Artificial pancreas is used to deliver basal insulin automatically and continuously at meal time by pressing the buttons of insulin pump. Blood sugar data is given to the insulin pump before meals. It calculates the correction bolus to bring the blood glucose level back to the target. But there are several complexities of artificial pancreas such as calibration for sensor correction, correctness in measurement of blood sugar levels, skill, intellect and knowledge of the diabetic patients, maintenance of medical equipments and verification of the correctness of automatic control of basal rate of insulin pump, adaptive filtering for learning unique basal rate, feedback from a continuous blood glucose sensor and adjustment of correction bolus during increase or decrease of blood sugar level. Typically, implantable insulin pumps work for an average of eight years and the sensors stop working after an average of nine months. From the aforesaid analysis, it is clear that oral insulin is a much more simple and rational strategic option as compared to artificial pancreas and demands much more focus of R&D.

It is an interesting research agenda to do SWOT analysis on artificial liver vs. biological liver transplantation. Both the options may be essential for various types of liver diseases such as liver cancer, cirrhosis of liver, jaundice, hepatitis, alcoholic liver problem, chronic liver problem, autoimmune hepatitis, Wilson's disease, black stool, blood vomit, swollen legs and heal and water accumulation. But, there are several constraints such as adaptability and immunity. Can an artificial liver mimic all the functions of a biological liver?

Generally, the patients suffer from liver cirrhosis due to regular consumption of booz; liver cells are destroyed and the liver is scarred due to the effect of alcohol. Non-alcoholic fatty liver disease (NAFLD) is the accumulation of fat in the liver not triggered by alcohol but caused by erratic life-style, high blood sugar, cholesterol and obesity. It often remains undetected and may lead to liver cancer. There are other various types of liver problems such as liver cirrhosis and acute hepatitis [B or C type]. Acute hepatitis are treatable and can be prevented with vaccines but chronic hepatitis or NAFLD are not fully reversible. It can not be cured but can be merely controlled. The common prevention strategies for NAFLD include avoiding fatty food, daily physical exercise, periodic screening of liver and control of blood sugar and cholesterol levels. It is technologically hard to develop an artificial liver that can mimic all the functions of biological liver in human body. Alternatively, it is rational to adopt an optimal mix of proactive and reactive approaches which can protect liver from various toxic effects.

## Liver Protection Mechanism:

### Proactive approach:

- Control consumption of booz / country liquor / wine / alcohol for the treatment of cirrhosis of liver;

- Avoid excessive consumption of non-vegetarian food (e.g. red meat, egg, fish);

- Take fruits regularly (e.g. Jambura or 'batabi lebu', mousambi, orange);

- Take herbal medicine periodically and vitamins;

- Acute hepatitis are treatable with vaccines;
* Avoid fatty food, daily physical exercise, periodic screening of liver and control of blood sugar and cholesterol levels for prevention of NAFLD;

## Reactive approach

* Acute liver failure: Organ transplantation is a feasible option but it should consider following issues carefully.

* Is there any problem of immunity and infection in case of liver transplantation from other animals?

* Which animal should be considered for organ transplantation: human being, goat, lamb, cow, pig?

* Is it possible to transplant a healthy liver from a dying person to a liver patient?

* Is it possible to set up animal liver bank to preserve animal livers in advance?

* Liver dialysis: BAL can replicate several metabolic functions such as detoxification, lipid and plasma lipoprotein synthesis, carbohydrate homeostasis and production of serum albumin and clotting factors without using multiple devices. BAL device reduced mortality by about half in acute liver failure cases.

* Is it possible to develop artificial liver that can mimic all the functions of normal and healthy biological liver? It is a promising but challenging task in terms of product design, clinical study and identification of ideal cell source that can grant patients substantial survival benefits compared to standard intensive care.

Liver transplantation is a feasible solution to acute liver failure but severe shortage of donors is a major constraint. Artificial hepatic support systems should provide optimal cell survival, proliferation and maintenance of sufficient liver functions. Liver is one of the most sophisticated organs in human body, the science of liver tissue construction is also very complex.

The evolution of technological innovation of artificial kidney depends on various factors such as tissue engineering, biocompatible materials, transport mechanism; hemodynamic, absorption, hemodialysis and hemofiltration therapy, animal studies and extensive clinical trials. Can an artificial kidney mimic the metabolic, endocrine, and transport functions of a healthy living kidney efficiently? The present technology cannot replace an ailing kidney with artificial one. It is technically hard and complex to develop artificial kidney and install the same in human body. What are the side-effects of an artificial kidney on human biological system? Is it possible to explore proactive and reactive approaches for the protection of kidneys rationally? Generally, it is recommended to drink water sufficiently and avoid excessive consumption of salts. Is it possible to improve the functions of a kidney artificially using medicines – it may be herbal, allopath or integrated medicine? Dialysis is a popular method of treatment. Acute kidney failure needs organ transplantation and surgical operation. Is there any problem of immunity and infection in case of transplantation of kidney from other animals? Which animal should be considered for organ transplantation? Is it possible to transplant a healthy kidney from a dying person to an ailing patient? These are alternative feasible options as compared to artificial kidney.
It has been possible to simulate the functions of a kidney through renal substitution therapy with hemodialysis or chronic ambulatory peritoneal dialysis (CAPD) and transplant it from a donor to a patient successfully. Dialysis is basically renal substitution rather than renal replacement therapy. It only mimics the filtration function but can not replace homeostatic, regulatory, metabolic and endocrine functions of a healthy kidney. So, dialysis has major medical, social, and economic problems. A biohybrid kidney may have biological and synthetic components. It is expected to offer many benefits such as reduced cost, time and infection and increased flexibility, mobility and life expectancy.

**Technological life-cycle analysis** : The basic objective of deep analytics is how to manage evolution of the aforesaid technological innovations effectively. It is really interesting to analyze the impact of various factors and patterns of trajectories of biomedical innovations. It is possible to do the analysis of life-cycle based on S-curve, trajectory, diffusion and dominant design of the aforesaid innovations. Technology trajectory is the path that the new technology follows based on rate of improvement in performance, diffusion and adoption. It is perceived today that the innovations of oral insulin, artificial pancreas, artificial liver and artificial kidney may be at emergence phase of S-curve. On the other side, the innovations on artificial cardiovascular devices and limbs may be at growth phase of the curve. The emergence of such new technologies follow a complex process. It is really hard to understand how the life-cycle of a new technology interacts with other technologies and impacts on healthcare and life-science sectors. The next phase is growth if the technology; initially it is difficult and costly to improve the performance of a new biomedical device. The performance is expected to improve with better understanding of the fundamental principles of the technology and system architecture. Initially, the new technology may be costly and risky for the early adopters. Gradually, it should reduce the cost and risks of the biomedical devices and penetrate the market rapidly.

The diffusion of biomedical technology and oral insulin depends on how new technologies can spread through potential adopters such as the patients and healthcare consultants. Diabetes is a very common healthcare problem today; the size of the market of oral insulin is expected to be big. The rate of diffusion depends on the effectiveness, reliability, consistency and flexibility in system performance and the economic and demographic profile of the adopters. The rate of improvement of the aforesaid biomedical technology technologies and oral insulin should be faster than the rate of market demand over time; the market penetration is expected to increase with high performance and efficiency of the bio-medical devices and oral insulin. At present, the evolution of these technologies are going through a phase of turbulence and uncertainty; the firms are exploring a set of competing options; a dominant design is expected to emerge through consensus and convergence of biomedical system. The dominant design must consider an optimal set of features which should meet the demand of the patients and healthcare experts in the best possible way.
<figure><img src="image_39.png" /><figcaption>Figure 5.4 : Technology life-cycle analysis</figcaption></figure>

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 as discussed during session 2.

# 7. STAFF - RESOURCES

## Staff-resources Analytics

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

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

* **Machine**: tools, instruments, computer hardware, software, internet;

* **Material**: Medicine;

* **Method**: process innovation for healthcare and cancer care;

* **Money**: optimal fund allocation, project management, resource allocation and distribution;

The expert panel have analyzed the demand of staff-resources for healthcare security in terms of sources of innovation and roles of biomedical engineering, pharmacy and life-science firms, oncology departments of healthcare institutes, government research laboratories and collaborative networks; optimal utilization of man, machine, material, method and money, dominant design factors of artificial organs and biomedical devices, process innovation in cancer treatment and technological spillover. The innovation demands the commitment of creative experts of oncology, bio-medical engineering, healthcare and life-science sectors who can contribute significantly through their intellectual abilities, thinking style, knowledge, motivation and group dynamics. In this connection, collaborative networks are interesting options which should coordinate and integrate the needs
and activities of R&D lab, start-ups (e.g. science parks, incubators), academic institutions, ministries of state and central government, patients, users and supply chain partners effectively. The creative talent should look at the hard problems in unconventional ways, generate new ideas and articulate shared vision.

The panel are exploring 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, management 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.

It is important to analyze this element in terms of 5M : 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.

Individual inventors may contribute through their inventive and entrepreneurial traits, skills and knowledge in multiple domains and highly curious argumentative mindset. The healthcare institutes and medical colleges should define sound research mission and vision and contribute through publication of research papers. Government also plays an active role in R&D either directly or indirectly or through collaboration networks and start-ups (e.g. science parks and incubators). Collaboration is facilitated by geographical proximity, regional technology clusters and technology spillovers. Technological spillover results from the spread of knowledge across organizational or regional boundaries; it occurs when the benefits from R&D activities of a firm spill over to other firms.

This 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. It is difficult to conclude that
moderate knowledge is adequate for creativity. A creative person is expected to have
confidence in own capabilities, tolerance for ambiguity, interest in solving problems
and willingness to overcome obstacles by taking reasonable risks. A cooperative and
collaborative environment must recognize and reward creative talent in time.
Organizational creativity is associated with several critical factors such as human
capital management, talent acquisition and retention policy, complex and tacit
knowledge management strategy, organization structure, corporate culture,
routines, incentive policy, social processes and contextual factors.

8. SKILL-STYLE-SUPPORT

Skill-style-support analytics

★ Skill: knowledge of operation and best practices of healthcare, life science, bio-technology, pharmacy, 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 analyzing skill-style-support for health security. What should be the innovation model for effective diffusion of Cancare ? is it possible to adopt K-A-B-C-D-E-T-F model? The workforce involved in aforesaid technological innovations are expected to develop different types of skills in technical (e.g. bio-medical engineering, pharmacy, life-science, oncology, deep learning and artificial neural network), healthcare and medical science domain such as research and development, knowledge management, product design, project management, supply chain management, sales and distribution. It is essential to teach deep learning innovatively in various programmes of Electrical, Electronics and Biomedical engineering as part of graduation, post graduation and Doctoral programmes. The learning community should be involved in consulting, projects and research assignments. They need good resources such as digital libraries having good collection of books, journals and magazines, software and experimental set up. The workforce of R&D labs can develop skills through effective knowledge management programmes and resources which support creation, storage, sharing and application of knowledge. The diffusion of technology requires the support of intelligent leadership style; the leaders must be able to tackle the complexity, pace and novelty of R&D projects through efficient project management, organization structure development, knowledge management and collaborative and cooperative work culture. The healthcare professionals are expected to be people, information and action oriented. Next, let us consider the element support.

Caution from malicious learning system : The basic objective is to protect learning
systems in adversarial setting from various types of threats such as use of flawed
learning algorithm or intentional change of training and testing data distribution.
The malicious agents may act consciously to limit or prevent accurate performance
of the learning system for economic incentives. It is a common problem where machine learning is used to prevent illegal or unsanctioned activities. Traditional techniques (e.g. efficient algorithm, linear classification) are necessary but not sufficient to ensure the security of the machine learning system. It is a hard problem and needs the support of an efficient mechanism equipped with intelligent threat analytics and adaptive secure multi-party computation algorithms. Malicious business intelligence is a critical threat to machine learning system. The conflict between security intelligence and business intelligence is inevitable. It needs fair, rational and intelligent business model innovation.

*Example:* Malicious business intelligence may attack a life-science supply chain and healthcare service chain through greedy heuristics in payment function for revenue and profit optimization, economic pressure and incentive policy, fraudulent health insurance model, flaws in investment decision on technology management, irrational and dull HR policy in talent management and chaotics in formulation of public policy, mechanisms and corporate governance. In fact, the conflict between business intelligence and security intelligence is inevitable; the deep learning mechanism is expected to resolve this conflict between security and business intelligence.

Let us consider a specific instance of machine learning in healthcare service chain. The deep learning mechanism must call the threat analytics to audit various critical processes associated with a healthcare service chain in cancer care such as registration, consulting, testing, surgical operations, billing, payment processing and follow-up. Generally, different types of information systems are commonly used to support these processes such as transaction processing system (TPS), decision support system (DSS), group decision support system (GDSS), knowledge management system (KMS) and business intelligence (BI) system. The primary objective of these information systems is to ensure fairness and correctness in computation of registration card, appointment slip for consulting, prescription by consultant, surgery schedule, quality control certificate, medical test report, discharge certificate, bills and payment receipt, feedback form and patient's guide. The other important issue is to preserve the privacy of patient's personal and medical data. The deep learning mechanism should verify the security of the computing schema associated with the machine learning system in healthcare service chain to identify probable sources of errors in cancer care.

* Incorrect data provided by the cancer patients to the registration associate during registration intentionally or due to lack of knowledge or incorrect perception of the patients or their attendants; the patients or their attendants may be irrational in information sharing properly with the service providers.

* No verification of patient's identity correctly during registration; the cases of emergency situation or accidents may skip verification due to unavailability of data about the patients.

* Wrong entry of data into various information systems by the healthcare associates due to time and resource constraints or misunderstanding or lack of validation of input data.

* Computational errors due to wrong configuration of enterprise applications and / or errors in the heuristics, deep learning algorithms and quantitative models
and / or no updating of data (e.g. service charge, tariff of testing, price of drugs and healthcare products; low accuracy of pattern recognition algorithms in image processing system may result incorrect medical diagnosis.

* Access control problem causing dangerous errors in information system; a malicious agent may enter false data into HIS during the absence of authorized users.

* A malicious agent may launch attacks on TPS, DSS, GDSS, KMS and BIS through malicious data mining, insecure data storage, flaws in data visualization and image processing algorithms and transaction processing logic.

* Swap or mixing of test data of various patients or drugs administration due to confusion, poor document management, lack of clear understanding or training of the healthcare workforce; false data injection on viruses in test reports are serious threats in today's healthcare practice. The patients are not often given test reports today by the service provider to hide malicious trading practice or to charge extra amount. Testing of uncommon viruses enhance the cost of testing unnecessarily. Sometimes, broadcast of epidemic results panic among the public and this critical and helpless situation is exploited by malicious testing and medicare practice inhumanly.

* Errors in decision making by the health consultants due to lack of proper knowledge management system (e.g. case based reasoning, intelligent DSS and GDSS) or misperception or lack of coordination among the workforce of various departments or inappropriate enterprise application integration or error in test reports; incomplete prescription due to memory failure or silly mistakes.

* Errors in scheduling due to exceptions (e.g. unfit patients, non-availability of healthcare experts), flawed and inadequate doctor-patient ratio;.

* surgical operation by unauthorized and unskilled workforce, intentional errors due to malicious business practice, lack of ethics, casual approach and dull HR policy; unintentional errors due to physical and mental fatigue for excessive workload and sickness, non-availability of basic infrastructure and logistics arrangements;

* Lack of verification of correctness of computation in medical billing and payment processing by the service provider and / or service consumer;

* Incorrect data in patient's help guide may cause confusions and mismatch between the computed results and perceived one;

* Incorrect feedback by the patients or their attendants due to misperception, misunderstanding of feedback form, lack of knowledge and critical observations or casual attitude.

* Sybil attack: It is really complex to trace the corrupted players in healthcare domain. A malicious agent may control multiple pseudonymous identities and can manipulate, disrupt or corrupt an application that relies on redundancy by injecting false data or suppressing critical data; it is sybil attack. The patients may be treated incorrectly and diagnosed as cancer casually though there is another simple medical problem. Natural intuition and perception may not be applied for simple medical problems. The patients may be incorrectly recommended for costly treatment. They may be recommended for costly treatment procedure repeatedly (e.g. CT scan, X-ray), drugs and surgical
operations. The poor and helpless patients may be forced to validate and verify
the test reports and medical diagnosis at various healthcare institutes. This is an
instance of modern biological, chemical and radiological terrorism today.

