grid, Canals, Drainage system, Irrigation system, Water storage system (e.g. dams, lakes, ponds, rivers), Migration of human civilization from risky zone to favourable zones

**Drought** : Artificial rainfall, Cloud seeding, Irrigation system, Water storage system, Fertilizer and Migration of human civilization from risky zone to favourable zones.

**Storm / Cyclone** : Resiliency management, Infrastructure maintenance (e.g. energy, utilities, trees, huts, houses)

**Earthquake** : Soil mining, Tunnel, Unplanned urban and rural development planning and civil infrastructure development, Migration of human civilization from risky zone to favourable zones

**Volcano** : Migration of human civilization from risky zone to favourable zones

**Wood fire** : Water jet, Artificial rainfall, Migration of human civilization from risky zone to favourable zones

**Snowfall** : Resiliency, traffic congestion

**Epidemic and pandemic outbreak**

**Astronomical hazards** : Private search

**Environmental hazards** [Air pollution (Smoke from vehicles, power plants, industrial plants (e.g. chemical, metallurgical, fertilizers, oil, gas), factories); Water pollution: cleaning of weeds i.e. kachuripana, Soil pollution: plastic, garbage, recycle and reuse; Sound pollution : fire crackers, bombs, construction works, industrial plants and factories; Sunlight pollution : Nano-housing]

**Paste / wild beasts** : Mosquitoes - Malaria, dengue, chickengunia (Mosquito net, DDT, Bleaching powder, Cleaning of garbage); Flies : food poisoning (use covers; no animal husbandries (e.g. khatals – cows, buffaloes, goats) and poultry firms in urban zone); Attacks of wild animals, Wild-life sanctuaries (e.g. tigers, loans, elephants, snakes, rhinos, hippopotamus, lions, monkeys, baboons), Conservation of forests and cleaning of bushes. */

* What is artificial immune system? How can it control epidemic and pandemic outbreak?
* What are the basic elements of system architecture for disaster control? How to represent the structure correctly?

* What do you mean by technology security for artificial immune system? How to verify the security intelligence? What is bioterrorism? How to assess and mitigate risks of bioterrorism globally?

* What are the strategic moves of technology innovation, adoption and diffusion? What is the outcome of technology life-cycle analysis?

* How to manage resources for disaster management? What should be the talent management strategy?

* What are the skills, leadership style and support demanded by the technological innovation?

* How to manage technology innovation project efficiently?

* What should be the shared vision, common goals and communication protocols?

* How can you ensure a perfect fit among ‘7-S’ elements for disaster management?

* Explain the problem of real-time moving target search? Justify it as a technology for humanity. What is the scope of this technology for the protection of our earth against astronomical hazards?

* What is the dominant design of the technology?

* What are the basic elements of the system architecture? How to represent the structure correctly?

* What do you mean by technology security for real-time moving target search? How to verify the security intelligence? What is the role of adaptive security and dynamic data management in this context? Design adaptive security architecture.

* What are the strategic moves of technology innovation, adoption and diffusion? What is the outcome of technology life-cycle analysis?

* How to manage resources in this innovation project? What should be the talent management strategy?

* What are the skills, leadership style and support demanded by the technological innovation?

* How to manage technology innovation project efficiently?

* What should be the shared vision, common goals and communication protocols?

* How can you ensure a perfect fit among ‘7-S’ elements?

* What is private search? Please do the complexity analysis of private light beam search based on multi-objective optimization?

* Construct a real-time moving target search algorithm for robot navigation. Please do the complexity analysis.

* Explain the technology of artificial rainfall? Justify it as a technology for humanity. What is the scope of this technology for the protection against drought and flood?

* What is the dominant design of the technology? Is it possible to adopt laser induced rainfall?
* What are the basic elements of the system architecture? How to represent the structure correctly?

* What do you mean by technology security? How to verify the security intelligence?

* What are the strategic moves of technology innovation, adoption and diffusion? What is the outcome of technology life-cycle analysis?

* How to manage resource sharing rationally for this innovation project? Develop a collaborative resource sharing mechanism to resolve the conflicts of water distribution among two neighboring states or countries.

* What should be the talent management strategy? What are the skills, leadership style and support demanded by the technological innovation?

* How to manage technology innovation project efficiently?

* What should be the shared vision, common goals and communication protocols?

* How can you ensure a perfect fit among ‘7-S’ elements?
<figure><img src="image_30.png" /></figure>
SESSION 3: FOOD & HOME SECURITY - SMART AGRICULTURE, NANOHOUSING, SMART VILLAGES & SMART CITIES

Event : Technology for humanity and global security summit;

Venue: Social security hall, Technology park : Sanada;

Time Schedule : 3 p.m. – 6 p.m., 15.8.2020;

Agents : Representatives of various global organizations, World bank, Global Economic forum, Technology management experts from science and technology forums, agriculture, textile, civil, structural, mechanical and chemical engineers, scientists, representatives and ministers from the departments of agriculture, consumer goods and housing.

Topic of discussion and key focus areas: Food security, home security, garments security, consumer goods security, organic farming, smart farming, agricultural engineering, nano housing, textile engineering;

Keynote speakers : Prof. Boris Zekov, Dr, Hansie Kallis, Dr. Anupam Swaminathan, Dr. Iqbal Hussain, Mr. Ronald Thomas, Dr. K. Phillips, Dr, M. Waugh, Dr, Chang

1. SCOPE

Scope Analytics

Agents: System analysts, business analysts; agriculture scientists, engineers;

Moves : Critical success factors analysis, Requirements management;

Security parameters: define a set of sustainable development goals for poverty control.

Food security : zero hunger;

* Security against climate change, flood, drought, storm, cyclone, snowfall, rainfall, bushfire, attack of wild animals (e.g. elephants), paste;

Home security : disaster proof nano-housing schema;

* Security against earthquake, fire, flood, storm, cyclone, snowfall, rainfall, attack of wild animals and insects; act of terrorism, theft;

Garments and consumer goods security;

Responsible consumption and production through optimal resource planning and supply chain management;

Prof. Boris Zekov and Dr. Chang are analyzing the above scope analytics in terms of food security, home security, garments and consumer goods security. The basic objectives are responsible consumption and production through optimal resource planning and supply chain management and emerging technologies on agriculture, housing, textiles and chemical engineering. Agricultural engineering is the engineering of agricultural production and processing through various disciplines (e.g. agriculture science, rural sociology, agriculture economics, mechanical, chemical, civil, electrical, food science); the basic objectives are to improve the agricultural productivity in terms of quantity and quality, efficacy and sustainability of agricultural practices. Agriculture is a set of specific activities
which transform the environment for the production of animals and plants for
human use.

There is scope of innovation, adoption and diffusion of emerging technologies on agricultural science, plant breeding, genetics, plant pathology, horticulture, soil science, agronomy, agricultural biotechnology, fertilizer, entomology, production techniques, irrigation management, drought resistant crops and animals, development of new pesticides, yield sensing technologies, simulation models of crop growth, minimization of the effects of pests (e.g. weeds, insects, pathogens, nematodes) on crop or animal production systems, transformation of primary products into end consumer products, production, preservation, and packaging of dairy products, prevention and correction of adverse environmental effects, soil degradation, waste management, bioremediation and agricultural biotechnology (e.g. genetic engineering, molecular markers, molecular diagnostics, vaccines, tissue culture).

## 2. SYSTEM

### System Analytics

**Agents**: system analysts, business analysts, scientists, engineers;

**Objects / entities**: sustainable smart cities, smart villages,

**Moves**: requirements engineering, system design, prototype testing, erection, installation, testing, commissioning;

**Emerging technologies**: innovate a set of emerging technologies based on global security parameters and sustainable development goals.

