Managing waterpipe systems for smart buildings

A processor may receive an input dataset. The input dataset may include a plurality of waterpipe components and one or more performance factors of the waterpipe system. A processor may generate a digital twin of the waterpipe system using the input dataset. A processor may simulate, using the digital twin, one or more features of the waterpipe system. The simulating may include a forecast having one or more predicted conditions associated with the waterpipe system.

BACKGROUND

The present disclosure relates generally to the field of waterpipe management, and more particularly to identifying conditions within a waterpipe system.

Everyday water use requires the utilization of comprehensive and complex waterpipe systems. These waterpipe systems allow people to carry out everyday activities, ranging from hand washing to agricultural irrigation. As such, proper management of various waterpipe systems is necessary to prevent potential interruption of these activities.

SUMMARY

Embodiments of the present disclosure include a method, computer program product, and system for managing a waterpipe system. A processor may receive an input dataset. The input dataset may include a plurality of waterpipe components and one or more performance factors of the waterpipe system. A processor may generate a digital twin of the waterpipe system using the input dataset. A processor may simulate, using the digital twin, one or more features of the waterpipe system. The simulating may include a forecast having one or more predicted conditions associated with the waterpipe system.

DETAILED DESCRIPTION

Aspects of the present disclosure relate generally to the field of water management and more particularly to using digital twins to manage waterpipe systems. While the present disclosure is not necessarily limited to such applications, various aspects of the disclosure may be appreciated through a discussion of several examples using this context.

The instant features, structures, or characteristics as described throughout this specification may be combined or removed in any suitable manner in one or more embodiments. For example, the usage of the phrases “example embodiments,” “some embodiments,” or other similar language, throughout this specification refers to the fact that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment. Accordingly, appearances of the phrases “example embodiments,” “in some embodiments,” “in other embodiments,” or other similar language, throughout this specification do not necessarily all refer to the same group of embodiments, and the described features, structures, or characteristics may be combined or removed in any suitable manner in one or more embodiments. Further, in the FIGS., any connection between elements can permit one-way and/or two-way communication even if the depicted connection is a one-way or two-way arrow. Also, any device depicted in the drawings can be a different device. For example, if a mobile device is shown sending information, a wired device could also be used to send the information.

Water is an essential resource that is transported and used every day through various waterpipe systems that can range in complexity from a single pipe to an intricate network of piping components. Such waterpipe systems allow for water to be transported directly to one or more particular points of access (e.g., an upstairs shower and kitchen sink). In order to accommodate for this type of water transport, waterpipe systems can utilize a plurality of components including, but not limited, various sized and shaped pipes, valves, pumps, and reservoirs, to ensure water is readily available at each particular access point. While waterpipe systems offer a cornucopia of benefits, a variety of problems still plague these systems.

One such problem includes the degradation of one or more of the plurality of components of the waterpipe system. Degradation can occur in waterpipe systems for a variety of reason, such as wear occurring over time, environmental conditions (e.g., low freezing temperatures), or water performance factors (e.g., high pressure or particular contamination level). Such degradation can result in water escaping the waterpipe system and causing damage to the surrounding environment. Depending on the amount of water escaping or leaking from the waterpipe system the problem can cause structural damage and/or can lead to moisture accumulation. Moisture accumulation, when not immediately addressed, can result in the growth of bacteria and fugus that can cause structural rot or erosion, as well as significant health and safety concerns. In addition, the water escaping (e.g., leaking) from the waterpipe system is lost and cannot be recaptured for use in the system. This loss of water from the waterpipe system can result in a significant increase in water waste and decrease the efficiency of the waterpipe system.

In recent years, water waste has been identified as a key issue resulting from the increased awareness of water pollution and, in some regions of the world, water scarcity. Traditional waterpipe systems can be wasteful. Often water transported to a specific access point is only used for one purpose (e.g., washing produce in a sink) before it is considered wastewater and reenters the waterpipe system via a drain and is disposed of In these traditional systems, the wastewater is removed and combined with other types of wastewater, such as water accumulated after a shower, before being funneled into the sewer system. In these traditional waterpipe systems, because water is only used for one purpose, often the water considered wastewater only has a small concentration or number of contaminants. While these contaminants may preclude the water from being used for some purposes (e.g., human consumption), the water can be repurposed for other uses or activities (e.g., watering a garden). Accordingly, there is a need for a smart waterpipe system that can identify and minimize, not only damage to the waterpipe system and the damage potentially caused the by waterpipe system, but also ensure water is not unnecessarily wasted.

As such, the present disclosure provides embodiments associated with managing and simulating a waterpipe system that reduces water waste, potential damage to the waterpipe system, and to the environment surrounding the waterpipe system. In embodiments, an artificial intelligence enabled digital twin simulation engine is generated to simulate a waterpipe system. A digital twin can simulate a particular waterpipe system and take into consideration various factors and conditions of the waterpipe system including, but not limited to, the water quality, pattern of scaling, rusting, blockages or jams in the valves or pipes, and weakening in one or more of the plurality of waterpipe system components. In addition, the digital twin simulation engine can also simulate how the water might be contaminated at different stages of water flow at a particular water access point, and how the contaminated water can be reused for a different purpose.