Fairness and correctness of computation and testing is a critical concern in cancer
therapy. Knowledge management is another critical success factor; case based
reasoning may be a good solution for correct clinical decision making. For effective
deep learning system, digital technology management is not only the critical success
factor (CSF). There are other several CSFs such as HR policy in talent
management, motivation and commitment, quality of education in terms of trust,
ethics and values, intelligent public policy, mechanisms and corporate governance.

The workforce involved in aforesaid technological innovations are expected to develop different types of skills in technical (e.g. bio-medical engineering, pharmacy, life-science), healthcare and medical science domain such as research and development, knowledge management, product design, project management, supply chain management, sales and distribution. It is essential to teach Biomedical technology innovatively in various programmes of Electrical, Electronics and Biomedical engineering as part of graduation, post graduation and Doctoral programmes. The learning community should be involved in consulting, projects and research assignments. They need good resources such as books, journals, software and experimental set up. However, they should understand the motivation of the problems and various issues of technology management through deep analytics. The workforce can develop skills through effective knowledge management programmes and resources which support creation, storage, sharing and application of knowledge. The diffusion of technology requires the support of intelligent leadership style; the leaders must be able to tackle the complexity, pace and novelty of R&D projects through efficient project management, organization structure development, knowledge management and collaborative and cooperative work culture. The leaders are expected to be people, information and action oriented.

It is essential to develop skill in new product development through proper coordination among design, supply and patient chain and R&D, production and marketing functions. The basic objectives are to maximize fit with customer's needs and demands, ensure quality assurance, minimize time to market, and control product development cost. It may be an intelligent initiative to involve the suppliers and the customers in the development process, beta testing, fault tree and failure mode effects analysis and TFPG as part of quality control measures. It is really challenging to manage new product development team through diversity, knowledge base, multiple skills, problem solving capability, cooperative corporate culture and intelligent communication protocol at optimal administrative costs.

Let us analyze skill-style-support. The workforces involved in this technological
innovation 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 orkforce
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 the innovation requires the support of great leadership style, effective governance, formation of special task force and expert committee, intelligent and rational corporate communication. 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.

What should be the ideal organization model for this technological innovation? A traditional functionally centered organization model may not be suitable for supporting end-to-end healthcare process. Such process management is more than a way to improve the performance of individual processes; it is a way to operate and manage a business. An enterprise that has institutionalized process management and aligned management systems to support is a process enterprise. It is centered on its customers, managed around its processes and is aligned around a common, customer oriented goal. The business models of top technological innovations require the support of a process enterprise structure enabled with advanced information and communication technology. The structure should have project, design, production, supply chain management maintenance, human resource management, sales & marketing and finance cells. The structure should be governed by an executive committee comprising of CEO and directors. The process managers should be able to identify core processes in the value chain; communicate throughout the organization about these critical processes; create and deploy measures regarding end-to-end process performance and define process owners with end-to-end authority for process design, resource procurement, process monitoring for redesign and improvement. The process enterprise requires a collaborative and cooperative work culture. Innovation in edidemic and pandemic control demands proper technological support in testing and medical diagnosis, proactive, reactive and preventive support for proper technology management. The technology needs the support of a collaborative enterprise model.

## 9. CONCLUSION

This session has explored the importance of a deep analytics based mechanism for cancer prevention in the context of human biological system. It presents a new framework of human biological system in terms of computing, data, networking, application and security schema of an information system based on analogical reasoning. DACPM promotes a hybrid approach which recognizes the role of both proactive and reactive approaches in making decisions on healthcare investment for cancer prevention. The reactive approach may outperform proactive one against the threats that never occur actually. Sometimes, reactive approach may be cost effective as compared to proactive approach. The basic building blocks of the proposed mechanism are threat analytics and adaptive secure multiparty computation. The threat analytics monitor the system performance of human biological system based on time series data, detects and analyzes different types of vulnerabilities on the biological system.
This work finds a set of interesting research agenda for future work: (a) explore new risk factors and causes of cancer, classifying cancers, opportunities for early detection and prevention and cost reduction of cancer care; (b) how to design an intelligent threat analytics; (c) how to design intelligent verification mechanisms; (d) how to rationalize DACPM, (e) how to quantify and code miscellaneous security intelligence parameters, (f) check the performance of kernel based learning algorithms with CNN, (g) how to apply integrated medicine for critical case (e.g. multiple organ failure syndrome) and exercise allopathic, homeopathy, herbal, yoga and naturopathy effectively for various purposes such as pain management, combating side effects of radiation and chemotherapy (e.g. hair fall, nausea, vomiting), every cancer patient requires specific treatment considering complexity of disease and (h) explore new approaches of cancer prevention such as vaccination for auto-immunity, laser therapy, integrated and regenerative medicine, precision medicine, gene therapy and stem cell therapy and (i) is it possible to imagine the security schema of human biological system based on antivirus, firewalls and various cryptographic tools (e.g. encryption, decryption, digital signature and signcryption) apart from secure multi-party computation? The next session explores the strategic option of bio-medical instrumentation and organ transplantation for various types of cancers such as pancreatic and liver cancer.

The expert panel are summarizing the outcome of deep analytic on the evaluation of today's biotechnology technology. The diffusion of the technology is controlled by four factors: machine intelligence, security intelligence, collaborative intelligence and collective intelligence [Figure 5.5]. The machine intelligence considers a set of important criteria such as dominant design features, construction materials, system performance, biocompatibility and ease of use and deployment. It is essential to understand the fundamental principles, functions and mechanisms of the aforesaid biological organs through innovative experimental set up. The security intelligence considers safety, reliability, consistency, efficient surgical operation and reduced risk of infection. The design of biomedical devices must consider biological, chemical, mechanical, electrical and human factors of safety rationally. The collaborative intelligence demands proper integration and coordination among patient care chain, design chain and supply chain of biomedical engineering. The collective intelligence is determined by efficient demand, supply and capacity management of critical resources. Another critical success factor of technology diffusion is correctness and rationality of scope analytics. For example, oral insulin has more strength and opportunities of growth as compared to artificial pancreas. The technology of artificial kidney and liver should explore the hidden potential of tissue engineering. On the other side, the technology of artificial cardiovascular devices and limbs should explore the strength of mechanical and electrical engineering and mechatronics. It is also an interesting research agenda to explore the scope of living biological organ transplantation through organ donation, organ banks and alternative medicines (e.g. integrated medicine, regenerative medicine, precision medicine) as a part of proactive and reactive healthcare approaches. Finally, deep analytics can streamline the diffusion of biomedical technology through efficient coordination and integration among 7-S elements.
<figure><img src="image_40.png" /><figcaption>Figure 5.5: Technology diffusion of biomedical technology</figcaption></figure>

This session presents artificial immune system mechanism (AIM). It is a new approach of epidemic and pandemic outbreak control. The basic building block of the mechanism is an analytics having multidimensional view of intelligent reasoning. The mechanism evaluates innate and adaptive system immunity in terms of collective, machine, security, collaborative and business intelligence. It is possible to redefine an efficient global healthcare policy for improved immunity and sustainable physical, mental and social health through reduction of artificial physical and mental stress. A biological system ensures optimal level of immunity by balancing natural and artificial intelligence (AI) based on intelligent reasoning. Effective control of epidemic and pandemic outbreak demands the innovation of smart biomedical devices such as non-contact infrared forehead thermometer. The digital thermal scanner is expected to have a set of important features such as capability to measure body temperature range with accuracy (e.g.0.3º C), ⁰C / ⁰F options, LCD backlight display, high or low body temperature indicator, high temperature alarm, auto power off after 15 seconds and warranty of one year.

The contribution of the present work is as follows. This novel concept of artificial immune mechanism has been applied to resolve the conflict between security intelligence and business intelligence for mitigating the risk of bio-terrorism today. The review of existing literature could not find out efficient mechanisms to counter bio-terrorism from the perspectives of security intelligence and business intelligence. The security intelligence has been defined weakly, incompletely and imprecisely. The system lacks intelligent model checking or system verification mechanisms based on rational threat analytics. The research methodology adopted in the present work includes case based reasoning, threat analytics and review of relevant literature on cryptography, secure multi-party computation and bio-terrorism. The logic of the bio-terrorism mechanism is explored through hypothetical case based reasoning on healthcare service chain, life-science supply chain, bio-technology and medical practice. The security intelligence is explored through threats analytics on malicious business intelligence.
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 AI reasoning, immunology and common sense healthcare from the childhood through an effective education and knowledge management system. It is not bio-inspired AI but the envision of AI inspired biological system which has a great potential to resolve the global healthcare problems significantly. AI has imagined the product concepts of highly complicated and costly artificial human organs such as artificial brain, heart, lungs, kidney, liver, pancreas, intestine, limbs, neural system, blood and cells though there are technological limitations and financial constraints of biomedical electronics, instrumentation, mechatronics, robotics, computational intelligence and materials science and also critical immunity issues. It is hard to develop and simulate artificial organs due to the inherent complexities of structure, material and mechanisms of the biological system. There are various risks of adaptive immunity and transmission of deadly diseases in artificial organ transplantation, artificial reproduction, common immunization programmes and breast milk feeding to the infants. Relaxation music, yoga and meditation is expected to be a good solution for the treatment of mental health though the modern entertainment world is getting flooded with ‘boom boom digital dhamaka’ and panic buttons through digital media and horror movies. AIM may be able to overcome some of those practically feasible constraints of the aforesaid imaginative reasoning through intelligent analytics and reasoning. AI community needs a new broad outlook, imagination and dreams to solve a complex problem through a set of simple mechanisms and solutions. Life is beautiful, let us apply AI for rational social choice to save the world.

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## Quiz

* Explain the technology of deep learning on prediction and prevention for cancer care? Justify it as a technology for humanity. What is the scope of this technology?

* What is the dominant design of the technology?

* What are the basic elements of the system architecture?
* What do you mean by technology security in cancer care? How to verify the security intelligence?

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

* How to manage resources for 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?

* Develop a deep learning algorithm for the prediction of cancer correctly?

* Explain the scope of regenerative, integrated, alternative, genomics and precision medicine for cancer care through SWOT analysis.

* Explain the technology of biomedical instrumentation for cancer care? Justify it as a technology for humanity. What is the scope of biomedical instrumentation technology?

* What is the dominant design of the biomedical technology?

* What are the basic elements of the system architecture?

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

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

* How to manage resources for this innovation project?

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

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

* Explain the scope of laser therapy, pervasive computing and surgical robotics for cancer care from the test cases stated in section 9.

* Can you design an automated biomedical test kit for cancer care? Show the system architecture.

* 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?

# APPENDIX

This section highlights the application of DACPM for nine different types of cancer.

## A. Cancer of Mind

**Psycho-oncology**: Psychiatric oncology is the study of psychiatric and social aspects of cancer such as cause, maintenance and prognosis of cancer, emotional reactions, psychiatric disorders, stress management and communication skills of the oncologists in revealing bad news and handling difficult questions and counseling. It is essential to understand psycho-neuro-endocrino-immunological mechanisms of the cancer patients. The psychological responses to cancer arise from knowledge of life-threatening diagnosis, uncertainty, financial burden and fear of death. The emotional responses arise from pain, nausea and unwanted side-effects of medical, surgical, and radiation treatments. This treatment also addresses various issues such as diet and nutritional supplements, yoga, meditation and physical exercises and aromatherapy.

## B. Neural control and coordination

**Agents**: Defender (e.g. human agent, doctor), Attacker (e.g. malicious agent or adversary);

**Model**: Human nervous system, sensory system;

**Objectives**: cancer prevention at optimal cost; focus : brain cancer [18,19];

**Constraints**: budget or financial constraint, resources, time, knowledge;

**Input**: Perception of human agent, performance measures of biological system or test data;

**Strategic moves**: deep learning, intelligent reasoning (perception, analytical, logical, common sense), optimal mix of proactive and reactive approaches, rational healthcare payment function and budget plan, adaptive secure multi-party computation;

**Revelation principle**: The agents preserve privacy of strategic data;

* **Defender**: The defenders share critical information collaboratively – collaborative planning, treatment and exception management (CPTEM).

* **Attacker**: The adversaries do not reveal the plan of malicious attack, information of targets and weak links in advance.

**Cancer Prevention Approaches:**
<figure><img src="image_41.png" /></figure>

Proactive approach:

* Identify targets

* application schema : Nervous and sensory system;

* networking schema :

* Nervous system : CNS – Brain, spinal chord; PNS, Neurons, nerves, cerebrospinal fluid, brain stem, meninges, neuroglia, ependymal cells, neurosecretory cells; cerebral nerve, spinal nerve;

* Sensory organs : eye, ear, nose, tongue, skin;

* computing schema : nerve impulse, reflex, neurotransmitter, neurosecretion, chemoreception; control and coordination, integration, memory, mechanism of sensory organs – see, hear, smell, feel, taste;

* data schema : sensory receptors – photo, chemo, thermo, electro and mechanoreceptors; structure of sensory organs;

* security schema : immunity, hormones, vitamins, minerals, blood, CSF;

* Threat modeling

* Call threat analytics and assess miscellaneous risk elements

* brain tumors : astrocytic, neuronal, embryonic and pineal;

* disorders of nervous system : memory loss, poliomyelitis, meningitis, sciatica, neuritis, synaptic delay, synaptic fatigue;

* eye defects – myopia, hypermetropia, astigmatism, presbiopia, cataract, glaucoma;

* skin cancer;

* throat cancer;

* Estimate probability (p) of occurrence along two dimensions : Low [L] and High [H];

* Estimate impact of risk i.e. sunk cost (c) along two dimensions : [L,H];

* Map threats into a set of risk profiles or classes : LL, LH, HL and HH;

* Estimate requirements of healthcare in terms of demand plan ($P^p$);

* Explore risk mitigation plan ($P^m$) : accept / transfer / remove / mitigate risks.

* Optimal diet intake to fight against malnutrition;

* Life-style : yoga and physical activities, stress control through meditation;

* Eye, ear and skin care against hostile climate (e.g. snowfall, scorching sunshine)

* Autoimmunity through vaccination

<figure><img src="image_42.png" /></figure>

Reactive approach:
* adopt sense-and-respond strategy based on following symptoms of brain cancer : **headache**, **weakness**, **clumsiness**, difficulty in walking, **seizures**, altered mental status like changes in concentration, memory, attention or alertness, intellectual capacity or emotional response, **nausea**, **vomiting**, lethargy, blurred **vision** and difficulty with speech;

* assess risks of single or multiple attacks on the human biological system; analyze performance, sensitivity, trends, exception and alerts.

♦ what is corrupted or compromised : Is the brain tumor malignant or benign?

♦ time series analysis : what occurred? what is occuring? what will occur?

♦ insights : how and why did it occur? do cause-effect analysis.

■ genetic factors

■ environmental effects

■ radiation

■ HIV infection

■ smoking

♦ recommend : what is the next best action?

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

* verify security intelligence of application, computing, networking, security and data schema of biological system.

♦ Level1: correctness, fairness, accountability, transparency, rationality, trust, commitment;

♦ Level 2: authentication, authorization, correct identification, privacy, audit;

♦ Level3: safety, reliability, consistency, liveness, deadlock-freeness, reachability, resiliency;

♦ Level4: stability, system dynamics, quality of application integration.

* Explore risk mitigation plan (P^r_d and P^r_m).

♦ Detection of viable tumor tissue → tumor delineation → selection of the best biopsy site → non-invasive tumor grading → therapy planning → monitoring tumor response;

♦ MRI and CT scan of brain tumor (Refer Deep Learning Algorithm of section 5.1);

♦ Biopsy trough surgery of brain tumor;

♦ Treating viral and bacterial infection, chronic inflammation, pain;

♦ Automatic drug injection into malignant brain tumor through nano-chip implanted into brain.

<figure><img src="image_43.png" /></figure>

Fight against bad luck : Identify critical risk elements.

♦ Genetic disorder (sex, race, ethnicity, somatic mutation)
* Reproductive disorder (flaws in organ formation and development since birth, personal, hormonal and family history)

♦ Injuries from accidents, war and crime

♦ Occupational exposure

♦ Environmental pollution (e.g. dust, sound pollution)

* Hostile climate, weather and other locational disadvantages, exposure to sunshine

♦ Malnutrition due to poverty

* Develop risk mitigation plan in terms of organ transplantation, surgical operation, and migration of human civilization from risky zone.