<figure><img src="image_31.png" /></figure>

### Food and beverage security

* Smart farming through automation and infrastructure development in agricultural engineering;

* Soil management (plough, hoe, cultivator)

* Seeding (seed drill for sowing of seeds)

* Fertilizer / manures

* organic manure (compost manure for organic firming)

* inorganic manure (N, P, K, Ammonium Sulphate)

* Irrigation (pulley, canal, bucket, Parsie wheels)

* Weeds (e.g. grass, Partheneum, Amaranthus, Chenopodium) control using weedicide

* inorganic control

* organic control

* Paste control for protection from the attacks of bacteria, fungi, virus and rats

* inorganic control (DDT, BHC, Malatheon; salts of S, Cu, Zn, P)

* organic control (using parasites and predators)

* Harvesting (thrashing, winnowing, combine harvester)

* Storage / warehousing (silo)

* Automation and civil infrastructure (e.g. warehouses) for animal husbandries (fisheries, dairy, poultry, epiculture, sericulture);
* Electrical (solar water pump);

* Mechanical (solar power enabled tractors, net, trollers);

* Biotechnology;

* Genetic engineering;

* Chemical (organic and inorganic fertilizer, pesticides);

* Food processing technology

* Digital technologies :
  * ERP-SCM system

* Supply chain planning (demand, inventory, production capacity);

* Supply chain collaboration

* Collaborative planning, forecasting and replenishment (CPFR) system

* Sourcing

* Supply chain execution

* Warehouse management system (WMS)

* Transportation management system (TMS)

* Pricing system

Home security (disaster proof nano-housing schema, roof-top solar panels, civil, mechanical, metallurgical, virtual reality);

Garments and consumer goods security : chemical (jacket, rain coats), textile, agriculture, process manufacturing, retail;

Dr, Kallis and Dr. Swaminathan are exploring the system associated with smart villages and smart cities. The key focus areas are solar water pump for agriculture and nano housing schema. They are analyzing the technology of solar water pumps. What is a solar pump and how is it different from conventional pumps? What are various types of solar water pump? What are the differences between surface and submersible pumps? Is a DC pump more efficient than AC pump? What are the advantages? What are the disadvantages such as impact of cloudy and foggy days and natural disaster? What are the basic working principles, irrigation capacity and average discharge? What is the procedure of site selection, erection, testing, and commissioning and relocation procedures of solar pump? What is the outcome of cost-benefit analysis? What are the marketing, promotion, advertising, sales and distribution strategies? What are the outcomes of technology life-cycle analysis?

<figure><img src="image_32.png" /><figcaption>Figure 3.1: Solar water pump for agriculture</figcaption></figure>
A solar water pump is a system powered by renewable solar energy [Figure 3.1]. It is used to extract water from various sources of water (e.g. lake, pond, river, borewell) for agriculture, irrigation and domestic drinking water applications (0.1-5 HP), municipal and rural community applications (15 - 100 litres of water per peak watt). For example, 2 HP and 7.5 HP pump may supply water to 2 and 10 acres of land respectively but this data may vary depending on the level of ground water and the type of irrigation required for a particular crop. A solar water pump can be used effectively for domestic application and irrigation (e.g. submersible, surface or deep well) in agriculture. It gets electrical power from solar array wherein a number of solar modules are connected in series or parallel. The array converts solar radiation into electrical energy which is controlled by a variable frequency driver and enables the connected pump to draw water from ponds, rivers or borewells and distribute the same to green fields directly for agriculture or to tanks for storage through pipeline. Solar power can be used as the energy supply of cold storage or warehouses which are generally used to store food grains, fruits and vegetables and can reduce the cost of storage and wastage of perishable items significantly.

A solar pump may be of different types such as AC/DC and submersible / surface pumps. A submersible pump is used in a borewell having water level deeper than 15 meters; a surface pump may be used in an open well, pond and water level less than 10 meter. The basic components of the system include solar panels, motor pump set, electronic controllers and inverters. Solar panels supply DC to the motor; AC pump requires an inverter to convert DC into AC. DC pumps may have higher efficiency over AC pumps and do not have inverter for operation. But, DC pumps may have constraints in terms of cost, repair and maintenance services. The discharge rate may vary 15-20 Litres of water per peak watt depending on solar intensity, location and seasonal factors.

Solar water pumps offer many advantages as compared to conventional nonrenewable energy driven pumps such as cost of fuel and maintenance, low voltage regulation, power cut and environmental pollution (e.g. air, water, soil) problems. It can be installed at remote areas; it has fewer moving parts and less chance of wear and tear; the system needs minimal maintenance like cleaning of the panels on a regular basis. It is easy to operate and do not require lubricants. But, the pump may not work effectively during cloudy and foggy days; it need to the conventional grid. Solar panels may be damaged due to hail storm, cyclones and direct lightning strike (if no lightning arrester is used). Solar panels should be installed in areas free of shade, dust and dirt; should be easily accessible for cleaning and should be as close as possible to the pump and water source. It is interesting to exercise a comparative analysis on the cost of AC and DC solar water pumps of various suppliers, subsidies and promotional efforts initiated by the state and central governments of various countries globally.

*Solar microgrid for rural electrification:* Let us consider the application of solar power for rural electrification: how solar power can illuminate the life of poor rural people. The innovative business model of solar power can save energy cost of rural people in domestic applications and agriculture. The peasants and farmers can reduce the cost of energy used in water pumps for irrigation in agriculture. It can
improve the productivity required for green revolution. A smart *microgrid* is an interesting option of rural electrification. It consists of solar panels, power condition unit (PCU), distribution box (DB), battery system and loads. Its size depends on the load estimation and the number of PV panels and rating of solar cells. The PV panels comprise of a set of solar cells connected in series or parallel; they convert solar radiation into electrical power; the power flows from PV panels to PCU or power inverter; PCU controls, regulates and directs the power to various loads (e.g. domestic load, water pumps in Greenfield). The surplus power generated in the daytime is stored in the battery bank and may be utilized after the sunset. The typical energy demand of a rural house is approximately 3 units. For a village of 100 houses, a 5 KW microgrid may be useful. It can generate annual energy of Rs. 50000. It is an approximate calculation.

## 2.2 Home Security - Nanohousing Technology

The expert panels are exploring the option of nanohousing technology to ensure home security. Nanohousing system is basically an innovative and sustainable architectural proposition based on green concept for residential use and pre-engineered structure made from cement fiberboard, recycled light gauge steel and polyurethane foam, creation of flexible spaces using suspending technology and use of renewable energy systems. This is an optimistic and environmental solution for the global housing issue of very small living spaces at affordable prices. Nanohouse may be suitable for a family of three in an area of 270 sq ft.; the suspending technology may be able to nearly double the size of the living area within this space by transforming common living space by day into two separate bedrooms by night.

## 2.3 Garments & consumer goods security

Textile manufacturing technology ensures garments security. Fibre is converted into yarn and yarn into fabric. These are then dyed or printed, fabricated into clothes. Different types of fibres are used to produce yarn. Cotton is the most important natural fibre; there is demand of other various types of products at fair and affordable price such as jackets, rain coats and sweaters. There is scope of automation at various stages of textile manufacturing: cultivating and harvesting, preparatory processes, spinning, cloth yarn, bundle, sewing thread, weaving, knitting, finishing, marketing, sales and distribution. There is scope of improvement of various processes at the spinning, fabric forming, finishing and coloring processes. There is scope of innovation and production of various types of consumer goods at economies of scale such as shoes, sandals, talc powder, soap, sanitizer, bodywash, facewash, perfume, saving cream and toothpaste through the advancement of chemical engineering, pharmacy and biotechnologies.

# 3. STRUCTURE

Structure Analytics
Agents: System analysts, business analysts;

Moves: Design and configure

* Organization structure

* Technology forums

* National level: Government, NGOs, research organizations, ;

* International level: strategic alliance among global organizations ;

* System architecture; Innovate a set of emerging technologies as per the goals of food, home, garments and consumer goods security;

* Level 1: information technology, electrical, electronics, chemical, mechanical and civil engineering;

* Level 2: Identify fundamental building blocks of information technology

* Computing schema

* Data schema: database (demand, supply, production, distribution), big data analytics;

* Networking schema: web connectivity;

* security schema

* application schema: SCM system

* Supply chain planning (demand, inventory, production capacity);

* Supply chain collaboration (CPFR, sourcing)

* Supply chain execution (WMS, TMS, pricing system)

Dr. Iqbal Hussain is analyzing the structure of emerging technologies of agriculture and nano-housing schema. He is presenting the basic architecture of nanohousing system. Nanotechnology offers various types of benefits such as optimization of existing objects, reduction in weight and volume, reduction in number of production stages, efficient use of materials, reduced need for maintenance, reduction in the consumption of raw materials and energy and reduced CO2 emissions, conservation of resources, greater economy and comfort. It is an interesting option to explore how to use steel, concrete, hard materials and glass for nanohousing schema with economy of scale; how to ensure circulation of natural light; how to use concrete and stone innovatively and how to create a sense of comfort and beauty.