Waterpipe management systems, such as those discussed herein, can also be employed for other uses, such as firefighting, agricultural purposes (e.g., basic gardening or crop irrigation), textile industry, breweries (e.g., and other food/drink related industries where untimely identification of contaminants could affect consumer health), and pulp and paper industries. The aforementioned waterpipe systems can have a variety of other properties different from traditional residential waterpipe systems. These properties include, but are not limited to, different types of water hardness, different water pressures (e.g., firefighting waterpipe systems often require high water pressure), and different configurations (e.g., crop irrigation requires waterpipe components to span long distances). Because of these different properties and configurations, each waterpipe system can incur different types of damages. In these waterpipe systems, often where the damage has occurred and remedying the damage is difficult to detect and is often not detected until the waterpipe system fails in some way (e.g., water does not arrive at expected access point). As such, a method of preventing waterpipe system breakdown is needed.

The following disclosure provides various embodiments for a waterpipe management system that can leverage the use of digital twin technology to improve the management of waterpipe systems. In embodiments, an input dataset comprising data associated with the waterpipe system is received by a processor. The input dataset can include information about the plurality of components (e.g., pipes, valves, pumps, etc.) that make up the composition of the waterpipe system and one or more performance factors (environmental factors, piping parameters, water parameters, etc.). In embodiments, a digital twin of the waterpipe system is generated using the input dataset. The digital twin of the waterpipe system can simulate one or more features of the waterpipe system and generate a forecast having one or more predicted conditions associated with the waterpipe system.

A forecast may include, but is not limited to, one or more recommended actions, one or more recommended redirection plans, and in response to identifying one or more predicted conditions, recommending repairs to the waterpipe system, recommended maintenance schedules (e.g., when water usage is traditionally low), operating conditions or performance factors associated with the particular condition, and further recommendations for improving the overall health and longevity of the waterpipe system during various modes of operation or working conditions. Using digital twin technology can address the various other problems associated with traditional waterpipe systems, while also improving space and facility utilization, optimize accounting associated with waterpipe systems, and scale enterprises that utilize waterpipe systems.

Turning now to the figures,FIG.1depicts a computing environment100, in accordance with embodiments of the present disclosure. In embodiments, waterpipe management system101leverages the use of digital twin technology to effectively manage a waterpipe system.FIG.1provides an illustration of only one embodiment and does not imply any limitations with regard to the environments in which different embodiments may be implemented. Many modifications to the depicted environment may be made by those skilled in the art without departing from the scope of the invention as recited by the claims.

Computing environment100can include network102, client device104, and waterpipe management system101(e.g., a system) for managing waterpipe systems. Waterpipe management system101can be implemented as an application running on a user's computing device (e.g., client device104), as a service offered via the cloud, as a web browser plugin, as a smartphone application, or as a codependent application attached to a secondary application (e.g., as an “overlay” or a companion application to a partner application, such as text messaging application).

Network102can be any type or combination of networks. For example, network102can include any combination of personal area network (PAN), local area network (LAN), metropolitan area network (MAN), wide area network (WAN), wireless local area network (WLAN), storage area network (SAN), enterprise private network (EPN), or virtual private network (VPN). Network102can refer to an IP network, and may include one or more wired and/or wireless networks that are capable of receiving and transmitting data, voice, and/or video signals, including multimedia signals that include voice, data, and video information. For example, database106can communicate with various client devices104(e.g. tablets, laptops, smartphones, portable terminals, conferencing device components, client device104, etc.) over the Internet.

In some embodiments, network102can be implemented within a cloud computing environment, or using one or more cloud computing services. Consistent with various embodiments, a cloud computing environment can include a network-based, distributed data processing system that provides one or more cloud computing services. Further, a cloud computing environment can include many computers (e.g., hundreds or thousands of computers or more) disposed within one or more data centers and configured to share resources over network102. Cloud computing is discussed in greater detail in regard toFIGS.3A-4.

Client device104can be a laptop computer, tablet computer, smartphone, smartwatch, or any other computing device that allows for a client/user to interact with and execute the methods and/or techniques described herein. In various embodiments, client device104can provide a client/user with information and/or one or more findings identified by waterpipe management system101via digital twin interface106. Digital twin interface106can provide an interface between client device(s)104and waterpipe management system101.

Digital twin interface106can be a graphical user interface (GUI), a web user interface (WUI) or any other suitable interface for a user to interact with and execute the methods and/or techniques described herein. As described herein, this information can be provided to a client/user in any format. For example, information can be relayed to a client/user via client device104via video, audio, images, and or text (e.g., charts or waterpipe system readings) that is transmitted, communicated, or otherwise provided by waterpipe management system101. Client device104can represent any programmable electronic devices or combination of programmable electronic devices, capable of executing machine readable program instructions and as well as capable of communicating with other computing devices (not shown) within computing environment100via network102. Furthermore, client device104can comprise a plurality of devices, both stationary and portable, that enable a user to be mobile during a conference meeting.