Payment function:

♦ Select dominant strategy of healthcare investment from the options of reinforcement on the weakest link, experimental treatment, process re-engineering, transformational and renewal.

♦ Estimate aspiration point, reservation point, strong, weak, indifference and veto thresholds in healthcare.

♦ Trade-off proactive vs. reactive security; assign weights to each approach.

♦ Allocate healthcare budget in the ratio x:y:z where x: fund for proactive approach, y : fund for reactive approach and z: health insurance premium;

Output: Cancer prevention plan

C. Chemical coordination and integration

Agents: Defender (e.g. human agent, doctor), Attacker (e.g. malicious agent or adversary);

Model: Human endocrine system;

Objectives: cancer prevention at optimal cost; Focus : breast cancer [20,21];

Constraints: budget or financial constraint, resources, time, knowledge;

Input: Perception of human agent, performance measures of biological system or test data;

Strategic moves: deep learning, intelligent reasoning (perception, analytical, logical, common sense), optimal mix of proactive and reactive approaches, rational healthcare payment function and budget plan, adaptive secure multi-party computation;

Revelation principle: The agents preserve privacy of strategic data;

♦ Defender : The defenders share critical information collaboratively – collaborative planning, treatment and exception management (CPTEM);

♦ Attacker : The adversaries do not reveal the plan of malicious attack, information of targets and weak links in advance.

Cancer Prevention Approaches:

<figure><img src="image_44.png" /></figure>

Proactive approach:

• Identify targets :
* application schema : Endocrine, Exocrine and Heterocrine system, Breast;

* networking schema : Glands – hypothalamus, pituitary, pineal, thyroid, parathyroid, thymus, adrenals, pancreas, gonads : testes and ovaries, kidneys;

* computing schema : coordination between endocrine and nervous system, interaction among glands, hormone action mechanism ( formation of Camp);

* data schema : hormones (informational molecules secreted by endocrine cells), hypothalamus – neurohormones > release hormones (RH), inhibitory hormones (IH); pituitary – FSH LH, GTH, TSH, ACTH, GH (*), LTH, OT; pineal – melatonin; thyroid – thyroxine (**), calcitonin; parathyroid – PTH (#), thymus - thymosine, adrenals - aldosterone, glucocorticoids, sexcorticoids (##); pancreas – insulin ($), glucagon, SS; gonads : testes – LH and ovaries – Estrogen, Progesterone and Relaxin; kidneys - Renin; primary, secondary and final targets;

* security schema : innate and adaptive immunity, hormones, vitamins, minerals;

* **Threat modeling**

* Call threat analytics, understand molecular switches and assess miscellaneous risk elements of breast cancer:

* age (old age increases risk)

* gender ( females with higher risk)

* race

* reproductive factors (e.g. infertility, menarche age, menopause age, age of first pregnancy)

* parity (nulliparous women at higher risk)

* family history (inherited genetic mutation)

* obesity and weight

* breast density (higher density with higher risk)

* radiation exposure

* side-effects of hormone replacement therapy, cross-sex hormone therapy and birth controlling pills

* Assess the risks of other disorders

* over secretion : gigantism (*); grave's disease(**), osteoporosis (#);

* deficiency : dwarfism(*), goitre(**), addison's disease (##), diabetes mellitus ($);

* Estimate probability (*p*) of occurrence along two dimensions : Low [L] and High [H];

* Estimate impact of risk i.e. sunk cost (c) along two dimensions : [L,H];

* Map threats into a set of risk profiles or classes : LL, LH, HL and HH;
* Estimate requirements of healthcare in terms of demand plan ($P^d$);

* Explore risk mitigation plan ($P^m$) : accept / transfer / remove / mitigate risks.

* Optimal diet intake to fight against malnutrition;

* Life-style : Avoid smoking and alcohols, food habit, drug addiction control, obesity and overweight control through yoga and physical activities, stress control through meditation;

* Proactive risk mitigation strategies for breast cancer

* Early detection through self-breast examination (SBE) : 'know your breast';

* Rational diet chart, yoga and physical exercises;

* Diabetes control;

* Avoid wearing tight dress;

* Safe massage for breast development exercises;

* Caution: violent love-life

<figure><img src="image_45.png" /></figure>

## Reactive approach:

* adopt sense-and-respond strategy.

* assess risks of single or multiple attacks on the human biological system; analyze performance, sensitivity, trends, exception and alerts.

* what is corrupted or compromised?

* time series analysis : what occurred? what is occuring? what will occur?

* insights : how and why did it occur? do cause-effect analysis.

* recommend : what is the next best action?

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

* verify security intelligence of application, computing, networking, security and data schema of biological system.

* Level 1: correctness, fairness, accountability, transparency, rationality, commitment;

* Level 2: authentication, authorization, correct identification, privacy, audit;

* Level 3: reliability, consistency, liveness, resiliency;

* Level 4: stability, system dynamics, quality of application integration.

* Explore risk mitigation plan ($P^d$ and $P^m$).

* Breast cancer : Personalized screening

* Do clinical breast examination (CBE) → Data visualization

* Convolutional network for tumor detection in breast mammography (Refer Deep Learning Algorithm of section 5.1);
* Caution of mammography screening : radiation exposure, anxiety, false positives and over diagnosis;

* Integrated medicine

* Mastectomies

<figure><img src="image_46.png" /></figure>

Fight against bad luck : Identify critical risk elements.

* Genetic disorder (sex, race, ethnicity, somatic mutation)

* Reproductive disorder (flaws in organ formation and development since birth, personal, hormonal and family history)

* Side effects of medical treatment (e.g. hormone therapy)

* Malnutrition due to poverty

* Develop risk mitigation plan in terms of surgical operation, gene therapy, stem cell therapy.

Payment function:

* Select dominant strategy of healthcare investment from the options of reinforcement on the weakest link, experimental treatment, process re-engineering, transformational and renewal.

* Estimate aspiration point, reservation point, strong, weak, indifference and veto thresholds in healthcare.

* Trade-off proactive vs. reactive security; assign weights to each approach.

* Allocate healthcare budget in the ratio x:y:z where x: fund for proactive approach, y : fund for reactive approach and z: health insurance premium;

Output: Cancer prevention plan

Deep learning algorithm for breast cancer [22] :

Objective: Computer aided breast cancer detection and diagnosis with improved accuracy; avoid the limitations of qualitative visual analysis with microscope like lack of standardization, diagnostic errors and excessive cognitive load, precision medical treatment through computational image analysis;

Input : millions of training patches;

System Architecture: Deep Convolutional Neural Network;

Procedure of cancer metastasis detection :

* a patch-based classification stage

* a heat map based post processing stage

Output: identification of cancer metastases from whole slide images of breast sentinel lymph nodes; make patch-level predictions to discriminate tumor patches from normal-patches.

D. Digestive system

Agents: Defender (e.g. human agent, doctor), Attacker (e.g. malicious agent or adversary);

Model: Human digestive system;

Objectives: cancer prevention at optimal cost;
**Constraints:** budget or financial constraint, resources, time, knowledge;

**Input:** Perception of human agent, performance measures of digestive system or test data;

**Strategic moves:** deep learning, intelligent reasoning (perception, analytical, logical, common sense), optimal mix of proactive and reactive approaches, rational healthcare payment function and budget plan, adaptive secure multi-party computation;

**Revelation principle:** The agents preserve privacy of strategic data;

* **Defender** : The defenders share critical information collaboratively – collaborative planning, treatment and exception management (CPTEM).

* **Attacker** : The adversaries do not reveal the plan of malicious attack, information of targets and weak links in advance.

## Cancer Prevention Approaches:

<figure><img src="image_47.png" /></figure>

### Proactive approach:

* **Identify targets**

* application schema : digestive system;

* networking schema :

* alimentary canal – mouth, vestibule, oral cavity – tongue, teeth, pharynx, oesophagus, stomach, small intestine, large intestine;

* digestive glands – salivary gland, gastric glands, liver, pancreas, intestinal glands;

* computing schema :

* nutrition mechanisms – autotrophic, holophytic, heterotrophic, symbiotic and holozoic;

* movement of alimentary canal;

* hormonal control of digestive secretion;

* ingestion, digestion - intracellular, extracellular and mixed, egestion, absorption and assimilation;

* **data schema** : nutrients – food (carbohydrates, protein, fat), minerals, vitamins, bile;

* **security schema** : immunity, enzymes, bile, gastric juice, hormones, vitamins, minerals;

* **Threat modeling**

* Call threat analytics and assess miscellaneous risk elements:

* malnutrition, over nutrition,

* incomplete digestive tract,

* Gastrointestinal cancer [23,24,25]

* gastric, gastro esophageal junction and esophageal cancer (adenocarcinoma) with risk elements like low consumption of fruits and vegetables, high intake of N-compounds in salted and preserved foods and occupational exposure in coal mining and nickel, rubber and timber processing industries, high meat consumption,
smoking, alcohol consumption, gastric surgery and reproductive hormones

* oral cancer

* pancreatic Cancer with risk elements like tobacco smoking, diabetes and chronic pancreatitis, diet, body mass index and genetic syndrome

* hepatocellular carcinoma (HCC) or liver cancer caused by chronic viral hepatitis, alcohol and cirrhosis, aflatoxin, OCP and genetic metabolic factors, toxic exposures of medicine

* small bowel cancer and appendiceal tumors

* colorectal cancer with risk factors such as somatic or inherited genetic mutation, diet, obesity, inflammatory bowel diseases,

* anal cancer

* neuroendocrine tumor

* Estimate probability (p) of occurrence along two dimensions : Low [L] and High [H];

* Estimate impact of risk i.e. sunk cost (c) along two dimensions : [L,H];

* Map threats into a set of risk profiles or classes : LL, LH, HL and HH;

* Estimate requirements of healthcare in terms of demand plan ($P^p$);

* Explore risk mitigation plan ($P^m$) : accept / transfer / remove / mitigate risks.

* Auto-immunity and vaccination against hepatitis B and C;

* Optimal diet intake to fight against malnutrition;

* Life-style : Avoid smoking and alcohols, food habit, drug addiction control, obesity and overweight control through yoga and physical activities

* Oral cancer from wild polygamy;

<figure><img src="image_48.png" /></figure>

### Reactive approach:

* adopt sense-and-respond strategy.

* assess risks of single or multiple attacks on the human biological system; analyze performance, sensitivity, trends, exception and alerts.

* what is corrupted or compromised?

* time series analysis : what occurred? what is occuring? what will occur?

* insights : how and why did it occur? do cause-effect analysis.

* recommend : what is the next best action?

* predict: what is the best or worst that can happen?
* verify security intelligence of application, computing, networking, security and data schema of biological system.

♦ Level1: correctness, fairness, accountability, transparency, rationality, trust, commitment;

♦ Level 2: authentication, authorization, correct identification, privacy, audit;

♦ Level3: safety, reliability, consistency, liveness, deadlock-freeness, reachability, resiliency;

♦ Level4: stability, system dynamics, quality of application integration.

* Explore risk mitigation plan.

♦ Gastric cancer : surgery, perioperative chemotherapy, postoperative chemoradiotherapy;

♦ Pancreatic cancer : immunotherapy, CT scan, biopsy, surgery, systemic therapy or chemoradiation;

♦ Liver cancer : systemic chemotherapy, hormonal therapy, clinical trial of antiangiogenesis agents, radiation therapy;

♦ Colorectal cancer : fecal occult blood testing, barium x-ray, colonoscopy, sigmoidoscopy, genetic testing, radiotherapy, surgery;

♦ Do medical testing → Data visualization of images (e.g. liver, pancreas and alimentary canal, Refer Deep Learning Algorithm of section 5.1)

♦ Treating viral and bacterial infection, chronic inflammation, pain, diabetes, cholesterol and hormonal imbalance;

♦ Insulin injection

♦ Artificial liver and pancreas transplantation

<figure><img src="image_49.png" /></figure>

Fight against bad luck : Identify critical risk elements.

♦ Genetic disorder (sex, race, ethnicity, somatic mutation)

♦ Reproductive disorder (flaws in organ formation and development since birth, personal, hormonal and family history)

♦ Injuries from accidents, war and crime

♦ Occupational exposure

♦ Water and soil pollution

♦ Hostile climate, weather and other locational disadvantages, exposure to sunshine

♦ Malnutrition due to poverty

* Develop risk mitigation plan in terms of organ transplantation, surgical operation, gene therapy, stem cell therapy and migration of human civilization from risky zone.

Payment function:
* Select dominant strategy of healthcare investment from the options of reinforcement on the weakest link, experimental treatment, process re-engineering, transformational and renewal.

* Estimate aspiration point, reservation point, strong, weak, indifference and veto thresholds in healthcare.

* Trade-off proactive vs. reactive security; assign weights to each approach.

* Allocate healthcare budget in the ratio x:y:z where x: fund for proactive approach, y : fund for reactive approach and z: health insurance premium;

Output: Cancer prevention plan

E. Respiratory system

Agents: Defender (e.g. human agent, doctor), Attacker (e.g. malicious agent or adversary);

Model: Human respiratory system;

Objectives: cancer prevention at optimal cost; focus : lung cancer [ 26,27,28];

Constraints: budget or financial constraint, resources, time, knowledge;

Input: Perception of human agent, performance measures of biological system or test data;

Strategic moves: deep learning, intelligent reasoning (perception, analytical, logical, common sense), optimal mix of proactive and reactive approaches, rational healthcare payment function and budget plan, adaptive secure multi-party computation;

Revelation principle: The agents preserve privacy of strategic data;

* **Defender** : The defenders share critical information collaboratively – collaborative planning, treatment and exception management (CPTEM).

* **Attacker** : The adversaries do not reveal the plan of malicious attack, information of targets and weak links in advance.

Cancer Prevention Approaches:

<figure><img src="image_50.png" /></figure>

Proactive approach:

* Identify targets

* application schema : respiratory system;

* networking schema : respiratory tract, respiratory organs – lungs, tissues, larynx;

* computing schema : breathing mechanism – inspiration, air filtering, exchange of gases in alveoli, expiration; nervous and chemical control of respiration, transport of gases in blood (O₂, CO₂), artificial respiration mechanism;

* data schema (^) : respiratory rate, pulmonary air volume and capacity, composition of inspired, expired and alveolar air, TV, IRV,ERV,RV,VC,IC,FRC,TLC;

* security schema : innate and adaptive immunity, hormones, blood;

* Threat modeling
* Call threat analytics function and assess miscellaneous risk elements: lung cancer,

* Lung cancer: small cell and non-small cell lung cancer

* Tobacco exposure: duration and intensity of tobacco use;

* Exposure to asbestos, benzene, coal tar and radon gas;

* Environmental or industrial exposure to arsenic, chromium, chloromethyl ether, vinyl chloride and polycyclic aromatic hydrocarbons;

* Genetic predisposition

* Other disorders of respiratory system: hypoxia, asphyxia, bad cold, bronchitis, bronchial asthma, pneumonia, emphysema, occupational respiratory disorder, carbon monoxide poisoning;

* Throat cancer and ENT

* Estimate probability (p) of occurrence along two dimensions: Low [L] and High [H];

* Estimate impact of risk i.e. sunk cost (c) along two dimensions: [L,H];

* Map threats into a set of risk profiles or classes: LL, LH, HL and HH;

* Estimate requirements of healthcare in terms of demand plan ($P^d$);

* Explore risk mitigation plan ($P^m$): accept / transfer / remove / mitigate risks.

* Auto-immunity and vaccination;

* Optimal diet intake to fight against malnutrition;

* Life-style: Avoid smoking and alcohols, food habit, drug addiction control, obesity and overweight control, yoga (deep breathing exercises) and physical activities, stress control through meditation;

<figure><img src="image_51.png" /></figure>

## Reactive approach:

* adopt sense-and-respond strategy.

* assess risks of single or multiple attacks on the human respiratory system; analyze performance, sensitivity, trends, exception and alerts.

* what is corrupted or compromised?

* time series analysis: what occurred? what is occurring? what will occur?

* insights: how and why did it occur? do cause-effect analysis.