The best way to address issues of energy in nanohousing schema is to use solar power. A comfortable modern design of responsive architecture must explore that the nanohousing schema should generate its own energy and create a comfortable living environment continually adapting to changing weather conditions. Energy efficient infrastructure may be equipped with solar panels and sensitive lighting systems which minimizes CO2 emissions and reduces total energy costs for the city and its inhabitants to reach zero emission. Nanohousing schema should use climate responsive design techniques such as sun shading, cross ventilation and direct evaporative cooling to reduce the need for air conditioning. Lotus effect is expected to reduce the cleaning requirement and maintenance demands.

## 4. SECURITY
## Security Analytics

**Agents**: kids, children, youth, men, women, senior people;

**Organization**: food security council of global organization, research organization;

**Verification mechanism**: audit security intelligence.

* **system design policy**: verify rationality, fairness, correctness, transparency, accountability, trust and commitment;

* **system performance**: verify reliability, consistency, scalability, resiliency, liveness, deadlock freeness, reachability, synchronization, safety (from natural disaster, war, bioterrorism, acts of terrorisms);

* **access control** in technology innovation: verify authentication, authorization, correct identification, privacy, audit confidentiality, data integrity and non-repudiation;

* **malicious attacks**: verify the risk of false data injection, shilling (push and pull) and fault injection attack;

* **corruption** in resource planning and supply chain management;

call threat analytics and assess risks of emerging technologies on agriculture, animal husbandries, nanohousing, textile and chemical engineering.

* what is corrupted or compromised (agents, design schema)?

* time: what occurred? what is occurring? what will occur? assess probability of occurrence and impact.

* insights: how and why did it occur? do cause-effect analysis on system performance, exception and alerts.

* recommend: what is the next best action?

* predict: what is the best or worst that can happen?

**Output**: security intelligence

Mr. Ronald Thomas is discussing the security of emerging technologies related to food, home, garments and consumer goods. It is essential to verify rationality, fairness and correctness of the design of the systems. It is also crucial to verify system performance in terms of reliability, consistency and safety. The systems should be developed by a set of authorized agents. It is also important to verify the risk of corruption in resource planning and supply chain management and various types of malicious attacks.

# 5. STRATEGY

## Strategy Analytics

**Agents**: System analysts, business analysts, scientist, engineers, technology management consultants;

**Strategic moves**: Focus on emerging agricultural, animal husbandries, civil, construction, architecture and textile technologies.

★ Call deep analytics ‘7-S’ model; explore how to ensure a perfect fit among 7-S elements – scope, system, structure, security, strategy, staff-resources, skill-style-support;
★ Define a set of security goals and emerging technologies accordingly.

★ Do SWOT analysis: strength, weakness, opportunities and threats of existing technologies as compared to emerging technologies;

★ Fair and rational business model innovation

▪ Who are the consumers?

▪ What should be the offering of products and services?

▪ What do the consumers' value?

▪ What is the rational revenue stream ?

▪ How to deliver values to the consumers at rational cost?

★ Do technology life-cycle analysis on ‘S’ curve : presently at growth phase of ‘S’ curve.

★ Explore technology innovation-adoption-diffusion strategy.

▪ Smart farming

▪ Automation in agriculture, animal husbandries, textile engineering

▪ Collaborative planning, forecasting and production and distribution to minimize wastage;

▪ Adoption of digital technologies such as ERP, SCM and WMS for storage, distribution and transportation;

▪ Artificial rainfall and water conservation to tackle drought;

▪ Safety from natural disasters, malicious attacks of fungi, bacteria, viruses and insects and acts of terrorism;

▪ Environmental pollution control (e.g. air, water, soil);

★ Explore innovation model and knowledge management system for creation, storage, sharing and application of knowledge.

★ Adopt ‘4E’ approach for the development of underdeveloped zone by building smart villages and optimal resource planning, allocation and distribution : envision, explore, exercise and extend.

Prof. Phillips and Dr, Waugh are exploring the strategies for the innovation, adoption and diffusion of emerging agriculture, nanohousing, textile and consumer goods technologies. The forums have explored a set of interesting strategic moves for the innovation, adoption and diffusion of emerging technologies in agriculture, animal husbandries, civil, construction, architecture and textile engineering. It is essential to innovate dominant design of intelligent machines and equipments at optimal cost. Most of the technologies are at emergence phase of S-curve (e.g. solar water pump, electrical and hybrid vehicles like tractors).

The digital technologies are at growth phase of S-curve. Commercial SCM, WMS and ERP systems are already available in COTS market. It is essential to customize these softwares as per the requirements of related sectors. It is a challenging task to develop web enabled information system to support collaborative planning, forecasting, production and distribution mechanism in agriculture. It is a hard challenge to protect the crops, food, beverage and perishable goods from natural disaster and malicious insects, viruses, bacteria and worms; these technologies are evolving with the advancement of chemical engineering, genetics and biotechnologies. Innovative strategies should be explored for conservation of water through artificial rainfall.
Dr. Waugh is exploring the strategy of organic farming, a sustainable agricultural practice based on natural ecological systems and biowastes. The other key areas are genetic engineering, biofertilization and smart sustainable agriculture. This practice avoids the use of synthetic pesticides and fertilizers; the basic objective is to sustain soil quality and health. Composting of organic residues and the use in agriculture bring back plant nutrients and organic matter to the soil; but there are risks of presence of heavy metals or organic pollutants. This strategy increases soil organic matter; enhances soil fauna and soil microbial biomass and stimulates enzyme activity leading to increased mineralization of organic matter, Na, K, P, C and improved resistance against pests and diseases.

Organic farming increases soil cation exchange capacity, improves soil structure, soil physical characteristics (e.g. aggregate stability, bulk density, porosity, available water capacity, and infiltration). But, Nitrogen mineralization takes place relatively slowly. Increased available water capacity may protect crops against drought stress. Global food crisis is coupled with the environmental impact of global warming and fuel shortages; transgenic methods may be required to enhance food production and quality. Widely used chemical insecticides (e.g. phosphine, methyl bromide) are losing their utilities due to insect resistance and environmental damage. Traditional plant breeding methods may be adopted for insect resistance. For example, transgenic Avidin, a protein naturally occurring in egg white is useful for the protection of rice, maize, potato and apple leaf from insect pests. Agriculture should be cost-effective and efficient. It is interesting to explore the scope of low cost moisture, temperature sensors for optimizing water usage and yield, and radar sensors for monitoring any invasion in the farm, smart water management and consistent monitoring for weather conditions.

# 6. STAFF-RESOURCES

## Staff-resources Analytics

do estimation, planning, capacity utilization, allocation and distribution of '5M' resources.

* Man (human capital management [scientists, business analysts, system analysts, project managers, engineers, peasants, farmers, labourer], talent acquisition, talent retention, training, reward and recognition);

* Machine (tools, mechanical [tractors, machines], electrical [solar water pumps], computer hardware, software, internet), textile machines);

* Material (seed, fertilizer, paste controllers, crops, vegetables, fruits, food grains);

* Method (process innovation for resource allocation and distribution);

* Money (optimal fund allocation, project management, resource allocation, resource distribution, loan from bank, land management, insurance);

Dr. Iqbal Hussain and Mr. Thomas are presenting staff-resources for the innovation of emerging technologies on agriculture, nanohousing, textile and
chemical engineering. Optimal planning and capacity utilization of various types of resources is essential for promoting best practice in agriculture and animal husbandries. The expert panel have identified five critical resources for green, blue and white revolution - man, machine, materials, method and money. The advancement in agricultural engineering should support process innovation in agriculture and animal husbandries. It is essential to train and educate the staff (e.g. peasants, farmers, labourers, scientists, engineers) on new technologies - how to operate intelligent automated machines, how to install solar water pump and solar microgrid, how to do maintenance and how to use materials (e.g. seeds, fertilizer, paste controllers) in cost effective ways. The most critical issue is management of financial resources for the innovation and promotion of new technologies. It is rational to use ERP system for optimal planning and capacity utilization of resources; it is an interesting option to explore ERP system for sales and distribution, materials management, HR management, financial and cost control for the innovation of emerging agricultural technologies.

# 7. SKILL-STYLE-SUPPORT

## Skill-style-support Analytics

* **Skill:** knowledge of operation and best practices of agriculture and animal husbandries, nanotechnology, civil, construction and architecture, textile engineering, technical, system administration, management, governance, supply chain management;

* **Style:** leadership, shared vision, goal setting, intelligent communication, risk assessment and mitigation, innovation project management;

* **Support:** proactive, preventive and reactive support.