Waterpipe management system101can be a standalone computing system, a server, and/or a virtualized system running on one or more servers within a cloud networking environment capable leveraging digital twin technology to manage a waterpipe system. Waterpipe management system101can include database108, input dataset110, Data collection device(s)112, and digital twin module114. The term “module” may refer to a hardware module, software module, or a module may be a combination of hardware and software resources. Embodiments of hardware-based modules may include self-contained components such as chipsets, specialized circuitry, one or more memory devices and/or persistent storage (seeFIG.4). A software-based module may be part of a program (e.g., programs428,FIG.4), program code or linked to program code containing specifically programmed instructions loaded into a memory device or persistent storage device of one a data processing systems operating as part of the computing environment100. For example, data associated with digital twin module114, depicted inFIG.1, can be loaded into memory or a database, such as database108.

In embodiments, client device104can be a component of waterpipe management system101. In these embodiments, client device104can include all of the components, or fewer than all the components necessary to implement waterpipe management system101. For example, input dataset module110, can be configured on client device104while digital twin module114can be configured on a separate device.

In embodiments, waterpipe management system101can include database108, input dataset module110, data collection device(s)112, and digital twin module114. Waterpipe management system101can be configured to manage any type of waterpipe system that uses pipes and other piping components to direct waterflow (e.g., to a kitchen sink faucet or an outside spicket). These waterpipe systems can include, but are not limited to, any configuration of pipes and piping components used in a single room, a house, apartment building, residential block, industrial use building, town water system, or any combination thereof that can be implemented above or below ground. While in some embodiments, waterpipe systems managed by waterpipe management system101includes water input systems that act as a source of water to a particular access point (e.g., associated piping directing waterflow to a showerhead), in other embodiments, the waterpipe system managed by water management system101also includes the water output systems or drainage system that removes water after it is used (e.g., a shower drain and associated piping directing the waterflow of wastewater). The waterpipe system managed by waterpipe management system101can be a physical waterpipe system that is already built (e.g., already in use in a house or building) or can also be a proposed design (e.g., a blueprint of the waterpipe system).

In embodiments, database108can be configured to store a wide variety of information and different data types, as contemplated herein. While in some embodiments database108is a single database configured to maintain one or more libraries of information and historical repository120, in other embodiments, historical repository120is separately situated from database108. In embodiments, database108can include one or more libraries of data including, but not limited to, water quality standards, piping parameters, piping structures, data associated with water conditions, data associated with environmental conditions, and any other data necessary to manage a waterpipe system, as contemplated herein. Such data can be accessed from database108by waterpipe management system101, or individually by input dataset module110and/or digital twin module114, as needed. Database108may be configured to store data in various formats including, but not limited to audio and video recordings, readings, images, repositories of system data (e.g., client preferences), and/or any other data format type that can be capable of storing relevant waterpipe system data used by waterpipe management system101. In embodiments, database108can reside on a single server, on multiple servers within a cloud computing environment, on client system104and/or on the same physical system or virtualized system as waterpipe management system101.

In embodiments, waterpipe management system101can include historical repository120. In some embodiments, historical repository120can be independently situated from other components in waterpipe management system101, while in other embodiments, historical repository120can be a component of, database108, digital twin module118, input dataset module110, or any combination thereof. In embodiments, waterpipe management system101can configure historical repository120to receive and store information or data analyzed or determined from a particular waterpipe system managed by waterpipe management system101.

In embodiments, waterpipe management system101is configured to receive one or more input datasets via input dataset module110. Input dataset module110can provide waterpipe management system101with information and data (e.g., input dataset) about one or more particular waterpipe systems to be managed by the system. In embodiments, input dataset module110can be configured to receive one or more waterpipe system documents or digital files. In these embodiments, input dataset module110can be configured to convert the documents or digital files into one or more input datasets having plurality of waterpipe components116and/or one or more performance factors118. Input datasets, derived from documents or digital files, can be used to infer how a particular waterpipe system would be configured (e.g., waterpipe components116) and perform (e.g., performance factors118) if the design was implemented in real-life.

In embodiments, plurality of waterpipe components116can include, but is not limited to, pipes, pumps, valves, or any other component that can be used in a waterpipe system. In some embodiments, waterpipe components116can further include how each component is configured and/or data information associated particular waterpipe components. For example, plurality waterpipe components116can include information and data not only associated with a particular piping configuration (e.g., bent pipe is connected to a particular valve), but also data regarding various brands of waterpipe components, possible waterpipe component material, and one or more waterpiping parameters. Waterpiping paraments can include, but is not limited to, crack growth resistance, environmental stress crack resistance, tensile and compressive strength, minimum and maximum pressure limits, pipe diameter, and pipe wall thickness. In some embodiments, input dataset can provide partial information that can be linked to additional data or information stored in database108. For example, input dataset module110could identify a particular brand of pipe from the input dataset, and retrieve relevant data or piping parameters (e.g., safe operational pipe pressure ranges) associated with that particular brand of piping stored in database108.