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

* verify security intelligence of application, computing, networking, security and data schema of biological system.

* Level1: correctness, fairness, accountability, transparency, rationality, trust, commitment;

* Level 2: authentication, authorization, correct identification, privacy, audit;

* Level3: safety, reliability, consistency, liveness, deadlock freeness, reachability, resiliency;

* Level4: stability, system dynamics, quality of application integration.

* Explore risk mitigation plan.

* Prevention measures of lung cancer : stop smoking, early detection and screening and chemoprevention;

* Do medical testing of data schema (^);

* Data visualization of X-ray report of lungs and also biopsy report;

* Treating tobacco induced injuries in the air way, viral and bacterial infection, chronic inflammation; medication against chronic disease;

* Limited disease of lung cancer (LD):
  * combined chemo radiation therapy

* radiation intensity

* timing of chemotherapy : Sequential, concurrent, and alternating chemotherapy

* surgery

* Extensive disease of lung cancer (ED):
  * Select correct treatment algorithm

* systematic chemotherapy

* immunotherapy through tumor vaccines

<figure><img src="image_52.png" /></figure>

Fight against bad luck : Identify critical risk elements.

* Genetic disorder

* Reproductive disorder (flaws in organ formation and development since birth)

* Injuries from accidents, war and crime

* Occupational exposure

* Air and soil pollution

* Hostile climate, weather and other locational disadvantages, exposure to sunshine, snowfall and very cold climate;

* Malnutrition due to poverty

* Develop risk mitigation plan in terms of surgical operation and migration of human civilization from risky zone.

Payment function:
* Select dominant strategy of healthcare investment from the options of reinforcement on the weakest link, experimental treatment, process re-engineering, transformational and renewal.

* Estimate aspiration point, reservation point, strong, weak, indifference and veto thresholds in healthcare.

* Trade-off proactive vs. reactive security; assign weights to each approach.

* Allocate healthcare budget in the ratio x:y:z where x: fund for proactive approach, y : fund for reactive approach and z: health insurance premium;

Output: Cancer prevention plan

## F. Body fluids circulation – Cardiovascular system

Agents: Defender (e.g. human agent, doctor), Attacker (e.g. malicious agent or adversary);

Model: Human biological system – (a) body, (b) mind;

Objectives: cancer prevention at optimal cost; focus : leukemia or blood cancer [29,30];

Constraints: budget or financial constraint, resources, time, knowledge;

Input: Perception of human agent, performance measures of biological system or test data;

Strategic moves: deep learning, intelligent reasoning (perception, analytical, logical, common sense), optimal mix of proactive and reactive approaches, rational healthcare payment function and budget plan, adaptive secure multi-party computation;

Revelation principle: The agents preserve privacy of strategic data;

* Defender : The defenders share critical information collaboratively – collaborative planning, treatment and exception management (CPTEM).

* Attacker : The adversaries do not reveal the plan of malicious attack, information of targets and weak links in advance.

Cancer Prevention Approaches:

<figure><img src="image_53.png" /></figure>

### Proactive approach:

* Identify targets

* application schema : cardiovascular system;

* networking schema : heart, blood vascular system – open and closed circulatory system, arterial and venous system, blood, tissue fluid, lymphatic system – spleen, thymus, tonsils;

* computing schema : pulmonary and systemic circulation, blood clotting or coagulation mechanism, blood flow mechanism;

* data schema : blood group, efficiency of heart, heart rate, heart output, pulse, heart sound;

* security schema : blood, lymph, water, minerals, vitamins, hormones;

* Threat modeling

* Call threat analytics and assess miscellaneous risk elements :
* blood cancer / lukemia

* Acute lymphoblastic leukemia (ALL) : proliferation and accumulation of lymphoid progenitor cells in blood, bone marrow and tissues for both the children and adult; bone marrow failure, malaise, fatigue, bleeding fever, night sweats, weight loss and abnormal White blood cell (WBC) count;

* Adolescent and young adult acute lymphoblastic leukemia;

* Acute myeloid leukemia (AML) due to genetic mutations and chromosomal aberrations with symptom of Fanconi anemia;

* Chronic lymphocytic leukemia (CLL): clonal hematopoietic disorder;

* Chronic myeloid leukemia (CML)

* blood pressure disorder (SP, DP)

* cardiovascular diseases : Stroke (CVA or cardiovascular accident), rheumatic heart disease (RHD), coronary artery disease (CAD), hypertensive heart disease, atrial fibrillation, tachycardia, vaculities;

* Estimate probability (p) of occurrence along two dimensions : Low [L] and High [H];

* Estimate impact of risk i.e. sunk cost (c) along two dimensions : [L,H];

* Map threats into a set of risk profiles or classes : LL, LH, HL and HH;

* Estimate requirements of healthcare in terms of demand plan ($P^p$);

* Explore risk mitigation plan ($P^m$) : accept / transfer / remove / mitigate risks.

* Auto-immunity and vaccination

* Optimal diet intake to fight against malnutrition

* Life-style : Avoid smoking and alcohols, food habit, drug addiction control

<figure><img src="image_54.png" /></figure>

Reactive approach:

* adopt sense-and-respond strategy.

* assess risks of single or multiple attacks on the human biological system; analyze performance, sensitivity, trends, exception and alerts.

* what is corrupted or compromised?

* time series analysis : what occurred? what is occuring? what will occur?

* insights : how and why did it occur? do cause-effect analysis.
* recommend: what is the next best action?

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

* verify security intelligence of application, computing, networking, security and data schema of biological system.

* Level1: correctness, fairness, accountability, transparency, rationality, trust, commitment;

* Level 2: authentication, authorization, correct identification, privacy, audit;

* Level3: safety, reliability, consistency, liveness, deadlock-freeness, reachability, resiliency;

* Level4: stability, system dynamics, quality of application integration.

* Explore risk mitigation plan ($P^r_d$ and $P^r_m$).

* Diagnosis of ALL: immunophenotyping, cytogenetic-molecular profiling, allogeneic stem cell transplantation, salvage therapy, immunotherapy;

* Risk stratification of AML based on patient related variables (age and performance) and disease related predictors (cytogenetic and molecular characteristics);

* Induction therapy, supportive care and stem cell transplantation for AML;

* Do medical testing → Data visualization of ECG

* Treating viral and bacterial infection, chronic inflammation, pain, diabetes, cholesterol and hormonal imbalance

* Medication for blood pressure control

* Integrated medicine

* Regenerative medicine

<figure><img src="image_55.png" /></figure>

Fight against bad luck : Identify critical risk elements.

* Genetic disorder (sex, race, ethnicity, somatic mutation)

* Reproductive disorder (personal, hormonal and family history)

* Occupational exposure

* Air, water and sound pollution

* Hostile climate, weather and other locational disadvantages, exposure to sunshine

* Malnutrition due to poverty

* Develop risk mitigation plan in terms of organ transplantation, surgical operation, blood substitution and migration of human civilization from risky zone.

Payment function:

* Select dominant strategy of healthcare investment from the options of reinforcement on the weakest link, experimental treatment, process re-engineering, transformational and renewal.
* Estimate aspiration point, reservation point, strong, weak, indifference and veto thresholds in healthcare.

* Trade-off proactive vs. reactive security; assign weights to each approach.

* Allocate healthcare budget in the ratio x:y:z where x: fund for proactive approach, y : fund for reactive approach and z: health insurance premium;

Output: Cancer prevention plan

G. Excretory system

Agents: Defender (e.g. human agent, doctor), Attacker (e.g. malicious agent or adversary);

Model: Human excretory system;

Objectives: cancer prevention at optimal cost; focus : renal cancer, skin cancer [31];

Constraints: budget or financial constraint, resources, time, knowledge;

Input: Perception of human agent, performance measures of biological system or test data;

Strategic moves: deep learning, intelligent reasoning (perception, analytical, logical, common sense), optimal mix of proactive and reactive approaches, rational healthcare payment function and budget plan, adaptive secure multi-party computation;

Revelation principle: The agents preserve privacy of strategic data;

* **Defender** : The defenders share critical information collaboratively – collaborative planning, treatment and exception management (CPTEM).

* **Attacker** : The adversaries do not reveal the plan of malicious attack, information of targets and weak links in advance.

Cancer Prevention Approaches:

<figure><img src="image_56.png" /></figure>

Proactive approach:

* Identify targets

* application schema : excretory system;

* networking schema : kidney - nephron, ureters, urinary bladder and urethra; skin – sweat, lungs – CO2;

* computing schema : urea and urine formation, mechanism of kidney;

* data schema : urine and stool – quantity, physical properties, chemical composition and renal threshold;

* security schema : immunity, water, vitamins, minerals;

* Threat modeling

* Call threat analytics function and assess various risk elements :

* renal cancer : tobacco smoking, regular alcohol consumption, food habit (e.g. high intake of animal protein and fat), polluted drinking water, obesity, lack of physical activities, reproductive factors and hormones, medical conditions : hypertension, diabetes, urinary tract disease, drug addiction, radiation, occupational exposure : chemical, oil and
gas, Pb, Cd, asbestos, gasoline and hydrocarbons, genetic susceptibility;

* kidney disorder - renal failure, kidney stone; uremia, cystitis, glomerrulonephritis, pyelonephritis;

* urinary bladder cancer

* prostate cancer

* skin cancer : actinic keratosis, melanoma skin cancer, non-melanoma skin cancer;

* Estimate probability (p) of occurrence along two dimensions : Low [L] and High [H];

* Estimate impact of risk i.e. sunk cost (c) along two dimensions : [L,H];

* Map threats into a set of risk profiles or classes : LL, LH, HL and HH;

* Estimate requirements of healthcare in terms of demand plan ($P^d$);

* Explore risk mitigation plan ($P^m$) : accept / transfer / remove / mitigate risks.

* Auto-immunity and vaccination;

* Optimal diet (e.g. fruits, vegetables) and water intake to fight against malnutrition;

* Life-style : Avoid smoking and alcohols, food habit (e.g soft drinks), drug addiction control, wild polygamy, obesity and overweight control through yoga and physical activities;

<figure><img src="image_57.png" /></figure>

## Reactive approach:

* adopt sense-and-respond strategy.

* assess risks of single or multiple attacks on the human biological system; analyze performance, sensitivity, trends, exception and alerts.

* what is corrupted or compromised?

* time series analysis : what occurred? what is occuring? what will occur?

* insights : how and why did it occur? do cause-effect analysis.

* recommend : what is the next best action?

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

* verify security intelligence of application, computing, networking, security and data schema of biological system.

* Level1: correctness, fairness, accountability, transparency, rationality, trust, commitment;

* Level 2: authentication, authorization, correct identification, privacy, audit;

* Level3: safety, reliability, consistency, liveness, deadlock-freeness, reachability, resiliency;
* Level4: stability, system dynamics, quality of application integration.

* Explore risk mitigation plan.

* skin cancer :

* actinic keratosis - cryotherapy, topical treatment;

* melanoma skin cancer : biopsy - shave, punch, excisional, incisional, wound care;

* non-melanoma skin cancer : topical treatment, ED&C, excision, radiotherapy;

* renal cancer: immunotherapy, radiotherapy and supportive care, systemic therapy of metastatic disease, adjuvant therapy, surgical treatment of renal cell carcinoma, interventional radiology, laparoscopic radical nephrectomy;

* Do medical testing → Data visualization of kidney scan (Refer Deep Learning Algorithm of section 5.1, transferring a Convolutional Neural Network, trained on images for detection of kidney problem in ultrasound images); detection of renal tumor by USG, MRI and CT scan;

* Treating viral and bacterial infection, chronic inflammation, pain, diabetes, cholesterol and hormonal imbalance;

* Artificial kidney or kidney transplantation

* Integrated medicine

<figure><img src="image_58.png" /></figure>

* Fight against bad luck : Identify critical risk elements.

* Genetic disorder (sex, race, ethnicity, somatic mutation)

* Reproductive disorder (flaws in organ formation and development since birth, personal, hormonal and family history)

* Injuries from accidents, war and crime

* Occupational exposure

* Water pollution

* Hostile climate, weather and other locational disadvantages,

* Malnutrition due to poverty

* Develop risk mitigation plan in terms of organ transplantation and surgical operation and migration of human civilization from risky zone.

**Payment function:**

* Select dominant strategy of healthcare investment from the options of reinforcement on the weakest link, experimental treatment, process re-engineering, transformational and renewal.

* Estimate aspiration point, reservation point, strong, weak, indifference and veto thresholds in healthcare.

* Trade-off proactive vs. reactive security; assign weights to each approach.
* Allocate healthcare budget in the ratio *x:y:z* where *x*: fund for proactive approach, *y*: fund for reactive approach and *z*: health insurance premium;

Output: Cancer prevention plan

## H. Locomotion and Movement

Agents: Defender (e.g. human agent, doctor), Attacker (e.g. malicious agent or adversary);

Model: Human biological system – (a) body, (b) mind;

Objectives: cancer prevention at optimal cost; focus: bone cancer [32,33];

Constraints: budget or financial constraint, resources, time, knowledge;

Input: Perception of human agent, performance measures of biological system or test data;

Strategic moves: deep learning, intelligent reasoning (perception, analytical, logical, common sense), optimal mix of proactive and reactive approaches, rational healthcare payment function and budget plan, adaptive secure multi-party computation;

Revelation principle: The agents preserve privacy of strategic data;

* **Defender**: The defenders share critical information collaboratively – collaborative planning, treatment and exception management (CPTEM).

* **Attacker**: The adversaries do not reveal the plan of malicious attack, information of targets and weak links in advance.

Cancer Prevention Approaches:

<figure><img src="image_59.png" /></figure>

### Proactive approach:

* **Identify targets:**

* application schema: human skeletal and muscular system;

* networking schema:

* skeleton – bone (skull, spinal column, ribs, sternum, girdles, limb), cartilage, joints;

* muscles – red and white;

* computing schema:

* Mechanism of metastasis to bone, inflammatory cytokines in osteolysis, prostate cancer bone colonization causing metabolic imbalance between osteoblasts and osteoclasts, tumor-bone interaction, suppression of bone formation;

* locomotion and movement mechanism, autonomic and induced movement,

* muscle contraction mechanism;

* data schema: oxygen debt, muscle fatigue;

* security schema: bone marrow, minerals, vitamin D;

* **Threat modeling**

* Call threat analytics and assess miscellaneous risk elements:

* Risk factors: age, gender, race, site distribution;

* bone cancer: bone pain, spinal chord suppression;

* osteosarcoma (primary and malignant bone tumor);
* multiple myeloma : bone destruction, hypercalcemia, neurological disorder;

* head and neck cancer, cervix cancer;

* Other disorders: sprain, arthritis, osteoporosis, dislocation, slipped disc, fracture of bones, bursitis, tetany, myasthenia gravis and muscular dystrophy.

* Estimate probability (p) of occurrence along two dimensions : Low [L] and High [H];

* Estimate impact of risk i.e. sunk cost (c) along two dimensions : [L,H];

* Map threats into a set of risk profiles or classes : LL, LH, HL and HH;

* Estimate requirements of healthcare in terms of demand plan ($P^d$);

* Explore risk mitigation plan ($P^m$) : accept / transfer / remove / mitigate risks.

* Auto-immunity and vaccination;

* Optimal diet intake to fight against malnutrition;

* Life-style : Avoid smoking and alcohols, food habit, drug addiction control, wild polygamy, obesity and overweight control;

* Fairplay : Take less risk in sports, games and adventure;

* yoga and physical muscular activities, stress control through meditation;

* Use computers, tablets and laptops with a safe posture.

<figure><img src="image_60.png" /></figure>

## Reactive approach:

* adopt sense-and-respond strategy.

* assess risks of single or multiple attacks on the human biological system; analyze performance, sensitivity, trends, exception and alerts.

* what is corrupted or compromised?

* time series analysis : what occurred? what is occuring? what will occur?

* insights : how and why did it occur? do cause-effect analysis.

* recommend : what is the next best action?

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

* verify security intelligence of application, computing, networking, security and data schema of biological system.

* Level1: correctness, fairness, accountability, transparency, rationality, trust, commitment;

* Level 2: authentication, authorization, correct identification, privacy, audit;
* Level3: safety, reliability, consistency, liveness, deadlock-freeness, reachability, resiliency;

* Level4: stability, system dynamics, quality of application integration.