The expert panel are exploring skill-style-support for the innovation, adoption and diffusion of emerging agricultural, nano-housing, textile and consumer goods technologies. The panel have identified a set of key areas for skill development such as design of agricultural machinery, equipments and structures, agricultural resource management (e.g. land), water management, conservation and storage for crop irrigation and livestock production, surveying and land profiling, climatology and atmospheric science, soil management and conservation, soil erosion control, seeding, tillage, harvesting and processing of crops, livestock production (e.g. poultry, fish, dairy animals), waste management, (e.g. animal waste, agricultural residues and fertilizer runoff), food processing technology, electrical motors, physical and chemical properties of materials (e.g. fertilizers, paste controllers), crop processing and storage, controlled environment agriculture and experiments related to crop and animal production. Innovation leaders must have shared vision, goal, communication, project management, coordination skills and rational decision making capabilities. The technical staff should have capabilities on proactive and reactive support of automated machines, equipments, tools and systems.

It is essential to develop skills in various branches of engineering such as mechanical, electrical, civil, chemical, digital technology, genetics, biotechnology
and agricultural engineering; domain knowledge of best practices and process innovation in agriculture, fisheries, poultry, dairy, poultry, epiculture and sericulture and related research and development. Agricultural engineers are expected to develop skills in planning, supervising and managing the building of irrigation, drainage, flood water control systems, environmental impact assessments, agricultural product processing, interpretation of research results and implementation of best practices. Generally, they work in academic institutes of agriculture engineering, government agencies, consulting in private engineering firms, manufacturing industries of agricultural machineries, equipments, processing technology and structures for housing livestock and storing crops and also in production, sales, management, research and development on applied science.

## FURTHER READING

* Alban C, Job D, Douce R (2000) Biotin metabolism in plants. Annu Rev Plant Physiol Plant MolBiol 51:17-47.

* http://nanolivingsystem.com

* Nayar, A., Puri, V.: Smart farming: IoT based smart sensors agriculture stick for live temperature and moisture monitoring using Arduino, cloud computing & solar technology. In: The International Conference on Communication and Computing Systems (ICCCS-2016).

* Food and agriculture organization of the United Nations.

* Wu, Q., Liang, Y., Li, Y., Liang, Y.: Research on intelligent acquisition of smart agricultural big data. In: 2017 25th International Conference on Geoinformatics, pp. 1-7. IEEE (2017).

* Wolters, S.L., Balafoutis, T., Fountas, S., van Evert, F.K.: D1.2 Research project results on Smart Farming Technology, Project coordinator: Spyros Fountas.

* Gondchawar, N., Kawitkar, R.S.: IoT based smart agriculture. Int. J. Adv. Res. Comput. Commun. Eng. (IJARCCE) 5(6), 177-181 (2016).

* Vidya Devi, V., Meena Kumari, G.: Real-time automation and monitoring system formodernized agriculture. Int. J. Rev. Res. Appl. Sci. Eng. (IJRRASE) 3(1), 7-12 (2013)

* Sen, S., Madhu, B.: Smart agriculture: a bliss to farmers. Int. J. Eng. Sci. Res. Technol. (2017)

* Alin S, Xueyuan L, Kanamori T, Arao T (1996) Effect of long-term application of compost on some chemical properties of wheat rhizosphere and non-rhizosphere soils. Pedosphere 6:355-363

* Amlinger F, Favoino E, Pollak M, Peyr S, Centemero M, Caima V (2004) Heavy metals and organic compounds from wastes used as organic fertilisers. Study on behalf of the European Commission, Directorate-General Environment, ENV.A.2

* Cook J, Keeling A, Bloxham P (1998) Effect of green waste compost on yield parameters in spring barley (Hordeum vulgare) v. Hart. Acta Hortic 469:283-286
* Cortellini L, Toderi G, Baldoni G, Nassisi A (1996) Effects on the content of organic matter, nitrogen, phosphorus and heavy metals in soil and plants after application of compost and sewage sludge. In: De Bertoldi M, Sequi P, Lemmes B, Papi T (eds) The science of composting. Blackie Academic & Professional, London, pp 457–467.

* Majeed, A (19 January 2009), Cotton and textiles - the challenges ahead, Dawn-the Internet edition, retrieved 12 February 2009

* "Machine processes", Spinning the Web, Manchester City Council: Libraries, retrieved 29 January 2009

* "Cultivating and Harvesting", Spinning the Web, Manchester City Council: Libraries, 2009

## Quiz

* What is the scope of smart agriculture and housing technology for smart city and smart villages?

* What is the dominant design of these technologies?

* What are the basic elements of the system architecture?

* What do you mean by technology security? How can You verify the security intelligence?

* What are the strategic moves of technology innovation, adoption and diffusion? What is the outcome of technology life-cycle analysis and SWOT analysis of these technologies?

* How to manage resources for innovation project of these technologies?

* What should be the talent management strategy? What are the skills, leadership style and support demanded by the technological innovation?

* How do you manage technology innovation project efficiently? What should be the shared vision, common goals and communication protocols? How can you ensure a perfect fit among ‘7-S’ elements?
## SESSION 4: EDUCATION SECURITY - EMERGING TECHNOLOGIES, POLICY, METHODOLOGIES & MATERIALS

Event: Technology for humanity and global security summit;

Venue: Education security hall, Technology park: Sanada;

Time Schedule: 2 p.m. – 6 p.m., 15.8.2020;

Agents: Representatives of various global organizations (nations, child, peace, health, bank, economic forum), Technology management experts from science and technology forums, engineers, scientists, educationists, representatives and ministers from the departments of education, human resources management, children, women and family welfare of developed, developing and underdeveloped countries, business development consultants from high technology, representatives from NGOs;

Topic of discussion and key focus areas: Education security, education methodologies, education technologies, education policy;

Keynote speakers: Prof. Diana Fisher, Dr. Thomas Merkle, Prof. S. Robinson, Prof.

Dilip Kumar, Prof. T. Mandella, Dr. M. Khalid.

### 1. SCOPE

#### Scope Analytics

**Agents:** System analysts, business analysts, scientists, engineers;

**Moves:** Critical success factors analysis, Requirements management;

**Security parameters:** define a set of sustainable development goals to ensure education security in synchronization with other security parameters (financial security, social security, nutrition, garments, healthcare, energy, communication, logistics)

**Application domains:** child education (pre-primary, primary, secondary, higher secondary), higher education (graduation, post graduation), adult education, continuity education, education for special children (e.g. learning disability, physically challenged, mentally challenged, depression, Dyslexia)

**Objectives:** Skill development

* Quantitative and verbal skills, languages (mother tongue, foreign languages), common sense economics, general knowledge, decision making capabilities, analytical and logical reasoning, vocational skill;

* Sports and games (indoor and outdoor games, yoga, meditation);

* Extracurricular activities (debate, music, dance, general knowledge, event management, social works)

* Human values (morality, attitude, behavior)

* Creativity and innovation

**Methodologies:**

* learning with fun

* simulated learning environment

* multi-dimensional education methodologies (written test, quiz, case discussion, story telling, role playing, project, research, assignments, consulting, experiment, practical lab works)
Prof. Diana Fisher is presenting the scope of education security globally. Education is fundamental building block for achieving full human potential and promoting global development. Providing universal access to quality education is the key challenge to our society in terms of economic growth, social justice and equality, scientific advancement, national and global integration and cultural preservation. Universal high quality education is the best way forward for developing and maximizing rich talents and resources for the good of the individual, the society, the country and the world. Our ability to provide high quality educational opportunities to the young community will determine the future of our world. The global education development agenda is to ensure inclusive and equitable quality education and promote life-long learning opportunities for all. Such a challenging goal demands fundamental rethinking and radical redesign of global education system. It is important to solve a set of critical fundamental problems to implement global education policy effectively?

* What is the *scope* of global education policy: What is the goal and shared vision?

* Education for all : discriminately or non-discriminately?

* Education is a life-long learning process (child education, adult education, continuity education, education for special children).

* Contribute, contribute, contribute: apply knowledge rationally, analytically, logically with positive attitude.

* Reduce the weight and load of schoolbags anyway by how or by cook!

* What is the design of to-be flexible education system? What are the gaps, loopholes and open points of as-is education system?

* What is the *structure* of future education system and the regulator for effective creation, storage, transfer and application of knowledge?

* How to ensure and verify the *security* intelligence of future education system?

* What is the *strategy* of knowledge management in education policy? What is the strategic roadmap to implement a rational education policy? How to explore collective intelligence, collaborative intelligence, machine intelligence, business intelligence (i.e. corporatization / commercialization of education) and security intelligence concurrently?