In embodiments, performance factors118can include one or more factors that influence how the waterpipe system functions and performs when waterpipe system is in use. More particularly, performance factors118can provide information and data about how use of the waterpipe system influences one or more of the plurality of waterpipe components116and can include any factor that affects the operational use (e.g., flow of water) of the waterpipe system. Performance factors118can include, but are not limited to, water velocity, water acidity, temperature, external waterpipe components116conditions (e.g., soil conditions that can affect waterpipe components116), and internal waterpipe components116conditions (e.g., contaminants within one or more waterpipe components116that can affect the conditions of the component).

In embodiments where one or more of the plurality of waterpipe components116are not definitively identified from the documents or digital files (e.g., input dataset) or performance factors118are not provided in either the documents or database108, waterpipe management system101can be configured to determine what the missing waterpipe components116or performance factors118are. In some embodiments, waterpipe management system101can identify that one or more of the plurality of waterpipe components116or one or more performance factors118are missing and send a message to client device104indicating that the information is not available.

In these embodiments, waterpipe management system101can, using various methods contemplated herein: i) request a client/user to input information or data associated with the missing waterpipe component or missing performance factor; ii) make a recommendation on what the one or more missing waterpipe components or performance factor should be (e.g., use machine learning to extrapolate a similar waterpipe component or performance factor, based, at least in part, on the information and data from input dataset module110and database108and/or historical repository120); iii) automatically select the most likely waterpipe component or performance factor that would fulfill the missing waterpipe component or performance factor role; or iv) any combination thereof.

In embodiments, input dataset module110can be configured to receive information and data (e.g., plurality of waterpipe components116and/or performance factors118) regarding a particular waterpipe system and how the waterpipe system performs via one or more data collection devices112. In some embodiments, data collection device(s)112can be connected or coupled to, or in close proximity to, one or more of the plurality of waterpipe components116that make up the waterpipe system (e.g., one or more data collection devices112can be coupled to a pipe, pump, and/or valve). Data collection device(s)112can include, but are not limited to, one or more sensors, IoT (Internet of Things) devices, and recording systems configured to capture performance factors118associated with a particular waterpipe system. In these embodiments, waterpipe management system101can configure one or more data collection devices112to identify one or more of the plurality of waterpipe components116and/or performance factors118of the waterpipe system to provide a real-time data feed.

In embodiments, waterpipe management system101can configure data collection devices112to provide, not only a real-time feed of the status of the waterpipe system, but can also provide data and information (e.g., performance factors118) regarding conditions surrounding one or more of the plurality of waterpipe components116of the waterpipe system (e.g., acidity of soil surrounding a pipe). As discussed herein, performance factors118can include any element/factor that is capable of affecting how the waterpipe system functions. Input dataset module110can be configured to receive information and data collected from data collection device(s) and identify one or more performance factors118that affect a particular waterpipe system in real-time.

These performance factors118can include, but are not limited to: i) actual condition of waterpipe component116, such as pipe weakening, rusting, cracking, leaking, etc.; ii) data readings of one or more waterpipe component116under different conditions (e.g., pipe pressure readings during freezing temps), iii) data readings associated with the condition of the waterpipe system environment, such as temperature, UV exposure, soil composition, etc.; iv) real-time data associated with water conditions and waterflow through the waterpipe system, such as water velocity, water temperature, water acidity, waterpipe system environmental conditions and water contamination types and levels of contamination.

In some embodiments, data collection device(s)112can provide input dataset module110, with sufficient data (e.g., one or more input datasets) to define the plurality of waterpipe components116and performance factors118associated with the waterpipe system of interest. In other embodiments, input dataset module110can configure the data and information collected by one or more data collection device(s)112and combine it with a document or digital file of the waterpipe system (e.g., blueprint of waterpipe system) to define the plurality of waterpipe components116and performance factors118associated with the waterpipe system of interest. In embodiments, digital twin module114can be configured to receive waterpipe components116and performance factors118from input dataset module110with the waterpipe system. In these embodiments, digital twin module114can generate digital twin122and simulate one or more features of a particular waterpipe system to provide a client/user with a forecast126.

While in some embodiments, waterpipe management system101can configure one or more data collection devices112to provide a “snapshot” depicting the state of the waterpipe system at a particular instance, in other embodiments, waterpipe management system101can configure one or more data collection devices112to provide a more comprehensive surveillance of the waterpipe system. In embodiments, waterpipe management system101can configure one or more data collection devices112to: i) constantly survey the waterpipe system and relay the information and data to waterpipe management system101; ii) intermittently survey the waterpipe system (e.g., timed intervals); iii) data collection device(s)112can be configured to relay information only when there is information indicating a significant change in one or more waterpipe components116or performance factors118the waterpipe system; or any combination thereof. Waterpipe management system101can configure one or more data collection devices112to collect and store this observed or historical data in historical repository120. In embodiments, the historical data stored in historical repository120can be used by input dataset module110to define waterpipe configuration and/or by digital twin module114to generate digital twin122and enable waterpipe management system101to simulate digital twin122and generate forecast126using simulation engine124.