* Explore risk mitigation plan.

* Bone cancer treatment: radio graphy, radio surgery, bone marrow transplant, treatment against side effects of hormonal therapy in breast and prostate cancer, bone pain management;

* Bone pain management through eradication of bone tumors, decreasing the impact of tumor induced bone loss, surgical stabilization of fractures and pain medications;

* Optimal therapy and treatment outcomes in head and neck cancer through precise identification of the primary tumor and also local, regional, and distant extent of disease.

* Combined modality therapy

* Induction chemotherapy

* Concomitant radiotherapy and chemotherapy

* Adjuvant Chemoradiotherapy

* Do medical testing → Data visualization of digital x-ray, molecular images of cancer cells growing in bones, detection of tumor cells in bone marrow;

* Treating viral and bacterial infection, chronic inflammation, pain, diabetes, cholesterol and hormonal imbalance;

* Physiotherapy

* Integrated medicine

<figure><img src="image_61.png" /></figure>

* Fight against bad luck: Identify critical risk elements.

* Genetic disorder (sex, race, ethnicity, somatic mutation)

* Reproductive disorder (flaws in organ formation and development since birth, personal, hormonal and family history)

* Injuries from accidents, war and crime

* Bone fracture in sports and games (e.g. football, rugby, boxing)

* Occupational exposure (e.g. mason)

* Environmental pollution

* Hostile climate, weather and other locational disadvantages;

* Malnutrition due to poverty

* Develop risk mitigation plan in terms of organ transplantation, surgical operation, and migration of human civilization from risky zone.

Payment function:
* Select dominant strategy of healthcare investment from the options of reinforcement on the weakest link, experimental treatment, process re-engineering, transformational and renewal.

* Estimate aspiration point, reservation point, strong, weak, indifference and veto thresholds in healthcare.

* Trade-off proactive vs. reactive security; assign weights to each approach.

* Allocate healthcare budget in the ratio x:y:z where x: fund for proactive approach, y : fund for reactive approach and z: health insurance premium;

Output: Cancer prevention plan

## I. Reproductive System

Agents: Defender (e.g. human agent, doctor), Attacker (e.g. malicious agent or adversary);

Model: Human reproductive system;

Objectives: cancer prevention at optimal cost; focus : (a) ovarian cancer; (b) testicular cancer;

Constraints: budget or financial constraint, resources, time, knowledge;

Input: Perception of human agent, performance measures of biological system or test data;

Strategic moves: deep learning, intelligent reasoning (perception, analytical, logical, common sense), optimal mix of proactive and reactive approaches, rational healthcare payment function and budget plan, adaptive secure multi-party computation;

Revelation principle: The agents preserve privacy of strategic data;

* Defender: The defenders share critical information collaboratively – collaborative planning, treatment and exception management (CPTEM).

* Attacker: The adversaries do not reveal the plan of malicious attack, information of targets and weak links in advance.

Cancer Prevention Approaches:

<figure><img src="image_62.png" /></figure>

Proactive approach:

* Identify targets :

* application schema : human reproductive system;

* networking schema :

* male : scrotum, testes, vasa efferentia, epididymes, vasa deferntia, ejaculatory ducts, urethra, penis; prostate glands;

* female : ovaries, fallopian tube, uterus, vagina, vulva, breast;

* computing schema : spermatogenesis, oogenesis, menstrual cycle, menopause, fertilization, cleavage, implantation, gastrulation, organogenesis, parturition, lactation;

* data schema : sperm, ovum, egg, zygote;

* security schema : hormones, minerals, vitamins;

* Threat modeling

* Call threat analytics and assess miscellaneous risk elements :
* Testicular cancer

* Metastatic germ cell cancer

* CSI Non-seminoma

* Ovarian cancer

* genetic risk factors : inherited susceptibility,

* hormonal risk factors (estrogen and
progesterone)

* age at menarche and age at menopause, gender, race

* pregnancy, parity and infertility

* lactation, benign gynecologic conditions and gynecologic surgery

* oral contraceptives

* hormone replacement therapy

* anthropometric factors

* diet and nutrition, lack of exercise and physical activity, life-style and environmental factors : smoking, alcohol consumption, asthma, drug use, occupational exposure

* other disorders : impotence, sterility, menstrual irregularity, prostetomegaly;

* Estimate probability (p) of occurrence along two dimensions : Low [L] and High [H];

♦ Estimate impact of risk i.e. sunk cost (c) along two dimensions :
[L,H];

♦ Map threats into a set of risk profiles or classes : LL, LH,HL and HH;

♦ Estimate requirements of healthcare in terms of demand plan;

♦ Explore risk mitigation plan : accept / transfer / remove / mitigate risks.

* Auto-immunity and vaccination;

- Optimal diet intake to fight against malnutrition;

* Life-style : Avoid smoking and alcohols, food habit, drug addiction control, wild polygamy, obesity and overweight control;

* yoga and physical activities, stress control through meditation;

* secure multi-party computation

<figure><img src="image_63.png" /></figure>

Reactive approach:

* adopt sense-and-respond strategy.

* assess risks of single or multiple attacks on the human biological system; analyze performance, sensitivity, trends, exception and alerts.

♦ what is corrupted or compromised?

♦ time series analysis : what occurred? what is occuring?
what will occur?
* insights : how and why did it occur? do cause-effect analysis.

* recommend : what is the next best action?

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

* verify security intelligence of application, computing, networking, security and data schema of biological system.

* Level1: correctness, fairness, accountability, transparency, rationality, trust, commitment;

* Level 2: authentication, authorization, correct identification, privacy, audit;

* Level3: safety, reliability, consistency, liveness, deadlock-freeness, reachability, resiliency;

* Level4: stability, system dynamics, quality of application integration.

* Explore risk mitigation plan.

* Testicular cancer

* USG detecting a painless swollen mass in testes

* Determination of AFP, LDH and hCG

* Surgical exploration in testis to detest germ cell tumor

* Orchiectomy

* Organ preserving surgery in case of benign histology

* Surveillance for low risk patients and adjuvant BEP chemotherapy for high risk patients and also risk adapted treatment

* First line treatment for metastatic disease and residual tumor resection

* Salvage treatment, late relapse and follow up

* Treatment of fertility and sexuality : hypogonadism, ejaculatory disorder, disorder with erectile function and libido, metabolic syndrome (MBS)

* Ovarian cancer:

* screening and early detection,

* early stage treatment : staging, adjuvant chemotherapy,

* advanced stage treatment : surgical debulking principle,

* chemotherapy for recurrent ovarian cancer;

* targeted molecular therapy (TMT)

* Treating viral and bacterial infection, chronic inflammation, pain, diabetes, cholesterol and hormonal imbalance;

* Radiotherapy

* Integrated medicine

<figure><img src="image_64.png" /></figure>

Fight against bad luck : Identify critical risk elements.
* Genetic disorder (sex, race, ethnicity, somatic mutation)

* Reproductive disorder (flaws in organ formation and development since birth, personal, hormonal and family history)

* Occupational exposure (e.g. high workload, stress)

* Environmental pollution

* Hostile climate, weather and other locational disadvantages

* Malnutrition due to poverty

* Develop risk mitigation plan in terms of organ transplantation, surgical operation, and migration of human civilization from risky zone.

Payment function:

* Select dominant strategy of healthcare investment from the options of reinforcement on the weakest link, experimental treatment, process re-engineering, transformational and renewal.

* Estimate aspiration point, reservation point, strong, weak, indifference and veto thresholds in healthcare.

* Trade-off proactive vs. reactive security; assign weights to each approach.

* Allocate healthcare budget in the ratio x:y:z where x: fund for proactive approach, y : fund for reactive approach and z: health insurance premium;

Output: Cancer prevention plan.
## SESSION 6: ENERGY & UTILITIES SECURITY for HUMANITY - SOLAR POWER ELECTRONICS, NANO SOLAR CELL, INDUCTION COOKER

**Event**: Technology for humanity and global security summit

**Venue**: Energy & utility security hall, Technology park : Sanada

**Time Schedule**: 10 a.m. – 1 p.m., 16.8.2020

**Agents**: Representatives of various global organizations (UN, UNICEF, UNESCO, WHO, World bank, Global Economic forum), Technology management experts from science and technology forums on renewable energy, Environmental engineers, Climate change and social activists, Social scientists, representatives and ministers from the departments of energy and utilities of developed, developing and underdeveloped countries, CEOs of solar power companies, business development consultants of energy and utilities sectors, Engineers and scientists of electrical, electronics, power plant, chemical engineering.

**Topic of discussion and key focus areas**: Energy security, Utilities security, Solar power, Solar induction cooker, Solar power electronics, Nano solar cell, Deep Analytics, Business model innovations, Solar microgrid, Technology diffusion, SWOT analysis, Pure drinking water supply, Mobile communication.

**Keynote speakers**: Dr. Paolo Maradona, Prof. Bruno Platini, Prof. Tony Fergunson, Prof. Johan Macacini, Dr. Robert Messi.

### 1. SCOPE

#### Scope Analytics

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

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

**Security parameters**: define a set of sustainable development goals.

* Energy security: clean and affordable power;

* Utilities security:

* pure drinking water: artificial rain, water conservation /* refer to session 2*/

* oil (petrol, diesel): /* refer to session 7*/

* gas: solar induction cooker may be a substitute of gas for cooking application;

* telecom: /* refer to session 8*/

* internet: /* refer to session 8*/

* computing: /* refer to session 8*/

* Poverty control

* Business model innovation

* Environmental pollution control

**Application domains**: Solar lighting system, solar power pack, consumer electronics and home appliances, solar water heater, solar charging for computing devices and
mobile phones, solar water pumps for agriculture, solar induction cooker, solar microgrid for rural electrification.

Prof. Tony Ferguson and Dr. Robert Messi have started the session exploring various applications of solar power system. The issues of water, oil (petrol, diesel) and telecom, computing and internet have been covered during sessions 2, 7 and 8 respectively. Entrepreneurial success depends on various factors. The critical success factors are associated with entrepreneurial motivation, creativity, business model innovation, rational and intelligent business plan, core competencies, new technology management, sustainable policy for economic growth, corporate social responsibilities, industry structure, government's support in terms of incentives and subsidies, dynamic role of entrepreneurial education institutes, business incubator, business cluster and good support of financial institutions. Let us first explore a set of innovative business models for solar power technology.

This session is focused on the problem of global energy security and has explored a set of fundamental research agendas: What should be the strategic moves for the diffusion of solar technology? What should be the dominant design of solar power system in terms of structure and security? What is the scope of solar technology? What should be the right innovation model? What is the outcome of a rational SWOT analysis on various types of energy? What is the outcome of solar technology life-cycle analysis? Solar power electronics and nanotechnology based solar cells are two critical success factors of the dominant design of solar power system for the improvement of energy conversion efficiency and reduction of cost of solar energy generation. Are there any other interesting strategic moves in this connection? Is it really possible to enhance the absorption capacity of solar cells by 1000 times using the concept of nanotechnology? Can we adopt K-A-B-C-D-E-T-F innovation model for fast diffusion of solar technology globally?

Photovoltaic (PV) is the most direct way to convert solar radiation into electricity and is based on the photovoltaic effect, which was first observed by Henri Becquerel in 1839. Solar power electronics is an interesting option in transformation of old and traditional energy system which requires fundamental rethinking and radical redesign of as-is energy policy and technology. The present work has analyzed the technology of solar power through deep analytics in terms of seven 'S' dimensions: scope (S₁), system (S₂), structure (S₃), security (S₄), strategy (S₅), staff-resources (S₆) and skill-style-support (S₇). Effective solar technology diffusion strategy demands a perfect fit, proper coordination and integration among these seven elements. It is clear from scope and SWOT analysis that solar power is a potential option of sustainable energy and business model innovations for the future as compared to other sources of energy. There are some technological constraints such as efficiency and cost of solar cells. Presently, solar power system is at the growth phase of technology life-cycle and it demands an intelligent and rational technology diffusion strategy through the support, commitment and involvement of efficient and creative innovators.

The basic objective of this session is to analyze the technology of renewable energy, more specifically solar energy. This is an interesting cross-fertilization between management science (e.g. business intelligence, technology management,
entrepreneurship) and engineering science (e.g. photonics, power electronics, chemical engineering, electrical engineering, renewable energy and structural engineering). It is basically a modest effort to business model innovation and system implementation; it tries to explore a set of fundamental questions based on rational analytics: What are the intelligent moves in solar technology management? Who are the customers? What do they value? How is it possible to deliver value to the customers at optimal cost? What are the emerging application domains? What is the revenue model? What is the quality policy? What are the corporate social responsibilities? Can the business model generate significant number of new job opportunities in our society? Is the technology ready, feasible and practically implementable? What are the major constraints? What are the critical success factors?

The contribution of this work is that proper diffusion of solar technology at a fast speed requires effective coordination and integration among seven ‘S’ elements of the deep analytics. These moves must be integrated, coordinated and synchronized for effective diffusion of solar power technology. The scope analytics outline a set of interesting business model innovation in solar technology. The system intelligence is explored along five dimensions: smart materials innovation for photonic cell, power electronic circuit intelligence in terms of power amplifier, DC-DC boost converter, microinverter, energy storage, energy efficient load (e.g. LED, computing devices, motors) and topology (e.g. microgrid, standalone or hybrid system). The security intelligence is explored along four dimensions: switchgear, relay and earthing system and maximum power tracking based load manager. The strategic intelligence is associated with good governance, good wishes in public policy, industry analysis, efficient enterprise resource planning, supply chain management and marketing efforts like strategic pricing, promotion, trust in communication, sales and distribution.

The business model requires the support of a functional organization structure enabled with advanced information and communication technology. The structure should have project, power generation, distribution, maintenance, revenue management, HR, SCM and finance cells. The structure is also important for effective knowledge management: creation, storage, sharing and application of knowledge in a transparent, collaborative and innovative way. The business model should be operated by a pool of intelligent, educated, efficient, productive, committed and motivated staffs or HR workforce.

The workforce require different types of skills such as research and development, product design, sales, event management, project management, erection, testing, commissioning and service maintenance. One of the critical success factors is the style or quality of leadership in terms of motivation, commitment, support, coordination and excellent communication. The leaders must be able to share vision and values among all the stakeholders honestly and appropriately in time. It is really challenging to implement the solar power system physically and practically for global energy security. There are different threats from traditional industries: coal, oil and gas, thermal and nuclear power, local bias, power play and politics. It is essential to understand the intelligence of business modeling and system dynamics, fundamental rethinking and radical redesign of global energy trading. The
traditional boundaries of electrical, power and consumer electronics and structural engineering industries must be redefined for future growth in a stable way. The research methodology adopted for this work includes literature review on solar energy, photonics and photovoltaic power electronics and case analysis.

The people of today's world need energy security through emerging renewable technology, new business models and innovative applications. Presently, the global energy consumption is 10 TW per year and 30 TW by 2050. The solar energy plays a significant role in meeting the global energy demand in future. Solar power is useful for the growth of rural, urban, semi-urban and remote zone. The business models based on solar power can create significant number of new job opportunities in photovoltaic micro grid project, erection, installation, testing, commissioning and maintenance of standalone solar power system. Further, there are good opportunities of technology consulting in power electronics and product design and business consulting in global supply chain management. This section explores various types of innovative business models and applications of solar power electronics in terms of solar lighting system, solar power pack, consumer electronics and home appliances, solar charging for laptop and tablets, microgrid for rural electrification and solar water pumps for agriculture with some practical examples of business analytics. This section requires detailed cost benefit analysis based on current technical and commercial data.

**Solar Lighting System** : Solar power system can be used intelligently in various applications such as lighting of homes, religious places, tourist spots, streets, transportation management systems (e.g. airport, rail stations, bus stops, public toilets), educational institutes (e.g. schools, colleges, universities, research labs), healthcare institutes (e.g. public and private hospitals, health clinics, drug shops, pathological lab), office buildings of public and private firms, IT firms, hotels, restaurants, dairy firms, biotechnology firms and food processing units and space science. A typical solar lighting system can illuminate a house of 5 persons lighting 5 lamps for up to 5 hours daily. It can save the cost of 300 litres of Kerosene of about Rs. 10,000. The PV panel converts solar radiation into electrical power; the current is controlled by a charge controller or inverter and charges a battery. The battery supplies power to the connected load while switched on and illuminate. Rooftop solar power system should be used as alternative power supply during power cut due to cyclone or other various types of disaster.