* What are the criteria of *staff-resources* fit for the education policy: man, machine, material, method (i.e. process innovation) and money (fund)? What are the optimal mix of education methodologies, right education materials and fund allocation protocols?

* What are the *skills, style* (TQM: Total Quality Management) and *support* essential to implement the education policy? What should be the right education technology?

## 2. SYSTEM

System Analytics
Agents: System analysts, business analysts, technology management consultants, scientists, engineers;

* *Moves*: requirements engineering, system design, coding, prototype testing, erection, installation, testing, commissioning;

*Emerging technologies*: Innovate a set of emerging technologies based on education security (digital technology, information technology, electrical, electronics, telecommunication, chemical, mechanical, civil);

* Electronics and telecommunication (smart phones, mobile phones, smart boards, projectors, Internet, digital library, e-books, printer, xerox machine, phones, fax, projectors); Digital technology (computer, tablets);

* Electrical (power system, solar power at academic institutions, solar microgrid)

* Mechanical (furniture, pipeline, Physics lab, geometry box, engineering drawing tools [scale, T], engineering lab);

* Chemical (chemistry lab, paper, pen, pencil, rubber, cutting tool, bag, shoe, socks, shirt, trousers, whitener, paint color, color pencils);

* Bio science lab (botany lab, zoology lab, human physiology lab, genetics lab, biotechnology lab, biomedical lab);

* Civil (building, road, gym, playground, car parking space);

* Metallurgy (steel structure, glass, wood, aluminum, tin)

* Technology for multi-dimensional education methodology (practical lab works, projects, case discussion, consulting assignments, research assignments, written test, quiz, supervised and unsupervised learning to avoid rote learning, vocational training for skill development)

Dr. Thomas Merkle, Prof. S. Robinson and Prof. Dilip Kumar are presenting the essential features of future education system. The human society is undergoing rapid changes in the knowledge landscape with advances in applied arts, science and technologies. The evolution of technologies for humanity, business analytics, data science, soft computing, AI, law, security, management, medical and social sciences is redefining the skill of global workforce and job profile with multidisciplinary abilities. The learners must not only learn but more importantly learn how to learn effectively. The traditional obsolete dead methods of rote learning must be rejected. The future generation education system is expected to reduce mental stress and information overloading and should promote intelligent learning mechanisms: how to think critically and solve problems rationally, how to be creative, innovative and multidisciplinary, how to innovate, adapt and absorb new technologies ans how to gain satisfactory and value adding job opportunities. The education system is expected to be experimental through intelligent laboratory activities, holistic, integrated, inquiry driven, discovery oriented, learner centred, interactive discussion based, flexible and interesting. It is a challenging task to grow interests among the learning communities through innovative education methodologies and materials. The education system should also promote culture, ethics and moral values through extracurricular activities such as sports and games, yoga, meditation, music, dance, debate, applied arts and crafts. The education system
must be associated with logical, analytical, rational, intelligent and caring academic community.

## 3. STRUCTURE

### *Structure Analytics*

Agents: System analysts, business analysts;

Moves: Design and configure

* Organization structure

* Education forums

* National level

* Government, NGOs, research organizations,

* ministries of education and human resources (school education, higher education);

* Regulator having a *cellular structure* having different cells (science, engineering & technology, management science, medical science, law, arts)

* International level: strategic alliance among global organizations;

* System architecture; Innovate a set of emerging technologies as per the goals of education security;

* Level 1: information technology, electrical, electronics, chemical, mechanical and civil engineering;

* Level 2: Identify fundamental building blocks of information technology (computing schema, data schema [e-books, digital library], networking schema (internet), security schema, application schema [software])

Dr. M. Khalid is trying to explore the gap between the current state of learning outcomes and what is required in future. It is essential to adopt a set of major reforms that can incorporate quality, equity and integrity into the education system, including preprimary, primary, secondary, higher secondary and higher education system. In many developing countries, the structure of higher education system is illdefined, corrupted, compromised and also neglected. It is not an easy task to offer quality education for all learners regardless of their social and economic background. For example, if courses such as technology management and technologies for humanity are not taught at the technical institutes properly, the effects will be inevitable; the technologies will be selected irrationally by hype and rumour. Is the future education policy too much focused on the hype of digital technologies (e.g. online learning) and neglecting other streams (e.g. Physics, Chemistry, Biology, Lab works), education methodologies and technologies? Why the education system is so lagging in the underdeveloped and developing world?

## 4. SECURITY

### *Security Analytics*

Agents: kids, children, youth, men, women;
Verification mechanism: call threat analytics and assess risks of emerging education technologies.

* what is corrupted or compromised (agents, computing schema, communication schema, data schema, application schema)?

* time : what occurred? what is occuring? what will occur? assess probability of occurrence and impact.

* insights : how and why did it occur? do cause-effect analysis on performance, sensitivity, trends, exception and alerts.

* recommend : what is the next best action?

* predict : what is the best or worst that can happen?

* what are the strength, weakness, opportunities and threats of online and offline education technologies?

audit security intelligence.

* audit authentication, authorization, correct identification, privacy, confidentiality, data integrity and nonrepudiation of education policy makers;

* verify rationality, fairness, correctness, transparency, accountability, trust and commitment of the education policy in human capital development;

* system performance: verify reliability, consistency, scalability, resiliency, liveness, deadlock freeness and safety of education technologies; ensure safety of the learners from war, bioterrorism, migration and natural disaster;

* assess the risk of multi-party corruption in education system (politics, ragging, free riding, discrimination, hate crimes, malpractice, dishonesty, ethics);

* verify the risk of false data injection, shilling (push and pull), denial of service (DoS) and fault injection attack on education system.

The basic objective of the expert panel is to revise and revamp various aspects of the education structure, regulation and governance to create a new education system that is aligned with the sustainable development goal of the summit. Prof. T. Mandella is analyzing the security of future education system. Education must develop not only cognitive capacities (basic capacities of literacy and numeracy) and higher order cognitive capacities (critical thinking and problem solving) but also social, ethical, and emotional capacities of the learners. It is crucial to develop faculties as the most respected and essential members of our society by ensuring livelihood, respect, dignity, autonomy, quality control, accountability, trust and commitment. It is a challenging task to provide quality education to all students with focus on historically marginalized, disadvantaged, and underrepresented groups. Education is a great leveller and is the best tool for achieving economic and social mobility, inclusion and equality, local and global needs of human society, rich diversity and culture, social, cultural and technological needs, ethics, self-confidence, self-knowledge, cooperation, and integration.

## 5. STRATEGY

### Strategy Analytics
Agents: educationists, system analysts, business analysts, scientist, engineers;
Strategic moves :

Call deep analytics ‘7-S’ model; explore how to ensure a perfect fit among 7-S elements (scope, system, structure, security, strategy, staff-resources, skill-style-support);

Define a set of security goals and emerging technologies accordingly.

Do SWOT analysis: strength, weakness, opportunities and threats of existing offline technologies as compared to emerging online technologies;

Fair and rational business model innovation for education sector

▪ Who are the consumers?

▪ What should be the offering of products and services?

▪ What do the consumers value?

▪ What is the rational revenue stream?

▪ How to deliver values to the consumers at rational cost?

Do technology life-cycle analysis on ‘S’ curve: presently at growth phase of ‘S’ curve.

Explore technology innovation-adoption-diffusion strategy.

Explore innovation model and knowledge management system for creation, storage, sharing and application of knowledge.

Adopt ‘4E’ approach for the development of underdeveloped zone by building smart villages and optimal resource planning, allocation and distribution (envision, explore, exercise, extend).

The expert panel have explored a set of interesting strategic moves for the innovation, adoption and diffusion of emerging technologies in education sector. The education policy is expected to be defined based on fundamental rethinking and radical redesign of as-is education system globally, identification of gaps and design of to-be system rationally. It may not be an intelligent approach to copy online education system blindly in the present environment of global economic shock and advancement and threats of emergent technologies (e.g. communication; 1G->2G->3G->4G->5G->6G->7G->8G->9G->10G..., high risk of obsolescence of phone sets, generation of e-wastes). The education policy should be based on an optimal mix of supervised and unsupervised learning mechanisms which should promote creativity, innovation, self-confidence and skill development through motivation, commitment, trust and fair rational efforts of the academic community. It is also required to explore the scope of other learning mechanisms such as transfer, batch, online and dropout learning.