In embodiments, waterpipe management system101can use the historical data stored in historical repository120, to produce predicted conditions of one or more features of the waterpipe system. In embodiments, waterpipe management system101can configure the historical data stored in historical repository120to identify one or more observed performance factors in the waterpipe system that can indicate a potential change in one or more of the plurality of waterpipe components116and/or other performance factors118. For example, one or more data collection devices112over a period of time can observe that an increase in water pH (e.g., observed performance factor) at a particular location within the waterpipe system, increases the occurrence of rust (potential change) inside one of the waterpipe components116. The occurrence of rust can then affect other performance factors118, such as the type and level of water contaminants in the waterpipe system. In embodiments, waterpipe management system101can discern, using statistical modeling, deep learning models, machine learning models, or a combination thereof, if and how a particular performance factor118will influence one or more waterpipe components116and other related performance factors118of the waterpipe system (e.g., how the increase in water velocity results in an increase in pressure).

In embodiments, waterpipe management system101can use the aforementioned techniques to identify historical patterns from the historical data collected by one or more data collection devices112and stored in historical repository120. An historical pattern can include, but is not limited to, identifying one or more particular performance factors118observed from one or more data collection devices112that causes a particular condition to one or more waterpipe components116in the waterpipe system, determining the effect of a particular performance factor118on one or more waterpipe components116over a particular period of time, determining the time period associated with the worsening (or improving) condition of the waterpipe components116, and determining how an observed performance factor (e.g., types and/or levels of contaminants in the water) impacts the waterflow through the waterpipe system and water use. Continuing with the above example, waterpipe management system101can use the various techniques contemplated herein (e.g., machine learning) and information stored in historical repository120to identify an historical pattern associated with the effects of an increase in water pH caused to one or more waterpipe components116, such as, how much rust accumulates over a particular time duration that the increased pH is observed in the water, and how the increase in pH and likely rust components in the water affect water use (e.g., considering if the contaminant type and level/amount of contaminant in the water is safe for human consumption).

In embodiments, waterpipe management system101can be configured to manage and observe more than one particular waterpipe system. In such embodiments, historical repository120can be configured to store information and data associated with each waterpipe system. While in some embodiments, historical patterns for a particular waterpipe system are determined from the historical data observed/collected only from that particular waterpipe system, in other embodiments, waterpipe management system101can configure historical repository120to identify historical patterns associated with historical data observed/collected from all waterpipe systems managed by waterpipe management system101. For example, in these embodiments, if waterpipe management system101manages waterpipe system A and waterpipe system B, a historical pattern identified from the historical data associated with waterpipe system A can be used by digital twin module114to simulate waterpipe system B if waterpipe system B has similar waterpipe components116and performance factors118as those found in waterpipe system A, even if each waterpipe system A and waterpipe system B is configured differently for different purposes. For example, if waterpipe system A is a waterpipe system for a house and waterpipe system B is a waterpipe system for an industrial building, but both waterpipe systems have a particular type of pipe then if a historical pattern is identified associated with the historical data collected from waterpipe system A and the particular pipe, then that particular historical pattern can be used by digital twin module114to simulate the digital twin of waterpipe system B.

In embodiments, waterpipe management system101can be configured to generate a digital twin122of a particular waterpipe system using digital twin module114. Digital twin module114can further include simulation engine124. In embodiments, digital twin module114can be configured to receive one or more input datasets form input dataset module110associated with the particular waterpipe of interest to generate one or more digital twins122. While commonly known in the art, digital twins, such as digital twin122, are generated using various artificial intelligence techniques to create a digital representation that mimics the structure and performance of a particular waterpipe system of interest. Using digital twin122of a particular waterpipe system, one or more features of the waterpipe system can be simulated by simulation engine124.

In embodiments, waterpipe management system101can provide digital twin services via digital twin module114to clients/users connecting and assessing digital twin module114via client device104. In these embodiments, the digital twin services and/or access may be provided to owners, purchasers, licensees, manufacturers, sellers, licensors, and other authorized individuals (collectively referred to herein as “client/users”) of the digital twins being accessed. Embodiments of waterpipe management system101may execute program code of digital twin module114, including, but not limited to, i) retrieving and creating digital twin122models; ii) aggregating, organizing, and storing data generated by data collection device(s)112(e.g., sensor devices, IoT devices, and or recording systems) associated with the waterpipe system of interest; and iii) monitoring changes in the operating conditions of the waterpipe system, including operation and changes associated with of plurality of waterpipe components116(e.g., pipes, valves, pumps etc.) and performance factors118of the waterpipe system of interest as reflected by the digital twin.

In embodiments, waterpipe management system101can configure digital twin module114to simulate digital twin122using simulation engine124. In these embodiments, simulation engine124can simulate one or more features of the waterpipe system (i.e., digital twin of the waterpipe system) to generate a forecast. In these embodiments, one or more features can refer to any element of the waterpipe system that is of interest to a client/user. Waterpipe management system101can determine how one or more features (e.g., particular waterpipe components116and/or particular performance factors118) of a waterpipe system are influenced when a particular stimuli or change is applied to a waterpipe system by applying a simulation (e.g., via simulation engine124) of the stimuli to the digital twin122of the waterpipe system. Examples of simulated features include, but are not limited to, how one or more features (e.g., waterpipe components116and performance factors118) system performs at particular temperatures, how the waterpipe system performs over a particular time duration, if some portion the water contained within the waterpipe system has contaminants, what the contaminants in the waterpipe system are, and if the type and/or amount of water contaminants limit the use of that particular portion of water.