**Solar Power Pack:** A power pack consists of a set of solar panels which convert solar radiation into electrical energy and transmit the power to domestic load or battery bank through a smart inverter. The battery bank stores surplus power when the demand mismatches with the supply. The inverter interacts with PV panel, domestic load, grid and battery intelligently to ensure continuous and regular supply of power. The rating may vary between 100W upto a few KW. A 1 KW power pack can save fuel cost of Rs. 50,000 per annum approximately and can also save energy bill of Rs. 10000 per annum.

**Consumer Electronics and Home Appliances:** Solar cells can be used as economical power supplies with miscellaneous applications such as solar cookers, fans, mobile phones, watches, tablets, laptops, torches, emergency lamps, LED, calculators,
radios, televisions, freezes, air conditioners, water heaters, cars and other different types of home appliances. Solar cells are generally used in *space vehicles*.

**Solar water heater:** A solar water heater consists of a collector, pipes and an insulated tank. The collector is made of glass tubes in evacuated vacuum tube system or metallic tubes in flat plate collector system. It gets heated in sunlight and the heated water reaches the top of a water tank. The relatively colder and denser water descends into the tubes and gets heated through a continuous Thermo-siphon cycling effect. A 100 LPD water heater provides 100 litres of hot water at 65°C and saves Rs. 5000 energy cost annually. The existing design needs a change in terms of mechanism, size and compactness. Solar power enable water purifier is expected to be attached with tube wells in urban and rural zone to ensure the supply of clean purified drinking water.

**Solar Charging for Computing Devices and Mobile Phones:** Solar charging of batteries has recently become very popular for laptops, tablets and mobile phones. The typical voltage output of a solar cell is 0.7 V. A solar panel may have eight cells connected in series producing 5.6 V at most. It can charge a single Li-ion battery used in cell phones to 4.2 V with a buck or step-down charger. It requires a boost step-up charger to charge a multicell Li-on battery of a laptop.

**Solar Water Pumps for Agriculture:** The expert panel have already discussed the application of solar water pumps for agriculture during session 3 [58,59].

**Solar induction cooker** [53-57]: Solar cooker is an interesting emerging application; it may be a direct or indirect application. An indirect application is related to the use of induction cooker or microwave oven enabled with solar panel. Let us exercise SWOT analysis of solar induction cooker and conventional gas cooking oven / gas pipelines. Is it possible to explore the option of solar power enabled induction cookers at mass scale? Solar power enabled induction cooker should be a substitute of costly cooking gas. It is irrational to invest capital on new gas pipeline projects today in the age of induction cooker. Solar cooker uses the solar energy from direct sunlight to heat, cook or pasteurize food or drink. It is relatively inexpensive, reduces fuel cost, having simple technology and large solar cookers can cook for hundreds of people. Solar cookers have various advantages in terms of minimal fuel consumption, reduced danger of accidental fire, health and environmental pollution.

There are many types of solar cookers such as parabolic, solar ovens and panel cookers. The basic principle of solar cooker is based on concentration of sunlight, conversion of light into heat and trapping of heat. A mirrored surface with high reflectivity concentrate sun light on a small cooking area. It can produce high temperature like 65 - 400°C depending on the geometry of the surface. An alternative design of solar cooker concentrates sunlight on a receiver such as a cooking pan. The interaction between solar energy and the receiver material converts light to heat; it is maximized by materials which can conduct and retain heat. The convection of heat can be reduced by isolating the air inside and outside the cooker. Parabolic solar cookers concentrate sunlight to a single point which is focused on the bottom of a pot and can heat the pot quickly to very high temperature. Parabolic troughs are used to concentrate sunlight for solar-energy. Spherical reflectors operate like paraboloidal reflectors and can attain temperatures
above 290°C to cook meat, vegetable, soup, baking of bread and boiling water in minutes.

But, solar cookers are less useful in cloudy weather and near the poles and may take longer time to cook food. The alternative solution is the adoption of induction cooker which can be operated through solar power fed by PV panels. It is essential to design user friendly solar cooker which can be commercialized. The basic principle is to incorporate heating into material by photovoltaic effect and thermal treatment. An efficient solar cooker needs the boosting of only 30W which is generated by a small standalone solar panel of 75W.

**Solar Microgrid for Rural Electrification:** A smart Microgrid is an interesting option of rural electrification [Figure 6.1]. 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.

<figure><img src="image_65.png" /><figcaption>Figure 6.1: Solar microgrid for rural electrification</figcaption></figure>
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. Many rural people suffer from road accidents and snake bites due to lack of adequate street light; the solar power can save them from those dangers in the form of solar torch. The rural students can study in the evening and night effectively using solar lamps. The rural people can save the cost of energy used for home appliances and domestic power supply. They are able to use modern electrical and electronics systems (e.g. home appliances, TV, music system, mobile phones, i-pod, computers, laptops, washing machines, freeze, induction cookers, microwave ovens etc.) through the use of solar power economically. In summer, they can feel comfortable using fans and air-conditioners and in winter, they can use room heaters and geezers. Rural market is a potential option for the growth of consumer electronics and electrical industries.

**PV Panels or Solar Cells Manufacturing:** The present global PV market is growing at about 40% per year and global PV production was about 11 GW in 2009 due to rapid reduction in production cost, technology improvement and market development reflecting the economy, reliability and versatility of solar energy. About 80% of the global PV production is based on c-Si and pc-Si wafer technologies. Major market segments comprise consumer applications, industrial systems, rural electrification in developing countries, microgrid and hybrid systems. The major markets exist in USA, European Union (e.g. Germany), Japan, China and Taiwan. The top ten producers of PV cells and modules are First Solar, Suntech Power, Sharp, Q-cells, Yingly Green Energy, JA Solar, Kyosera, Trina solar, Sunpower and Gintech. In future, a set of PV panels (or solar cells) manufacturing plants should be set up in India through joint ventures. Definitely, the new industrial units will be able to boost the growth of manufacturing industry in India. The budding entrepreneurs must try to explore a set of fundamental questions based on rational analytics: Who are the customers? What do they value? How is it possible to deliver value to the customers at optimal cost? What are the emerging application domains? What is the revenue model? What is the quality policy? What are the corporate social responsibilities? Can the business model generate significant number of new job opportunities? Is the technology ready, feasible and practically implementable? What are the major constraints? What are the critical success factors? What are the business intelligence moves in solar technology management? How to make an effective business plan? What are the critical elements of an intelligent business plan? A good business model consists of four interlocking elements : customer value proposition in terms of target customers, jobs and product and service offerings; profit formula in terms of revenue model, cost structure, margin model and resource velocity; key resources such as people, technology, products, equipments, information, channels, partnerships, alliances and brand and key processes, rules, metrics and norms. A good business plan must have a set of common elements such as executive summary, the mission and vision of a company, organization structure, roles and responsibilities of management team,
industry analysis, market, operation management strategy, marketing plan, financial plan, risks assessment and mitigation strategy. Many ventures fail due to lack of intelligence in defining a good business model and business plan.

The entrepreneurs need the support of business incubator, social network, business cluster and single window system from the ministry of MSME (Micro, Small and Medium enterprises). Entrepreneurial development institutes and MSME training institutes should focus on developing entrepreneurial skills in the domain of solar power electronics. A business incubator can nurture new ventures by providing them good guidance and support during start-up period. The entrepreneurs also need good network of technical experts and business development consultants. A business cluster may gain performance advantage through co-location, business relationships, right infrastructure and right skills. The aspiring entrepreneurs should be able to get all necessary permits and clearances by applying to a single agency of MSME ministry. The ministry of MSME should offer value adding incentive schemes and good mechanisms for access to debt, equity and venture capital, tax breaks, stimulating innovation, access to market and simplification of administrative burden and legal hassles. The policies should be correctly evaluated on regular basis. The rural banks and cooperative banks should launch innovative schemes (e.g. loan guarantee) to fulfill the needs of the budding entrepreneurs for rural electrification through smart Microgrids. Finally, the budding entrepreneurs must have commitment, determination, patience, tolerance of risk and uncertainty, creativity, self-reliance and motivation for successful ventures on solar power electronics.

## 3. SYSTEM

### System Analytics

**Agents**: system analysts, business analysts, scientists, engineers of renewable technology, electrical and electronics technology forum;

**Objects**: sustainable smart cities, smart villages;

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

**System intelligence**: Innovate a set of emerging technologies related to solar power;

* Photonic cell: Nano PV;

* Power electronics: DC-DC boost converter, Inverter;

* Topology: solar microgrid, standalone system, hybrid system;

* Energy efficient load: LED light;

* Battery storage;

Prof. Bruno Platini is giving a presentation on the emerging technology of solar power system; the key areas of his presentation are topology, photonic or solar cell, power electronics, energy storage system and load. The design of solar power system should be smart, compact, cost-effective, reliable, robust, modular, standardized and flexible in terms of service maintenance and focused on high performance and efficiency. There are lot of scopes of improvement of the existing design of solar water heaters, pumps, lighting systems, cookers and other home
appliances in terms of appearance, size, quality, cost and product performance. The customers are very much conscious about product performance, quality of service, cost and values of a standalone solar power system. It is an interesting option to obtain system intelligence through value engineering and value analysis, brainstorming, standardization of product design, excellent quality control practice and efficient supply chain management.

**Topology:** One of the critical factors of system intelligence is topology of solar power system. There are different types of topologies such as standalone system, smart micro grid and hybrid system. Solar power is the modern trend of sustainable energy which requires flexible use of standalone, grid connected and hybrid system. The standalone systems are available in the form of innovative solar power enabled home appliance products such as solar cooker, lighting system, water pump, water heater and charger of computing devices. The basic components of a standalone rooftop system are solar or photovoltaic (PV) panel, inverter (optional for AC load), meter, protection relays and load. Smart Microgrids are intelligent electricity distribution networks that interconnect loads, distributed energy resources and energy storage systems within transparently defined electrical boundaries to act as a single controllable entity that can be grid connected or isolated. The system intelligence of a microgrid is associated with right sensing, communication, measurement and control technologies for effective generation and distribution of energy, self healing, stability analysis, fault analysis and load balancing mechanisms. Microgrid is an interesting and smart option of rural electrification. A hybrid system uses solar rooftop system and electrical grid alternatively according to the availability of power. There are issues of proper system integration, stability and load balancing with hybrid power system. It is logical to build an optimal number of solar thermal power plants and solar parks with medium and large capacities. But, standalone systems are also required in remote zones such as rural, forests, hilly and desert areas.

**Photonic or Solar Cell :** It is interesting to explore the dominant design of solar power system in terms of Nanotechnology based solar cells and solar power electronics. The system intelligence greatly depends on the innovation of smart materials and progress of mono and polycrystalline thin film photovoltaic technologies based on Si, semiconductors and nano PV. The efficiencies of Si and Ga As monocrystalline solar cell are relatively high. Thin film PV can reduce the cost of solar cells. CdTe and Cu (In,Ga)Se₂ thin-film solar cells have efficiencies of 21% and 20.5% respectively. The production cost of CdTe thin-film modules is about $0.76 per peak watt; the same of mono and polycrystalline wafer Si solar is around $1.50 per peak watt (in 2011). Silicon solar cells can be classified into crystalline and thin film cells. The maximum efficiency of a crystalline solar cell is around 25.6%; the thickness may be as high as 400 µm. Reduced reflection loss, better light trapping and improved contact area result better efficiency of crystalline solar cells. Thin film silicon solar cells have reduced thickness of 50 µm; thin films can be deposited on low cost base and the efficiency may vary between 10.5 % and 21.2% . It is required to do similar type of analysis based on real up-to-date data.

The improved optical, chemical and electrical properties of nanomaterials can increase the efficiency of solar cells. Crystalline semiconductor III-V materials,
polymeric materials, and carbon based nanostructures are used for third generation PV cells. Third generation PVs are based on nanostructure which can improve the efficiency of solar cells at relatively low cost. Quantum wells and quantum dots are used in crystalline solar cells to achieve high efficiencies. Quantum dots are nanometer sized crystallite semiconductors. These are artificial atoms improving the energy of the carriers. Nanocrystals increase the surface area of a solar cell and absorb more solar energy. The other options are rectifying antennas using wave property of light and organic solar cells. It is really challenging to improve the efficiency of solar cells and reduce the cost of production through various strategic moves such as carrier multiplication, multi-junction cell structure, hot electron extraction, impurity and intermediate band devices. The carrier multiplication strategy increases the photocurrent generated by a solar cell and improves energy conversion efficiency by creating additional electron-hole pairs in PV devices. A multi-junction structure captures a large fraction of solar spectrum while minimizing thermal losses by stacking cells in the order of band gaps; its efficiency is 37.9%. It is essential to improve the efficiency of the solar cells through innovation of smart materials and explore economical manufacturing technology. A smart analytics needs up-to-date data on efficiency and cost of different types of solar cells.

<figure><img src="image_66.png" /><figcaption>Figure 6.2 : Circuit of PV cell and Electrical Characteristics (I-V curve and MPP)</figcaption></figure>

A Photovoltaic (PV) system converts sunlight into electricity directly. The basic building block of a PV system is PV cell; a set of PV cells are grouped to form panels or arrays. The cells are connected in series to obtain large output voltage. It is possible to obtain large output current by increasing the surface area of the cells or by connecting cells in parallel. A PV cell is basically a semiconductor diode with its p-n junction exposed to sunlight. The rate of generation of electrical carriers
depends on the flux of incident sunlight and the capacity of absorption of the semiconductor. The capacity of absorption depends on the temperature, semiconductor band gap, reflectance of cell surface, intrinsic concentration of carriers of the semiconductor, electronic mobility and recombination rate

Figure 6.2 shows the equivalent circuit of a PV cell. The basic equation describes the current (I) – voltage (V) characteristic of the ideal PV cell is $I = I_{pv} - I_0$ [exp(qV/akT) – 1] where $I_{pv}$ - current generated by the sun light, I - Shockley diode equation; $I_0$ - reverse saturation or leakage current of the diode, q - electron charge (1.60217646 × 10⁻¹⁹ C), k - Boltzmann constant (1.3806503 × 10⁻²³ J/K), T (in Kelvin) - temperature of the p-n junction and a - diode ideality constant. A solar panel can generate its maximum voltage in full sunlight with no load; it is open circuit voltage of the panel. As the load of the solar panel increases, the output voltage decreases nonlinearly. The power output of a PV system depends on various factors such as module temperature, dirt and dust and DC to AC conversion. The output power of a PV system reduces as the module temperature increases. Dirt and dust on the solar module surface blocks some of the sunlight and reduces output (e.g. 7%). Some power is lost through DC to AC conversion in inverters (e.g. 10-12%).

**Nano technology for solar cells :** The basic objective of Nanotechnology is to reduce the cost per solar cell and improve the energy conversion efficiency. The emerging technology is looking for efficient solar cells at reduced cost which can change the economics of energy market. The scope of nanotechnology may be explored in terms of nanoparticles, nanotubes, nanowhiskers as antireflective coating, multi-junction solar cells (MJSC), dye sensitized solar cells (DSSC) and quantum dot solar cells (CdSe QD). The technology of solar cells has been evolving through three generations : first generation having *crystal silicon cells* dominating the market, second generation having *amorphous silicon thin film cells* at reduced cost and third generation adopting *nanotechnology* with a mix of flexible and printable substrates and electronically conducting nanomaterials.

The structure of nanoparticles determines what range of frequencies they can resonate at or accept plasmon energy levels : roughly 575 - 9000 nm or 2.25 - 0 eV for nanoshells, 475 - 1400 nm or 2.6 - 1.0 eV and 600 - 1200 nm or 2.2 - 1.25 eV for nanocubes. In dye-sensitized solar cells, electrons pass through a TiO₂ layer and gather on fluorine-doped SnO₂ of a glass surface. In CdSe QD system, the split and transfer process occurs between a polymer and CdSe dots, which provide tunnels to the electrodes. TiO₂ only collects 5% of the solar spectrum with a bandgap of 3.2 eV. TiO₂ can be doped with N. Antireflection (AR) coating and quantum wells can also improve the energy conversion efficiency. Multi-junction cell allows the absorption of larger range of wavelengths in the solar spectrum through stacking of solar cells of different band gaps in series. A 3-junction solar cell can have about 40.7% efficiency under 240-sun illumination.