The education policy is too much focused on time period of various academic programmes; there should be more focus on other critical success factors such as total quality management, education methodology, education technology and education materials. The to-be education policy should explore the scope, system, structure, security, strategy, staff-resources, skill, style, support, shared vision and the ultimate goals of education system in terms of fairness, correctness, transparency, accountability and rationality. The change of time period from 3 to 4 years for graduation or (5+3+3+4) school education system should not be a time
pass; the time should be properly utilized through real contributions of the
academic community for the development of the nation and human society globally.
In many countries, the student community exert maximum effort, time and cost on
account of pre-primary and school education and preparation for aptitude tests and
become exhausted physically and mentally to create real path breaking
contributions in the domain of higher education at colleges, universities and
branded academic institutes. There is less focus and fund allocation on higher
education system, innovation, research and development; so the number of
contributions, ideas and innovation is less in the domain of higher education.
Another important issue is complexity: there is less focus on real contributions in
science, engineering and technologies as compared to applied arts and
entertainment since it is hard to innovate in science (mathematics, physics,
chemistry, biology, engineering, medical and management) as compared to create
stories (e.g. statistical juggleries, emotional false data injection attack, emotional
blackmail, luxurious thoughts) in other domains based on common sense. The
academic community and top talent are too busy in exploring simple schemes of
various luxurious event management programmes and corporate communication;
less focused on complex brain storming sessions as compared to the education
system in developed countries.

The concept of single regulator is interesting but what should be the structure of
single regulator? Single regulator should have a *cellular structure* having different
cells: science, engineering & technology, management science, medical science, law,
arts etc. If there is no proper regulatory control, the education system may collapse
in the coming future. The regulatory body is expected to ensure corporate social
responsibilities of various academic institutions and academic programmes.
Absolute independence often creates pockets of inefficiencies, corruption and lack of
commitment in as-is education system at various academic institutions.
Benchmarking, standardization and total quality control is essential for talent
management, reward, recognition, placement and job assistance. Why so many seats
are vacant in technical institutes each year? There is sufficient infrastructure but
the capacity utilization factor is very poor. Why?

The design of to-be education system should be structured, compact and free from
malicious attacks (e.g. ragging, free riding, mental stress, depression, information
overloading). Each course should be modernized and clearly outline the objectives,
motivation, pedagogy, evaluation methodology, bibliography etc. The evaluation
methodology should be multi-dimensional (e.g. Quiz and written test: 30%, case
discussion: 20%, project: 30%, consulting assignment: 10%, research: 10%). What
are the strength and weakness of open book examinations? The sole focus on online
quiz contest based on MCQ may result a dull education system in future. In school
education, (5+3+3+4) system may be interesting but the students should do their
assignments and projects independently otherwise activity based learning may
become totally vague. Which is preferred: activity based learning or (skill + value)
based learning? If the activities or problems are solved by the parents or tutors of
the students solely, the learners may not be able to develop problem solving skills in
real-life. Multiple choices are interesting in selection of courses but the learners
need focus and depth of knowledge to become experts. There may be the risk of loss
of focus. The books should be compact and written intelligently with no overlap, vague data content and information overloading. Special children (e.g. Dyslexia) need different education system. Use of mother tongue or local language is important but the options of foreign languages (e.g English) are also necessary. Focus on conceptual learning, problem solving, creativity and innovation, practical experiments, lab works and skill development are interesting options. *Simulated virtual lab* may be cost effective but may affect the learners in science, medical, engineering and technology streams. Virtual lab should be used with physical labs concurrently. The education policy should protect the learners from only ‘writing, writing, reading; reading, reading, writing, typing, typing, typing’ and various types of healthcare problems of eye, ear and mind due to excessive use of mobile phones and tablets!

Benchmarking, standardization, joint ventures and strategic alliance with foreign institutes in innovation, research and development (e.g. Ph.d., Postgraduate) may be an interesting option to improve the quality of education. Absolute independence of academic institutes may result corruption and inefficiencies in many pockets such as admission, education methodology, technology, innovation and knowledge management.

Vague topics of projects and research for Ph.d., Postgraduate and Graduate programmes are often selected by the academic community randomly as per personal whims and fancies; complex topics are often avoided and simple topics are chosen to complete research by how or by cook within deadline; the topics should be selected based on the needs of the country, society, industry and the world. The research programmes are expected to be well-defined, well-organized, structured, properly planned; the hardness and complexity of research problems should be challenged honestly. The ultimate objectives should be to create contributions for path breaking innovations. Existing research programme gives too much focus to course work and comprehensive qualifying examinations of the researchers; they should devote and dedicate more time to their thesis works and actual research contributions. They should be able to work sincerely with a free mind, free flow of information, collaboration and resources. Most surprisingly, in as-is system, they spend more time in event management and composition of stories; less time in actual innovation. That is why, the underdeveloped and developing countries are lagging so much in creativity and innovation as compared to the West. There should be a balanced approach; some researchers are totally indifferent to publication of research papers; some others are workaholic to large number of publications, some others are busy in knowledge manipulation but the ultimate outcome may be garbage input garbage output (GIGO). Many research guides may be really experts but less committed; some others may have lack of knowledge and no interest; some may be egoists. The researchers are expected to be guided properly; this is an issue of style of leadership, goal setting and intelligent vision of the system administrators, faculties and research guides.

Is it practically feasible to design academic curriculum: Certificate after 1 year, Diploma after 2 years, Degree after 3 years and Honours after 4 years? Many academic programmes are crippled with dead, obsolete courses having no depth and breadth; modern and advanced complex topics are avoided; quality research
publications are not included even in graduation levels; such types of programmes need complete overhauling. Availability of right resources (e.g. books, journals, software, hardware) at right time and correct use of the same is very important. Another important issue is peculiar testing and evaluation system. Online test security is a critical concern today. Is the online testing system (e.g. quiz contest) really evaluating the performance of the students correctly in higher education (e.g. engineering, medical, management, science, law)? Is the online test free from various malicious attacks by the adversaries in India today : session hijack, hanged web portal of academic institutions, networking problem of mobile service provider, privacy, confidentiality, internet traffic congestion, link failure, Denial of Service (DoS) attack, power cut (load shedding), delay, mobile charging problem, battery charging problem, internet access problem, sybil attack, natural disasters (e.g. cyclone, rainfall, storm), data integrity, non-repudiation, authentication, authorization, correct identification, trust, commitment, fairness, correctness, transparency, accountability, corruption, reliability, consistency, resiliency etc. The students are forced to just uploading and downloading files into or from whatsapp or ticking options on the portal; there is no test of depth and breadth of knowledge through such so called quiz contest. There is no logic and rationality of the decision making authorities of independent academic institutions; the standards and quality of higher education system may be becoming a vague silly joke and the present situation of epidemic is adding fuel to the fire. There is no value given to innovation, knowledge and skill development of the young student community.

Law of average having no head or tail is a critical threat. Many boards, councils and academic institutions may be in a hurry with a casual approach in testing and evaluation - how to publish final results by how or by cook; poor performances may be getting maximized; good performers may be getting victimized. There may be no rationality in heuristics of evaluation system. This is just like the film 'Heerak rajar deshe' directed by the great Satyajit Roy : 'Janar kono sesh nai; janar chesta britha tai'; (There is no end of knowledge; so, it is useless to learn anything); as if marks are bribed to the students in the name of peculiar rules and regulations. What may be the solution to this problem: is it 'dari dhare maro tan, raja hobe khan khan'! [Renew system and governance]. It is essential for the governments of various countries to rescue the education system from sureshot collapse, disaster and uncertainty in the coming future through an intelligent, rational unbiased national education policy.

# 6. STAFF-RESOURCES

## Staff-resources Analytics

do estimation, planning, capacity utilization, allocation and distribution of '5M' resources.

* Man (human capital management [learners, faculties, system administrators, scientists, business analysts, system analysts, project managers, engineers], talent acquisition, talent retention, training, reward and recognition)

* Machine (tools, computer hardware, software, internet, mobile phones, tablets)
★ **Material** (book, notebook, paper, pen, pencil, rubber, color, geometry box, bag)

★ **Method** (process innovation for resource allocation, education methodology)

★ **Money** (optimal fund allocation, project management, resource allocation, resource distribution, education loan from bank)

Optimal planning and capacity utilization of various types of resources is essential for promoting best practices and quality management in education sector. The expert panel have identified five critical resources for re-engineering in education sector : man, machine, materials, method and money. The critical issue is management of financial resources for the innovation and promotion of new technologies. It is rational to use ERP system for optimal planning and capacity utilization of resources; it is an interesting option to explore ERP system for efficient resource management.