In embodiments, simulation engine124can be configured to receive historical data and historical patterns stored in historical repository120to generate forecast126having one or more predicted conditions128and/or redirection plans130. Forecast126can have reports associated with simulation results to clients/users that can include, but are not limited to, recommendations and/or proposed actions to the clients/users, as well as predicated conditions128and redirection plans130. One or more predicted conditions128can include, but are not limited to, predicting operating conditions of the waterpipe system, such as how waterpipe system performance factors116and/or one or more waterpipe components (e.g., condition of a pipe) are operating over time and into a future predicted timeframe, water conditions (e.g., type and amount of water contaminants), or any combination thereof.

In some embodiments, one or more one or more predicted conditions can also include, one or more recommended actions (e.g., to be automatically relayed to a user), repairs to the waterpipe system, recommended maintenance schedules (e.g., based on times of low water use), operating conditions or performance factors118associated with the particular simulation, other preventative measures for prolonging or maximizing the lifespan the waterpipe components116during various modes of operation or working conditions (e.g., winter conditions and summer conditions). These embodiments can optimize the use of water and one or more waterpipe components116while also minimizing the occurrence of waterpipe system breakdowns caused by the deterioration of the waterpipe system. One or more individual functions or features of the digital twin module114may be implemented by one or more subprocesses or sub-modules of the digital twin module114. For example, in some embodiments, the exemplary embodiment of the digital twin module114depicted inFIG.1, digital twin module114can include simulation engine124, while in other embodiments digital twin module114can be configured to include, input dataset module110, historical repository120, and/or simulation engine124.

In embodiments, forecast126can include one or more predicted conditions and/or redirection plans associated with any feature of the particular waterpipe system of interest. In some embodiments, forecast126via simulation engine124can provide one or more predicted conditions and a redirection plan130associated with ameliorating the one or more predicted conditions128. In embodiments, forecast126may further provide a client/user with a description of parameters considered by simulation engine124while simulating the digital twin122of the waterpipe system to produce forecast126. A client/user may review each of the forecasts comprising one or more predicted conditions128and/or redirection plans130and select one or more actions (e.g., schedule maintenance) associated with the one or more predicted conditions128to apply to the waterpipe system.

In embodiments, forecast126can further include one or more accuracy indicators, determined by digital twin module114, indicating the accuracy of forecast126(e.g., using calculation of percent error). In some embodiments, while a high accuracy indicator can imply that some or all of the data used by digital twin module114to generate the one or more digital twins122and simulate the one or more forecast126is known or well understood, a low accuracy indicator can imply that some portion of relevant data associated with the waterpipe system of interest is omitted. In these embodiments relevant data can include, but is not limited to, any data associated with input dataset module110, database108, historical repository120, data collection device(s)112, or digital twin module114, that is used to define the waterpipe system of interest. For example, relevant data could refer to specific piping parameters (e.g., safe pressure ranges) for a particular pipe (e.g., one or more waterpipe components116) used in a waterpipe system. In this example, the pipe type could be identified as part of an input dataset associated with input dataset module110, but the relevant data associated with the specific piping parameter (e.g., safe pressure ranges associated with the particular pipe) could be missing from the input dataset.

Relevant data can be omitted by digital twin module114for a variety of reasons including, but not limited to, determining that the relevant data is missing or unavailable within waterpipe management system101and/or determining the relevant data collected (e.g., from a broken data collection device112) is, more likely than not, inaccurate. For example, one or more data collection devices112could be faulty (e.g., damaged by the environment) and provide waterpipe management system101with incorrect information. In these embodiments, waterpipe management system101may independently determine or receive an indication (e.g., via message from a data collection device112having a built-in self-test) that one or more of data collection devices112is defective and the data, if any data is received, should be disregarded or omitted. In other embodiments, waterpipe management system101can receive a data reading from one or more data collection devices112and determine that the data is inaccurate by comparing the data reading to the other data readings received by neighboring data collection devices112or by comparing the data reading to data readings collected and stored in historical repository120. In these embodiments, waterpipe management system101can use techniques contemplated herein (e.g., machine learning) to identify whether the data reading is likely inaccurate and should be omitted or if the data reading is indicative of a particular condition of one or more of the plurality of waterpipe components116or change in one or more performance factors118.

In embodiments, where relevant data is omitted from digital twin module114with the waterpipe system of interest, waterpipe management system101can utilize information from various libraries housed within database108, historical repository120, and one or more data collection device(s)112(e.g., a neighboring data collection device112proximate to the faulty data collection device112) to fill in the missing data. In embodiments, where some portion of the data necessary to generate one or more digital twins122and/or to perform either the simulation via simulation engine124is omitted, waterpipe management system101can configure digital twin module114to make intelligent extrapolations based on the data available to make assumptions on the data missing. Depending on the data used to make the intelligent extrapolations, digital twin module114can assign a reliability score to the data used.