**Power Electronics:** The next interesting issue is power electronics. Prof. Platini is trying to focus on DC-DC Boost converter, microinverter and maximum powerpoint tracking algorithm.

**DC-DC Boost Converters :** A DC chopper can be used as a DC converter to step up or step down a fixed dc voltage. The chopper can also be used for switching mode
voltage regulators and for transferring energy between two dc sources. But, harmonics are generated at the input and load side of chopper and the harmonic can be reduced by input and output filter. A chopper can operate on either fixed or variable frequency. A simple step-up boost converter is comprised of dc input voltage source V<sub>S</sub>, boost inductor L, controlled switch S, diode D, filter capacitor C and load resistance R [Figure 6.3, 6.4]. When S is on, the current in the boost inductor increases linearly. The diode D is off at the time. When S is turned off, the energy stored in the inductor is released through diode to RC circuit. The switch is operated with a duty ratio δ = t<sub>on</sub> / (t<sub>on</sub> + t<sub>off</sub>) = t<sub>on</sub> / T; T= 1/f, f : switching frequency; The average value of the output voltage is V<sub>O</sub> = δ.V<sub>S</sub> .V<sub>S</sub>.δ.T = (V<sub>O</sub> – V<sub>S</sub>)(1 – δ)T; DC voltage transfer function M<sub>V</sub> = V<sub>O</sub>/V<sub>S</sub> = 1/ (1-δ); the output voltage is always greater than the input voltage. The boundary value of inductance : L<sub>b</sub> = (1 – δ)<sup>2</sup>δR; C<sub>min</sub> = δ.V<sub>O</sub>/(V<sub>r</sub>R<sub>f</sub>.f); a large filter capacitor is required to limit the output voltage ripple.

<figure><img src="image_67.png" /><figcaption>Figure 6.3 : DC boost converter – simple circuit</figcaption></figure>

Let us perform the strength and weakness analysis of a DC-DC boost converter. Solar panels convert sun irradiation into electrical energy using photovoltaic effect. The output voltage of a solar panel varies based on solar irradiation and temperature; it is not possible to connect sophisticated electrical and electronic load with PV panels for this reason. So, the circuit requires a reliable and efficient DC-DC boost converter with constant step-up voltage. Here, the critical success factors are converter configuration, control mechanism, integration with power utilities, output limitation, efficiency, sensors and complex control algorithm. The cost of converter is approximately 15% of the system cost. But, there are various constraints such as reduction in gain, decreased output voltage, complex control schema, less efficiency and increased cost, variable PV power irradiation and load.

<figure><img src="image_68.png" /></figure>
The possible solution may be high output voltage DC-DC boost converter with MPPT algorithm based on PI controller. A PV module with parallel connection of a set of panels can obtain high current. For a PV panel, power capacity is about 100-300W, MPPT Voltage range is 15-40V, DC-DC boost converter is used for step up conversion of low voltage of a PV panel. The circuit a DC-DC boost converter consists of static switch, diodes, capacitors, inductors and load resistance. The important design parameters are input voltage, inductance, capacitance, load resistance, duty ratio, switching frequency. The other variables are supply voltage load voltage, supply current and load current.

*Maximum Power Point Tracking [MPPT]* : What are the strategic options to obtain maximum available solar power from PV panels?

* DC-DC boost converter with high gain may be connected with an inverter;

* Series / parallel connection of arrays of solar panel;

* Maximum power point tracking algorithm (MPPT) based on PI control;

* The power output of solar systems increases with the use of efficient sun tracking methods such as polar axis and azimuth / elevation types. AI based solar tracking policy may consider various factors such as forecasted weather conditions, energy consumption and complex closed-loop PI control logic.

*Power Amplifier*: The system intelligence of a solar power system is highly correlated to the design and topology of power electronic circuit. The energy conversion efficiency of a photonic solar cell is low (e.g. 20%). Therefore, a solar power system needs the support of a power amplifier. It is a new concept. Let the input power of a power amplifier is p; the output of the amplifier should be P = k.p where k is a constant greater than 1. Recently, Mitsubishi Electric Corporation has developed a prototype gallium nitride high electron mobility transistor amplifier with 100W output power for satellite communications. Generally, voltage and current amplifiers are used in boost converter. A voltage amplifier can raise the voltage generated by solar panels in poor light condition.

Is DC-DC boost converter considered as equivalent to power amplifier? What is boosted V or I? P=VI; If I ↑ and V = constant then P↑; If V ↑, I ↑; then P ↑; but increased I results overheating of electrical and electronic devices. P= Constant; if V ↑then I↓. If V↑ and I = constant then P↑; in case of PV power generation with voltage operation mode, high output voltage DC-DC boost converter maximizes the output of PV panel. Let us consider circuit intelligence of maximum power point tracking schema.

The solar power system requires the support of an intelligent load manager for effective monitoring of voltage (V), frequency (f), current (I), power (P), energy (E) and maximum power point tracking (MPPT). Maximum Power Point Tracking (MPPT) techniques find the voltage V~MPP~ or current I~MPP~ automatically at which a PV cell should operate to obtain maximum power output P~MPP~ under a given temperature and irradiance. There are different MPPT techniques such as hill climbing, Kalman filtering and perturb and observe (P&O) methods. Hill climbing
is related to a perturbation in the duty ratio of the power converter and P&O involves perturbation in the operating voltage of the solar cell. There are differences among various MPPT techniques in terms of complexity, number of sensors, convergence speed, cost, effectiveness, implementation hardware and use of soft computing based microcontrollers (e.g. Fuzzy Logic, Artificial Neural Network).

<figure><img src="image_69.png" /><figcaption>Figure 6.5 : MPPT Control Circuit</figcaption></figure>

Voltage control mode is considered to maximize power generation by PV panel. For example, MPPT may be set at 10V to attain maximum power 500W. The circuit for MPPT consists of two voltage sensor feedback, two P-I controllers, two limiters and a signal compensator. The feedback voltage from PV panel is compared with maximum reference voltage and obtained error is regulated through a P-I controller to obtain the output reference voltage. It is the maximum fixed output voltage reference for the converter. The feedback from DC load voltage is compared with the reference voltage to obtain the error which is then applied to another P-I controller to compensate the error. The signal of P-I controller defines the duty ratio δ for PWM mode. δ is then compared with a ramp-signal to generate pulses for static switch of the converter circuit. The proportional and integral gain of PI controller are fine-tuned to maintain MPPT under variable irradiation and load.

Solar micro-inverter : Inverters convert from DC to AC while rectifiers convert from AC to DC. Many inverters are bi-directional; operate in both inverting and rectifying modes. A standalone PV system operates at 110/240V AC with 50/60 Hz frequency. Inverters operate at 12, 24, 48, 96, 120 or 240V. An inverter for a stand-alone PV system should have sinusoidal output voltage, voltage and frequency within allowable tolerance limits, good voltage regulation and high efficiency at light loads. Inverters use semiconductor devices such as metal oxide semiconductor field effect transistor (MOSFET) and insulated gate bipolar transistors (IGBT). These devices are used in units up to 5 KVA and 96V DC. They have the advantage of low switching losses at higher frequencies. Voltage Source Inverters (VSI) and Current Source Inverters (CSI) are usually used in standalone PV applications. They can be single phase or three phase and use square wave, quasi-square wave, and pulse width modulation techniques.

The topologies, control method (e.g. pulse width modulation [PWM], boundary conduction mode [BCM], discontinuous conduction mode [DCM]) and soft switching methodologies using MOSFETs and IGBTs are the basic elements of circuit intelligence in power electronic inverters and converters. A PV ac module is
called *microinverter* which has benefits in terms of maximum power point tracking efficiency, low manufacturing cost, safe and simple installation procedure. Module integrated converters or microinverters (MICs) are designed to interface a single, low-voltage (e.g. 25-40 V) panel to the ac grid. Such converters provide benefits in terms of ease of installation, system redundancy, and increased energy capture in partially shaded conditions. An energy storage block can be used in a series connected path with the line interface block providing independent control over the capacitor voltage, soft-switching devices and full four quadrant operation with the grid. Several factors must be considered while selecting or designing an intelligent inverter for solar power system such as power conversion efficiency, electrical losses, rated power, duty rating, input voltage, voltage regulation, voltage and current protection, frequency and power factor.

A solar micro-inverter converts DC from a single solar panel to AC. The combined output from several microinverters is fed to the electrical grid. Solar panels produce DC voltage that depends on module design and lighting conditions. For example, panels using 6-inch 60 cells can produce a nominal 30 volts. The panels are connected in series to produce 300 - 600 V DC. The inverter converts this DC voltage into 110V / 230V AC, 50 Hz; microinverters are typically rated between 190 and 220 W and can tune the output of PV panel. Microinverters contrast with conventional string inverters having advantages simplicity in system design, space utilization, cooling and safety. Even small amount of shading, debris or snow lines on any one solar panel or a complete panel failure do not reduce the output of the entire array disproportionately. Each microinverter harvests optimum power through maximum power point tracking. The efficiency of a panel's output is strongly affected by the load. Inverters use MPPT to ensure optimal energy harvest by adjusting the applied load. Microinverters may not need large transformers; large electrolytic capacitors can be replaced by thin-film capacitors.

Module integrated converters or microinverters (MICs) can be used for single-phase grid-tied photovoltaic applications with a topology that places the energy storage block in a series-connected path with the line interface block. It can interface a single low voltage 25-40V PV panel to an AC grid. This design provides various types of benefits such as soft-switching for all semiconductor devices, independent control over capacitor voltage and full four-quadrant operation with the grid, ease of installation, system redundancy, and increased energy capture in partially shaded conditions. A third-port topology places energy storage buffer block in series with the line voltage interface. The topology achieves high efficiencies with its continuous constant power operation.

<figure><img src="image_70.png" /><figcaption>**Figure 6.6 : Microinverter topology**</figcaption></figure>
The circuit consists of four functional blocks of the converter: (1) high-frequency resonant inverter, (2) transformation stage, (3) energy buffer and (4) cycloconverter. Each is connected in series, with a common high frequency resonant current linking them together. This topology allows bidirectional power flow in each block and it is possible to reduce heavy conduction loss through soft switching techniques. Typical rating of a microinverter is 100W, 32V input, 240V output, 95% efficiency. In the classification of inverter topology, the location and the operation of energy storage buffer within the converter are two important parameters. Single stage topologies (e.g. flyback, ac-link) place capacitance in parallel with PV panel. The second option is two complete cascaded conversion stages with energy storage at an intermediate dc bus. Generally electrolytic capacitors are used for dc energy storage due to high energy density, but suffer from long-term failure rates.

Photovoltaic Grid-Tied-Interleaved Flyback Microinverters can achieve high efficiency in wide load range by intelligent control strategies such as Boundary conduction mode (BCM) and discontinuous conduction mode (DCM) [Table 6.1]. In this case loss analysis plays a critical role in estimation of efficiency of flyback microinverters. The dominant losses at heavy load include conduction loss of the power MOSFETs, diodes and transformer; the dominant losses at light load include gate driving loss, turn-off loss of power MOSFETs and transformer core loss.

**Energy Storage System:** The output of solar photovoltaic system varies significantly depending on the time of a day, weather and shading conditions. The system requires a stable energy source and it should be dispatched at request. It demands an efficient energy storage system for solar power system in the form of batteries. There are different options for integrating an energy storage system into a solar PV system such as PV to grid (dc to ac), PV to battery (dc to dc), battery to grid (dc to ac), and battery/PV to grid (dc to ac). An intelligent converter can be used for both single phase and three phase PV battery application. The system is expected to have improved efficiency, reduced weight, volume and cost and minimum number of conversion stages. Li-ion battery can be used for solar energy storage system. It requires a constant current constant voltage charging algorithm. The battery should be charged at a set current level until it reaches its final voltage.

**Load:** The system intelligence is associated with energy efficient loads and mechanisms. Energy consumption is a critical concern since energy dissipation results thermal problems in electrical and electronic devices. Energy is a critical design constraint of electrical and electronic system. There are various strategies of minimizing energy consumption in computing devices such as power down mechanisms and dynamic speed scaling in variable speed processors. The display of computing devices e.g. laptops, tablets) turns off after some period of inactivity. A computing device transitions to a standby or hibernate mode if it remains idle for a while. Intelligent task scheduling can save energy consumption in micro-processor enabled devices. Today, LEDs are widely used as energy efficient lighting or illumination systems. A simple standalone solar power system is easily compatible with light load such as LED, fans, TV and energy efficient motors and computing
devices. In agriculture, the pumps and motors should be efficient to reduce the
consumption of energy. The design and selection of electrical and electronics
equipments should focus on energy efficiency through intelligent algorithms and
operating mechanisms.

The system intelligence depends on good design and sizing of PV cells, power
conditioning system, inverters and converters, battery management system.
Technology management for solar power electronics requires discriminatory, fair
and rational pricing mechanisms, incentive and subsidy policy, economies of scale of
mass production, strategic cost reduction, product life-cycle management, quality
policy and intelligent cost-benefit analysis. Solar power electronics face two critical
constraints which should be improved through innovation, strategic alliance and
intelligent technology management in future : high cost of production and low
efficiency in conversion of sun light into electrical energy. It is essential to explore
intelligent business models and applications of solar power such as rural
electrification, agriculture and solar cooker. It can be a blue ocean space in energy
business.

4. SECURITY

Security Analytics

Security schema :

* Snubber circuit for high dv/dt and di/dt protection

* Fuses for fault protection

* Heat sink for thermal runaway

* Reverse recovery transients

* Supply and load side transients

Emerging technologies:

* Digital relays for voltage, current and frequency protection;

* Earthing system: Earthing rod, lightning arrester;

* Switchgear : Fuse, MCB, Circuit breaker;

* Load manager for maximum power point tracking;

Verification mechanism: audit security intelligence of solar power technology.

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

* multi-party corruption in case of quality problem;

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

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

* malicious attacks: false data injection, shilling: push and pull, denial of service (DoS), fault injection attack;

call threat analytics and assess risks of emerging solar technology :

* what is corrupted or compromised (agents, technology 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?

Output: security intelligence

Prof. Bruno Platini is also presenting the security of solar power system: how to verify the security intelligence of solar power system? It is essential to verify security intelligence of this technological innovation collectively through rational threat analytics at five levels: L1, L2, L3, L4 and L5. The basic building block is an intelligent threat analytics. At level L1, it is required to verify the efficiency of access control in terms of authentication, authorization, correct identification and audit. Only asset of authorized entities or agents are able to access the technology of solar power system through authenticated channels. The technical specifications of solar power system and the demand of the clients and consumers should be correctly identified by the service providers and producers. At level L2, it is essential to evaluate rationality fairness, correctness and transparency of solar power technology management strategy through SWOT analysis, TLC analysis and also technology innovation, adoption and diffusion strategy, At level L3, it is rational to assess the risk of various types of malicious attacks on solar power technology such as fault attack, Denial of Service (DoS), Sybil, false data injection and shilling attacks. The adversaries may execute push and pull attack by other existing power generation and distribution technologies by adopting irrational, incorrect and biased analysis for technology diffusion strategy. An adversary is a malicious agent who attacks solar power system and the associated protocols; the basic objectives are to cause disruption and malfunctioning of a secure system. The security element should be analyzed in terms of the assumptions, goals and capabilities of the adversary. It is also crucial to analyze the adversary model in terms of environment, location, network, resources, access privileges, equipments, devices, actions, results, risks, reasons and motivations of attacks and probable targets. At level L4, it is required to assess the threats of multi-party corruptions on solar power system. The corrupted entities may be trading agents, producers of solar cells and panels, service providers, system administrators and support staff.

Finally, at level L5, it is crucial to audit the solar power system performance in terms of its stability, robustness, reliability, consistency, resiliency, liveness, deadlock freeness, reachability, synchronization and safety. The performance of solar power system and quality of service is expected to be consistent and reliable. Safety indicates that under certain conditions, an event (e.g. electrical faults like overcurrent, overvoltage, short circuit, earth fault, under voltage, over frequency, under frequency) never occurs. Safety is a critical requirement of solar power system whether it is mechanical, electrical, electronics, information technology, civil or instrumentation engineering. 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 solar power system. Another important issue is robustness of a
system. The delivery of the output should be guaranteed and the adversary should not be able to threaten a denial of service attack.