## 7. SKILL-STYLE-SUPPORT

### Skill-style-support Analytics

★ Skill (knowledge of operation and best practices of education sector, engineering, technical, system administration, management, governance, supply chain management);

★ Style (leadership, shared vision, goal setting, intelligent communication, risk assessment and mitigation, innovation project management);

★ Support (proactive, preventive and reactive support)

The expert panel have identified a set of key areas for skill development such as knowledge of operation and best practices of education sector, engineering, technical, system administration, management, governance and supply chain management. Innovation leaders must have shared vision, goal, communication, project management and coordination skills and rational decision making capabilities. The technical staff should have capabilities on proactive and reactive support of equipments, tools and systems. It is essential to develop skills in various branches of engineering such as mechanical, electrical, civil, chemical, digital technology, domain knowledge of best practices and process innovation in education sector and related research and development. With the support of digital technologies, it is possible to develop a sophisticated knowledge management system (e.g. digital libraries, e-books, e-journals, e-papers, e-magazines). But, how many learners are really motivated to understand the distributed education materials during various academic programmes (e.g. engineering, medical); it is an issue of trust and commitment and real challenge to the education world. There should be proper integration among education technology, policy and methodology during today's age of technology transition.

### Quiz

* What is the scope of smart education technology?
* What is the dominant design of these technologies?

* What are the basic elements of the system architecture?

* What do you mean by technology security? How can You verify the security intelligence?

* What are the strategic moves of technology innovation, adoption and diffusion? What is the outcome of technology life-cycle analysis and SWOT analysis of online and offline technologies?

* How to manage resources for innovation project of these technologies

* What should be the talent management strategy? What are the skills, leadership style and support demanded by the technological innovation?

* How do You manage technology innovation project efficiently? What should be the shared vision, common goals and communication protocols? How can you ensure a perfect fit among ‘7-S’ elements?

Further Reading

* Kusumita Chakraborty. 2005. A study of literacy achievement in literacy centres of West Bengal. Registration Number : 306 Ph.D. (Education). Department of Education, Calcutta University, India.

* Aronowitz, S. (1994). Technology and the future of work. In G. Bender & T. Druckrey (Eds.), *Culture on the brink: Ideaologies of technology* (pp. 15–30). Seattle: Bay Press.

* Ballengee-Morris, C., & Stuhr, P. L. (2001). Multicultural art and visual cultural education in a changing world. *Art Education, 54*(4), 6–13.

* Barbosa, A. M. (1991). Art education and environment. *Journal of Multicultural and Cross-Cultural Research in ArtEducation, 9*(1), 59–64.

* Freedman, K. (1995). Educational change within structures of history, culture, and discourse. In R.W. Neperud (Ed.),*Context, content, and community in art education*. New York: Teachers College Press.

* Lanier, V. (1969). The teaching of art as social revolution. *Phi Delta Kappan, 50*(6), 314–319.

* Morley, D. (1992). *Television, audiences, and cultural studies*. London: Routledge.

* Neperud, R. (1973). Art education: Towards an environmental aesthetic. *Art Education, 26*(3).

* Rose, G. (2001). *Visual methodologies*. London: Sage.

* *Multicultural and Cross-cultural Research in Art Education, 14*, 80–91.

* Solso, R. (1997). *Mind and brain sciences in the 21st century*. Cambridge, MA: MIT Press.

* Tavin, K. (2000). Just doing it: Towards a critical thinking of visual culture. In D. Wiel & H. K. Anderson (Eds.). *Perspectives in critical theory: Essays by teachers in theory and practice* (pp. 187–210). New York: Peter Lang.
SESSION 5: HEALTH SECURITY - CANCER CARE, BIOMEDICAL TECHNOLOGY and ARTIFICIAL IMMUNE SYSTEM for EPIDEMIC CONTROL

Event: Technology for humanity and global security summit

Venue: Health security hall, Technology park: Sanada

Time Schedule: 2 p.m. – 6 p.m., 16.8.2020

Agents: Representatives of various global organizations (Health, Economic forum), Technology management experts from science and technology forums, Social engineers, Social scientists, representatives and ministers from the departments of child, women and family welfare of developed, developing and underdeveloped countries, CEOs of life science corporations, business development consultants of life science, pharmaceuticals.

Topic of discussion and key focus areas: Health security, cancer care, biomedical technologies, Artificial immune system, Epidemic and pandemic control

Keynote speakers: Prof. Bob Taylor, Dr. Jim Morrison, Prof. Michel Bolton, Prof. P. Kar, Prof. David Nissim, Dr. Arvind Gurumurthy, Dr. Muller, Dr. Nil Harvey

1. SCOPE

Scope Analytics

Agents: System analysts, business analysts; scientists, doctors, engineers;

Moves: Critical success factors analysis, Requirements management;

Security parameters: define a set of sustainable development goals on healthcare security, cancer care

Application domains:

* Cancer: cancer of mind / psycho-oncology, neural control and coordination, chemical coordination and integration, digestive system, respiratory system, cardiovascular system, excretory system, locomotion and movement system, reproductive system;

* Biomedical technology innovation: artificial pancreas, artificial liver, artificial kidney, artificial limbs, artificial cardiovascular devices, oral insulin;

* Artificial immune system for epidemic control.

Prof. P. Kar is starting the session based on key focus areas such as cancer prevention, proactive approach, reactive approach, bad luck, deep learning, optimal margin classifier, support vector machine, precision medicine, regenerative medicine, integrated medicine, cancer genomics, CNN, intelligent reasoning, biomedical technology, oral insulin, artificial pancreas, artificial kidney, artificial liver, artificial cardiovascular devices, artificial limbs, laser, surgical robotics, wearable computing, concurrent engineering, technology innovation, epidemic control,
pandemic outbreak, Intelligent broadcast, online grievance management system, artificial immune mechanism, self-nonself classification, danger signal, clonal selection, hotspot, cluster, social distancing, security intelligence, business intelligence, bio-terrorism, life science supply chain, and healthcare service chain.
This session explores an emerging technology for prediction and prevention of cancer. The complexity of emerging technology has been analyzed in terms of scope, system, structure, security, strategy, staff-resources and skill-style-support. Presently, the technology of cancer care is passing through the growth phase of S-Curve. The technology has been analyzed in terms of a set of intelligent strategic moves such as proactive and reactive approach, deep learning, optimal margin classifier, intelligent reasoning and biomedical instrumentation. Intelligent reasoning has been explored in terms of case based reasoning, perception and common sense. It is also essential to adopt a set of effective reactive strategies such as genomics, precision, integrated, regenerative and alternative medicines to fight against cancer. We have presented a deep analytics based cancer prevention mechanism (DACPM) balancing proactive and reactive approaches. The mechanism defines human biological system from the perspectives of application, computing, networking, data and security schema. This work also analyzes different types of cancer through DACPM.

This session also shows the application of deep analytics '7-S' model on the innovation of bio-medical technology for cancer care. The complexity of biomedical technology has been analyzed in terms of scope, system, structure, security, strategy, staff-resources and skill-style-support. The scope of biomedical technology has been explored in terms of artificial pancreas, artificial liver, artificial kidney, artificial cardiovascular system and artificial limbs. The critical observation is that oral insulin is a rational, simple, practically feasible and safe option as compared to artificial pancreas. It is hard to develop artificial kidney, liver and pancreas which can mimic all the functions of related biological organs. The concept of oral insulin is now at emergence phase of technology life-cycle; artificial cardiovascular devices and limbs. It is rational to adopt proactive and reactive approaches to overcome the constraints of biomedical technology. This work also explores the scope of laser therapy, pervasive and wearable computing and surgical robotics for cancer care. Is it possible to innovate an affordable cheap test kit for cancer care which should be able to detect cancer of human beings by measuring a set of critical health parameters (e.g. blood, urine, sweat, stool, saliva, mucosa, semen etc.) through biosensors in an automated manner? Can AI promote such complex innovations in future?