For example, data associated with a particular waterpipe system stored historical repository120could have a high reliability score when used to fill in omitted data/information needed to generate/simulate digital twin122, while data from database108that could generically apply to many different waterpipe systems could have a lower reliability score. In embodiments, the various reliability scores used by digital twin module114can be accumulated to generate the one or more accuracy indicators. As discussed herein, the accuracy indicators can provide a confidence level to a client/user regarding how accurate the forecast126is and if the one or more predicted conditions128provided are more likely than not to occur in the actual waterpipe system101. In embodiments where forecast126is based on historical repository120(e.g., and the data collected from the waterpipe system via data collection devices112), as more data is collected over time digital twin module114and more particularly, simulation engine124can generate more accurate digital twins122and forecasts126as a result of having more data available associated with the particular waterpipe system.

In some embodiments, simulating a feature of digital twin122of a particular waterpipe system can include determining whether a portion of water within the waterpipe system is contaminated water. In traditional waterpipe systems, water is transported to a particular access point (e.g., a sink faucet) where it is usually given one use (e.g., rinse vegetables) before it is removed from the area via a removal point (e.g., sink drain) to the sewer system. In embodiments, waterpipe management system101can configure data from historical repository120, data collection device(s)112and determine using, digital twin module114if the water used at a particular access point can be used for a secondary purpose (e.g., watering a garden) once the used water enters the removal point (but before the used water enters the sewer system). Waterpipe management system101can use information received from one or more data collection devices112to identify the origin of the water, analyze the type and number of contaminates (e.g., dirt, bacteria, and/or various chemicals) in the portion of water and analyze the concentrations of each of the one or more contaminates. In embodiments, waterpipe management system101can configure digital twin module to use the contaminant information received from one or more data collection devices112and historical repository120to determine whether the portion of water has one or more contaminates above a contamination threshold.

In embodiments, a contamination threshold can be exceeded in a variety of ways. When a contamination threshold is exceeded the portion of water is designated as wastewater and cannot be repurposed within the waterpipe system. In some embodiments, water can be considered to exceed a contamination threshold depending on the type of contaminants and the concentration of contaminants in the portion of water. For example, if a benign contaminant (e.g., rust particulates) having a very low concentration were to be analyzed within the portion of water, this water could likely be reused for a variety of purposes (e.g., washing dishes, watering the garden, etc.). Alternatively, if this same benign contaminant was found at a very high concentration within the portion of water, this could reduce the number of purposes (e.g., to only watering the garden), or if there are no available purposes (e.g., the concentration is too high), the contamination threshold would be exceeded. In other embodiments, a contaminant can be very toxic and even at low concentrations, if found within the portion of water analyzed by waterpipe management system101, can exceed the contamination threshold.

As discussed herein, waterpipe systems can be configured in a variety of ways. As a result, depending on the technology associated with a waterpipe system, such as “smart” waterpipe systems, a contamination threshold can be higher than that of a more traditional waterpipe system. A “smart” waterpipe system can have a higher contamination threshold because a such systems can have more technology associated with repurposing the portion of water that is contaminated. For example, a waterpipe system could have various filters that remove chemicals or particulates, or chemical treatments that allow water to be, at least in part, “cleaned.” These cleaning processes could allow the previously contaminated water to be reused within the waterpipe system without having to direct the water to the sewer system. Waterpipe systems that do not have these cleaning processes would likely have a lower contamination threshold.

In embodiments, depending on the contamination level and whether a contamination threshold has been exceeded, waterpipe management system101can configure digital twin module114to generate a forecast126having redirection plan130. Redirection plan130can include a recommendation on how the portion of water should be directed through the waterpipe system. In some embodiments, waterpipe management system101can determine that the portion of water is not contaminated. In these embodiments, forecast126can include a redirection plan130that recommends redirecting the portion of water to an uncontaminated portion of the waterpipe system for reuse. If no contaminants are identified within the portion of water analyzed, then the water can be used for any use (e.g., human consumption). Because some water uses require a higher quality standard (e.g., having few contaminants), such water for human consumption, in some embodiments, redirection plan130may include recommendations to place the uncontaminated water within a special reservoir to be sued for those purposes requiring a higher quality standard. It is noted that in various embodiments, a structure (e.g., house, building) could incorporate sensors (e.g., flaps, drains, etc.) and be in communication with the water management system101, which could then automatically adjust settings for the piping system and then determine/identify when to divert specific waste water (e.g., with a low bacteria count, greywater, etc.) to another location (e.g., a garden, the reservoir, etc.).

In embodiments, waterpipe management system101can determine the portion of water does not have one or more contaminates above a contamination threshold further (e.g., the one or more contaminates are below the contamination threshold). In these embodiments, waterpipe management system101can determine (e.g., via data collection112, digital twin module114, and/or historical repository120) that neither the type nor concentration of the contaminant results in the contamination threshold being exceeded. In embodiments, waterpipe management system101can also determine how the contaminated portion of water can be reused. In these embodiments, digital twin module114can generate forecast126with redirection plan130.