Another important issue is the protection of power electronic circuit used in solar power system. The threat analytics analyzes the power electronics circuit from five different perspectives: snubber circuit for high dv/dt and di/dt protection, fuses for fault protection, thermal runaway by heat sinks, reverse recovery transients, supply and load side transients. Voltage transients are caused in converter circuit due to reverse recovery process of power electronic devices and switching actions in the presence of circuit inductance. Short circuit faults may result excessive current flow in power electronic circuit. Overheating may occur due to losses in semiconductor devices; it must be dissipated sufficiently and effectively for operating the device within upper temperature limit otherwise it may affect the reliability and consistency of power electronic circuit. Fuses are used for overcurrent protection. Power converters may develop short circuit or faults and the resultant fault currents must be cleared quickly. Fast acting fuses are normally used to protect semiconductor devices. As the fault current increases, the fuse opens and clears the fault current in few milliseconds. It is essential to select the location of fuse in the power electronic circuit; generally a fuse is connected in series with each device. A fuse is selected based on the estimation of fault current. A fuse must carry continuously the device rated current; it must be able to withstand voltage after arc extinction; peak arc voltage must be less than peak voltage rating of the device.

Next, let us consider cooling by heat sink. Heat is generated due to on state and switching losses in power electronic devices. The heat must be transferred from the power electronic devices to a cooling medium to maintain junction temperature within specified range. Convection cooling is commonly used in industrial applications. It is rational to consider a set of important design parameters of heat sink such as contact area between device and heat sink, correct mounting pressure of the device on the heat sink, material (e.g. Al), size, and thermal resistance of power devices. Let us consider a power electronic circuit where a voltage source is connected in series with three resistances. $T_j = P_a(R_{jc}+ R_{cs}+R_{sa})$; $T_j$ : junction temperature, $P_a$ :average power loss, $R_{jc}$ : resistance from junction to case; $R_{cs}$ : thermal resistance from case to sink, $R_{sa}$ : resistance from sink to ambient; $T_a$ : Ambient temperature

It is also essential to consider the protection through snubber circuit. It limits di/dt and dv/dt; since transients may occur in power electronic circuit. di/dt = $I_L/t_r$ = $I_{cs}/t_r$; during turn on collector current rises. dv/dt = $V_s / t_f = V_{cc}/t_f$, during turn off, collector emitter voltage must rise in relation to the fall of $I_c$. Snubber circuit protects the power electronic circuit within allowable limit of di/dt and dv/dt. Inductor $L_s$ limits di/dt; it is a series snubber. RC snubber is normally connected across a semi-conductor device to limit dv/dt within maximum allowable rating. There are three types of snubber circuit : polarized (Resistance $R$ limits forward dv/dt); reverse polarized (Resistance limits discharge current of the capacitor) and unpolarized (semiconductor devices are connected in parallel).

Finally, we consider the risk of transients. There are three types of transients - reverse recovery transients, supply side transients and load side transients. In case of supply side transients, a transformer is normally connected to the input side of
converters. Under steady state conditions, an amount of energy is stored in the magnetizing inductance $L_m$ of transformer and switching off the supply produces a transient voltage at the input of the converter. A capacitance C is connected across the secondary of a transformer to limit transient voltage and a resistance is connected in series with C to limit transient voltage oscillation. In case of load side transient voltage, under normal condition, an amount of energy is stored in the supply and leakage inductance of the transformers. When the load is disconnected, transient voltages are produced due to the energy stored in the inductance. In case of reverse recovery transients,

In a circuit, voltage source $V_s$ is connected with an inductance L, capacitance C and resistance R and a diode $D_m$ is connected across C and R. Due to reverse recovery time $t_r$ and recovery current $I_r$, an amount of energy is trapped in the circuit inductance and transient voltage appears across inductance. In addition to $dv/dt$ protection, snubber circuit limits peak transient voltage across inductance. The snubber also limits peak transient voltage across device. The values of snubber circuit R and C are selected so that the circuit is slightly underdamped. The peak reverse voltage depends on damping ratio and current. The energy stored in inductance L is transferred to the snubber capacitance C and is mostly dissipated in snubber resistance. $L \cdot di/dt + R \cdot i + (1/C) \int i dt + v_c(t=0) = V_s$; $V = V_s - L \cdot di/dt$; $i(t=0) = I$; $v_c(t=0)=0$

The intelligence in selection of protective system and load monitoring depends on the complexity of system topology, scalability of operation and cost. A standalone solar power system may be protected by a digital relay having features of over voltage, over current, over frequency, under voltage, under frequency, earth fault and short circuit protection. Additionally, the system should be equipped with switchgear devices like fuse, miniature circuit breaker (MCB), earthling system and simple switches. The power electronic circuit should be protected appropriately. Less harmonic should be injected by inverters to avoid heating, thermal losses and damage of consumer electronics and home appliances. Photovoltaic inverters must be able to withstand overloading for short term to take care of higher starting currents from pumps and refrigerators. The other protection issues are related to over/under voltage and frequency, short circuit, surge protection, low idling and no load losses, low battery voltage disconnect and low audio and radio frequency noise. A solar park should be protected by heavy duty equipments such as air circuit breakers (CB), MCCBs, isolators, lightning arresters (LA), power control panels and sophisticated digital relays. The cost of the protection system and load manager is a function of scalability of operation and complexity of the system configuration.

Prevention and detection are traditional approaches to the security of power system. In the context of expanding threats and risks, real-time system monitoring is essential to predict new threats and automate routine responses and practices. The system should not only rely on traditional prevent-and-detect perimeter defense strategies and rule based security but should adopt adaptive security through intelligent analytics. Advanced analytics is the basic building block of next generation security protection of solar power system which should be able to manage an enormous volume, velocity and variety of data through AI and machine learning techniques. Intelligent analytics are expected to detect anomalous patterns
by comparing with the normal profile and the activities of the users, peer groups
and other entities such as devices, applications and smart networks and trigger
alarms by sensing single or multiple attacks on the system. The security element
must overcome the barriers among security, application development and
operations teams and be integrated deeply into system architecture. Next, it is
essential to develop effective ways to move towards adaptive security architecture.
The mechanism should surfaces anomalies and adjusts individualized security
controls proactively in near real-time to protect the critical data of a system.
Adaptive Security with dynamic data protection is expected to offer many benefits
over traditional security platforms depending on the size complexity of solar power
system – real time monitoring of events, users and network 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.
The emerging solar power technology is expected to adapt to the needs of a system
irrespective of the size of network, nature of operation or exposure of threats. It can
assess the requirements of security with greater accuracy through a set of intelligent
policies and procedures.

Solar power system may face various types of threats from both external and internal environments but it should be vigilant and protected through a set of security policies. 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 network or grid associated with a system 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 solar power system to protect against and adapt to specific threats before the occurrence of known or unknown types of malicious attacks. Let us explain the objectives of adaptive security in depth. New threats are getting originated as an outcome of solar technology innovation and may cause new forms of disruptions with severe impact. The system demands continuous monitoring and remediation; traditional ‘prevent and detect’ and incident response mindsets may be not sufficient to prevent a set of malicious attacks. 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.

# 5. STRUCTURE

## *Structure Analytics*

Agents: system analysts, business analysts;

Moves: Design and configure

* Solar power system architecture

* Smart microgrid

* AC Coupled microgrid

* DC couple microgrid
* AC-DC coupled hybrid microgrids

* AC/DC Sources and loads

* Renewable energy system

* Energy storage system

* Organization structure

* Technology forums

* National level : Government (E-governance model), research organizations;

* International level : strategic alliance among global organizations

Dr. Paolo Maradona is discussing the structure of solar power system in terms of smart microgrid, various topologies such as AC coupled, DC coupled and AC/DC coupled hybrid microgrids, AC/DC sources and loads, renewable energy system (e.g. PV or solar power system), capacity and access oriented energy storage system, stand alone and grid connected operation mode, power management strategies and control schemes for both steady state and transient conditions [refer: appendix]. Smart grids are considered as next generation power systems which interconnect a set of microgrids consisting of Distributed generations (DGs) and renewable energy (RE) resources (e.g. solar, wind, tidal, clean alternative energy sources. Hybrid AC/DC microgrid contains both AC/DC power sources and AC/DC loads. It can be classified into three categories based on how the sources and loads are connected to the system and how AC and DC buses are configured into low and high frequency AC-coupled, DC-coupled and AC-DC-coupled microgrids [38-43]. In AC-coupled hybrid microgrids, DGs and SEs are connected to the common AC bus through their interfacing converters. In DC-coupled hybrid microgrids, DGs and SEs are connected to the common DC bus and an Interfacing Converter (IFC) links DC and AC buses. In AC-DC-coupled hybrid microgrids, DGs and SEs are connected to DC and AC buses and the buses are linked by Interlinking Converter (ILC). The basic objective of energy management is to match demand and supply of power optimizing cost (e.g. fuel, capital and maintenance costs), voltage and frequency regulations and real-time power dispatching among different power sources in microgrids. Microgrid architectures can be classified utility, industrial, commercial and remote type based on applications. In the appendix, table 7.1 compares various structures of microgrids based on a set of evaluation parameters such as topology, structural complexity, operation mode, control schema, power management strategies, cost and benefits.

Hybrid DC- and AC-Coupled microgrids integrate a variety of DER units into existing distribution system. It connects the distributed energy storage systems like batteries and fuel cells to bidirectional AC-DC converters and PV systems connected through DC-DC Boost converters. Microgrids can be classified into single and two stages power conversion systems [Appendix: Figure 6.12]. In single-Stage power conversion systems, a transformer is used for isolation or voltage conversion. It is a very simple structure having high efficiency, small size and weight and reduced cost. Two-Stage Power Conversion is the most common configuration for all electronically coupled DER units and it consists of a DC-DC converter for energy sources with DC output voltage or an AC-DC converter for energy sources with AC
output voltage with a grid-connected DC-AC converter. The converter on the energy source side extract the maximum power from the primary energy source and the grid side converter is controlled to follow grid requirements. Multilevel converter reduces the cost and improves the efficiency of power conversion systems.
A power electronics enabled microgrid consists of a static transfer switch (STS), distributed critical and noncritical loads, multiple DER units with various power electronics interfaces, protection devices and measurement, monitoring, and control units. DC microgrids are used in telecommunication systems, electric vehicles office buildings, commercial facilities, Photovoltaic (PV) and fuel cell system. HFAC Microgrids are generally used in distributed power systems for military and aircraft systems working in single-phase 400 Hz. It is an interesting agenda to explore the use of solar power for DC microgrids application.

Microgrid is the basic building block of the future flexible, reliable and smart power grid with increased penetration of Distributed Energy Resources (DER) such as solar or PV panels. The entire architecture of future electrical power system may consider three possible concept models : Microgrids, ICT driven Active Networks and Internet. Microgrid paradigm interconnects multiple customers to multiple DER units including DG and Distributed Storage (DS) units and form an intentional or non-intentional energetic island in the electrical distribution network. The customers and DER units can operate in parallel with the main grid and supports a smooth transition during abnormal grid conditions. The evolution and rapid development of efficient power electronics technology improves the transient response, Digital Signal Processors (DSP) reduce the processing time and support complex control algorithms and efficient power electronic converters enable cost-effective and flexible control, power management and energy flows efficiently. This structural analysis is the basis of the vision of an efficient solar microgrid or solar park for rural electrification and agricultural application.

# 6. STRATEGY

## Strategy Analytics

Agents: System analysts, business analysts, 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 energy security goals and emerging technologies accordingly.

* Do SWOT analysis: strength, weakness, opportunities and threats of existing technologies related to energy security.

* Fair and rational business model innovation associated with solar power

* 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 emergence phase of 'S' curve.

* Explore technology innovation-adoption-diffusion strategy for solar power system.

* Explore innovation model and dominant design of solar power system.

* 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. Johan Macacini is exploring the strategy for the innovation, adoption and diffusion of solar power technology. This element can be analyzed from different dimensions such as SWOT analysis, technology life-cycle analysis, R&D policy, learning curve, shared vision, communication protocol and knowledge management strategy.

**SWOT Analysis** : The technology of solar power is related to the problem of energy security. The people in today's world are faced with significant challenges in energy sector such as shortage of energy, high cost of power generation and distribution, power distribution loss, environmental pollution, greenhouse gas emission and rural electrification. We must set an efficient national and global energy policy to promote the development of a sustainable energy system which should be viable environmentally, socially and economically based on solar power. The sustainability in energy not only requires the development of renewable energy but also promotes the use of energy efficient system such as LED lighting system which slows down the growth of energy demand and promotes the concept of clean energy that can cut down the usage of fossil fuel significantly.

Let us first do the SWOT analysis on solar power. Renewable energy uses natural energy sources such as sun, wind, water, earth's heat and plants. There are different types of renewable energy such as solar, wind, hydropower, ocean or tidal, geothermal and bio-energy. Clean and green renewable energy technologies turn these fuels into electricity, mechanical, heat and chemical energy. It is basically an initiative of natural resource planning (NRP), a specific case of ERP. The world has limited supply of fossil fuels; there are critical issues of environmental pollution, safety and problem of waste disposal, rapid growth of energy demand. The use of thermal and nuclear power cause global warming which in turn results increase in sea level, flood, drought, heat wave and different types of natural disaster. Air pollution is one of the most dangerous killers worldwide – more than alcohol, sugar and kidney failure. The main cause of air pollution is the burning of fossil fuels. The crisis of global warming is associated with rising seas, catastrophic flood, devastating heat waves, changing heat structure of the atmosphere, unprecedented hurricanes, summer storms and smog. These events clearly show how the traditional old power plant engineering technologies are affecting the climate and weather globally. Renewable energy is plentiful and the technologies are improving rapidly. Solar technologies convert the infinite power of the sun into heat, light and power. Solar electricity or photovoltaic (PV) technology converts sunlight directly into electrical energy. Solar energy is a potential option for sustainable global energy demand. The PV market is growing rapidly.
National energy policy should be redefined since solar energy is an alternative source of energy and a substitute of traditional sources of energy such as thermal, hydel and nuclear power. It is essential to define a clear vision on renewable sources of clean energy such as solar power and set up relevant advanced research institutes to ensure energy security. Sufficient capital has been already invested on thermal, diesel and hydel power. The initial investment on hydel power plant is very high. It is not a good option for hot and dry zone where there is scarcity of water (e.g. drought in Brazil). The tribal workforce should be relieved from hard mining career (e.g. coal) in future. The nuclear power is very expensive due to shortage of fuel (e.g. Uranium). The coastal zones need several solar and wind power plants; it may be a hybrid system. Land may not be a constraint for the adoption of solar power; there is large barren land in rural zone; coastal areas, desert, hills, plateau and forests. The barren land may be utilized for solar park. It is possible to adopt 'million roof program with solar power'. It is possible to make strategic alliance with reputed solar energy vendors and manufacturers of Germany, Japan, USA, China and Israel for fast and efficient implementation of solar power system. It is possible to build many solar parks but it is also required to promote intelligent standalone solar power system. This change in energy policy is not a simple, trivial problem. The people expect more dynamic and active performance from Solar Energy Society and Rural Electrification Corporation Limited. It is required to define an intelligent solar energy policy, imports of PV modules and anti-dumping strategy.

The strong points of solar power are direct conversion of solar radiation into electricity, no mechanical moving parts, no noise, no high temperatures, no pollution. PV modules have a very long life-time, the energy source i.e. the sun is free, ubiquitous, and inexhaustible. PV is a very flexible energy source, its power ranges from microwatts to megawatts. Solar power can boost the growth of various types of industries like photovoltaic cells or modules, power electronics devices (e.g. power amplifiers, converters and inverters), battery and energy storage devices, intelligent load managers with power tracking capabilities, smart micro-grid, steel and aluminum structures. It can reduce the cost of power generation, transmission and distribution and power distribution loss significantly. But, there are few constraints of this technology such as low efficiency of solar cell, maintenance, cleaning of dust, dirt and moisture from solar panels and the negative impact of natural disasters like storm, rainfall and snowfall.

<figure><img src="image_71.png" /><figcaption>Figure 6.7 : Technology life-cycle analysis</figcaption></figure>