This session also presents the construction of a deep analytics based cancer prevention mechanism (DACPM) balancing proactive and reactive approaches. It defines human biological system from the perspectives of application, computing, networking, data and security schema of an information system. The strategic moves of DACPM include deep learning, intelligent reasoning, threat analytics, optimal mix of proactive and reactive approaches, rational healthcare payment function and budget plan and adaptive secure multi-party computation. The performance of human biological system is expected to be verified through the properties of adaptive secure multiparty computation: fairness, correctness,
accountability, transparency, rationality, trust, commitment; authentication, authorization, correct identification, privacy, audit; safety, reliability, consistency, liveness, deadlock-freeness, reachability, resiliency, robustness and stability of application integration. It analyzes the complexity of the mechanism in terms of computational cost of deep learning algorithm. This work is specifically focused on reasoning nine test cases through DACPM in depth to fight against the epidemic of cancer: The human biological system is assumed to be a computer. It is not a rational thinking that the most of the causes of cancer are due to bad luck; it is still not known enough about the causes and prevention measures of cancer. Deep analytics does not necessarily mean deep learning algorithm, it is also associated with intelligent reasoning – analytical, logical, common sense, case based reasoning and also perception to fight against the epidemic of cancer. A human agent must have common sense healthcare knowledge base for proper biological system control through intelligent self-assessment, self-confidence, life-style, diet control and right decision making at right time. It demands the necessity of learning the basic concept of reasoning and common sense healthcare through an effective knowledge management system based on deep analytics and intelligent broadcast communication.

The basic objective of this session is to generate a rational cancer prevention plan subject to financial constraints. The work has reviewed the relevant literature on cancer, oncology and deep learning and has adopted analogical reasoning as research methodology.

Technological innovations are practical implementation of creative novel ideas into new biomedical devices. Many potential ideas pass through the wide end of an innovation funnel but very few may become successful, profitable, economically and technically feasible products in future. It is an interesting research agenda whether deep analytics may be an effective tool for the diffusion of biomedical technology in future. It is a multi-dimensional analysis wherein seven factors must be integrated, coordinated and synchronized. This session shows the application of deep analytics '7-S' model on innovation of bio-medical technology.

Recently, there is a trend of cross fertilization between five disciplines: medical science, management information system, artificial intelligence, artificial neural network and management science. This work is associated with the problem of cancer prevention. Cancer is a costly, global and complex problem; it results a major obstacle to human development and well-being. The attack of cancer has increased from 12.7 million (2008) to 14.1 million (2012) and this trend is projected to continue about 25 million cases over next two decades; the greatest impact will be in low and middle income ill equipped countries. The future of a cancer patient depends on the living zone. In less economically developed countries, cancer is diagnosed at more advanced stages while access to effective treatment is limited or unavailable. The highest-income countries often struggle with the spiraling costs of cancer treatment and care. Cancer has a social cost, human potential is lost and cancer care has an escalating economic impact. It is essential to identify the causes and prevention strategies for cancer control.

Let us first look at bio-statistics of cancer. It is a major cause of morbidity and mortality, with about 14 million new cases and 8 million deaths in 2012, affecting
populations in all countries and all regions. Among men, five most common sites of
cancer were lung (16.7%), prostate (15.0%), colorectum (10.0%), stomach (8.5%),
and liver (7.5%). Among women, five most common sites of cancer were breast
(25.2%), colorectum (9.2%), lung (8.7%), cervix (7.9%), and stomach (4.8%). There
were 8.7 million people (older than 15 years) alive with cancer diagnosed in the
previous year, 22.0 million in the previous 3 years, and 32.6 million in previous 5
years. The worldwide estimate for the number of cancers diagnosed in childhood
(ages 0–14 years) in 2012 is 165000 (95000 in boys and 70000 in girls). The highest
incidence rates are associated with high income countries of North America and
western Europe, Japan, Korea, Australia, and New Zealand. More than 60% of
cases and 70% of deaths occur in Africa, Asia, and Central and South America.
Cancers are caused by mutations that may be inherited or caused by environmental
factors or DNA replication errors.

Dr. Kar has defined the structure of human biological system from the perspectives of application, computing, networking, data and security schema of an information system. The application schema is related to the function and features of a specific biological system. The networking schema is related to the configuration of the system such as nodes and interconnections among the nodes. The computing schema deals with the protocol, process, procedure and mechanisms of a system and its various components. The data schema is associated with various entities, their attributes and interrelationships, inputs and output of a system. The security schema verifies the disorders of the system and protects the system through various means such as vaccination precision, regenerative and integrated medicine, chemotherapy and laser.

In this session, the scope of cancer has been explored in terms of (i) cancer of mind, (ii) neural control and coordination : brain cancer, (iii) chemical coordination and integration : breast cancer (iv) digestion and absorption : liver, pancreas, stomach and colorectal cancer (v) respiratory : lung cancer, (vi) body fluids circulation : blood cancer, (vii) excretory : renal cancer and urinary bladder cancer, (viii) locomotion and movement: bone cancer and (ix) reproductive system : ovarian and testis cancer.

Dr, Rina Brown and Prof. Bob Taylor have explored the scope of emerging
biomedical technologies in terms of artificial pancreas vs. oral insulin, artificial
kidney, artificial liver, artificial cardiovascular devices (e.g. heart valves, stents,
pace makers, artificial limbs, arms, legs and laser therapy. The scope of innovation
on biomedical technology should be explored rationally through intelligent analysis
of the basic objectives, goals, needs, constraints and mechanisms; strength,
weakness, opportunities and threats of various strategic options. First, it is essential
to understand the mechanisms of various human organs (e.g. pancreas, liver,
kidney, heart, limb, brain) in terms of human physiology, input, output, feedback
control, function, process, chemical reaction, secretion of enzymes and hormones,
coordination, integration and system performance. Next, it is rational to analyze
whether it is practically feasible to make artificial organs which can mimic various
functions of biological organs of human body in the best possible ways. The scope of
biomedical technology spans over several domains such as artificial pancreas, liver,
kidney, cardiovascular system and limbs
**Artificial pancreas:** Let us first do scope analysis on oral insulin vs. artificial pancreas for the treatment of diabetes; which is more feasible technology innovation and why? Pancreas synthesizes insulin which extracts glucose from carbohydrate for the supply of energy and storage. It controls blood sugar level and prevents hyperglycemia or hypoglycemia. Insulin is a collection of 51 amino acids with two chains A (21 amino acid) and chain B (30 amino acid) linked by disulfide bridges. Diabetes is a chronic disease, it arises when sufficient amount of insulin is not produced by the pancreas (Type 1 diabetes) or insulin which is formed is not utilized properly by the body (Type 2 diabetes). It leads to an elevation of blood glucose level (hyperglycemia). Diabetes is the most common endocrine disorder. It is a real challenge to find out effective administration and delivery mechanism of Insulin. Subcutaneous (SC) route may lead to hyperinsulinemia. Repeated injections if insulin may result various types of health problems such as lipoatrophy or lipohypertrophy, peripheral hyperinsulinemia, peripheral hypertension, atherosclerosis, cancer, hypoglycaemia and other adverse metabolic effects. Can an artificial pancreas mimic all the functions of a biological pancreas? It is essential to explore alternative route such as oral insulin which mimics the typical insulin pathway within the body after endogenous secretion subject to various constraint such as good bowel absorption and very low oral bioavailability of insulin.

**Artificial liver:** Next, let us consider the scope analysis of artificial liver. Liver is a complex organ doing various vital functions such as synthesis, detoxification and regulation; its failure may result a life threatening condition. Liver failure (LF) can either occur as acute liver failure (ALF) due to intoxication or as acute-on-chronic liver failure (AoCLF). The common symptoms are icterus, hepatic encephalopathy and impairment of coagulation and may result even multi organ failure. In case of liver failure, water-soluble toxins (e.g. ammonia) and albumin-bound toxins (e.g. bilirubin, amino and fatty acids) may accumulate and cause encephalopathy and dysfunction of other organs. Detoxification and regulation can be addressed by artificial devices similar to dialysis, the synthetic function of the liver can only be provided by living cells. We have done analysis on strength, weakness, threats and opportunities of artificial liver and have also outlined a liver protection mechanism by adopting an optimal mix of proactive and reactive approaches.

**Artificial kidney:** Next, let us consider the innovation of artificial kidney. There are various therapies of kidney problems [e.g. end-stage renal disease (ESRD), continuous renal-replacement therapy (CRRT)] which cause sepsis, systemic inflammatory response syndrome, acute respiratory distress syndrome, congestive heart failure, tumorlysis syndrome and genetic metabolic disturbances. The dominant therapies are hemodialysis and hemofiltration. An artificial kidney should perform three physical processes efficiently that determine the removal rate for uremic toxins through membrane-based devices: *convection* removes toxin through a semipermeable membrane; *diffusion* removes smaller molecules with high diffusion coefficients and *adsorption*.

**Artificial cardiovascular devices:** Next, let us consider the technological innovation of artificial cardiovascular devices. Cardiovascular disease (CVD) is the leading cause of death worldwide. In this domain, the technological innovation is facing several challenges such as improved device function (e.g. cardiac valves, stents, pacemakers