In these embodiments, redirection plan130can include a recommendation of how the water could be redirected through the waterpipe system for reuse. In some embodiments, redirection plan130can also provide recommendations of additional technology add-ons that can be incorporated into the waterpipe system that would aid in “cleaning” the water. In these embodiments, redirection plan130can consider the types and concentrations of contaminants and suggest a corresponding technology that could increasing the number of potential purposes the contaminated water could be used for. In some embodiments, redirection plan130also considers water scarcity levels when making a recommendation. For example, in situations where there is a significant lack of water available for human consumption, redirection plan130can recommend specific technology waterpipe system add-ons that will “clean” the water of contaminants so that the water can be used for this purpose.

In embodiments where waterpipe management system101has determined the portion of water has one or more contaminates or concentration of contaminates above a contamination threshold, digital twin module can generate forecast126providing that the portion water cannot be repurposed. In some embodiments, forecast126can also recommend redirection plan130. In embodiments where the type and/or concentration of contaminants in a portion of water exceeds the contamination threshold, the redirection plan130can recommend directing the water to the sewer system. In some embodiments, waterpipe management system can determine that these contaminants can impact the condition of the waterpipe system and/or should not be released into the sewer system.

For example, if there is a significant concentration of chemical waste a portion of water, releasing this waste could damage the waterpipe system or sewer system and could result in polluting the sewer system. In these embodiments, redirection plan130can recommend that the contaminated portion of water is released into a special waste reservoir for the type of waste. This waste can then be removed by the client/user or by a contracting waste removal company. In these embodiments, waterpipe management system101can be configured to automatically send out a notification to a client/user or in some situations send out a request to the waste removal company when the contaminated water should be removed from the special waste reservoir.

In embodiments, the forecast126generated by digital twin module114and configured by waterpipe management system101can recommend a new piping design to mitigate the one or more predicted conditions128associated with the waterpipe system. In these embodiments, digital twin module114, input dataset module110, data collection devices112, and historical repository120can be configured to simulate the generated digital twin122to produce forecast126with one or more predicted conditions128and redirection plan130. In these embodiments, forecast126can identify a condition of the one or more plurality of waterpipe components116and/or performance factors that is affecting the waterpipe system. Simulation engine124can generate a redirection plan130which can include recommendations on how the waterpipe system can be altered to prevent the one or more predicted conditions from occurring, and/or how the waterpipe system design/configuration can be improved upon to reduce water waste and potential waterpipe system failures.

Referring now toFIG.2, a flowchart illustrating an example method200for management a waterpipe system, in accordance with embodiments of the present disclosure. In some embodiments, the method200may be performed by waterpipe management system101, as referenced inFIG.1.

In some embodiments, the method200begins at operation202where the processor receives an input dataset having a plurality of waterpipe components and performance factors. The method200proceeds to operation204where the processor generates a digital twin of the waterpipe system of interest using, at least in part, the input dataset. The method200proceeds to operation206where the processor simulates, using the digital twin, one or more features of the waterpipe system. In embodiments the simulation can include a forecast having one or more predicted conditions associated with the waterpipe system. In some embodiments, as depicted, after operation206the method200may end.

Characteristics are as follows:

Resource pooling: the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of portion independence in that the consumer generally has no control or knowledge over the exact portion of the provided resources but may be able to specify portion at a higher level of abstraction (e.g., country, state, or datacenter).

Service Models are as follows:

Deployment Models are as follows:

Referring now toFIG.3A, illustrative cloud computing environment310is depicted. As shown, cloud computing environment310includes one or more cloud computing nodes300with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone300A, desktop computer300B, laptop computer300C, and/or automobile computer system300N may communicate. Nodes300may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds as described hereinabove, or a combination thereof. This allows cloud computing environment310to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices300A-N shown inFIG.3Aare intended to be illustrative only and that computing nodes300and cloud computing300and cloud computing environment310can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser).

Referring now toFIG.3B, a set of functional abstraction layers provided by cloud computing environment310(FIG.3A) is shown. It should be understood in advance that the components, layers, and functions shown inFIG.3Bare intended to be illustrative only and embodiments of the disclosure are not limited thereto. As depicted below, the following layers and corresponding functions are provided.

Hardware and software layer315includes hardware and software components. Examples of hardware components include: mainframes302; RISC (Reduced Instruction Set Computer) architecture based servers304; servers306; blade servers308; storage devices311; and networks and networking components312. In some embodiments, software components include network application server software314and database software316.

Virtualization layer320provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers322; virtual storage324; virtual networks326, including virtual private networks; virtual applications and operating systems328; and virtual clients330.

Workloads layer360provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation362; software development and lifecycle management364; virtual classroom education delivery366; data analytics processing368; transaction processing370; and waterpipe system managing372.

FIG.4, illustrated is a high-level block diagram of an example computer system401that may be used in implementing one or more of the methods, tools, and modules, and any related functions, described herein (e.g., using one or more processor circuits or computer processors of the computer), in accordance with embodiments of the present invention. In some embodiments, the major components of the computer system401may comprise one or more Processor402, a memory subsystem404, a terminal interface412, a storage interface416, an I/O (Input/Output) device interface414, and a network interface418, all of which may be communicatively coupled, directly or indirectly, for inter-component communication via a memory bus403, an I/O bus408, and an I/O bus interface unit410.

The computer system401may contain one or more general-purpose programmable central processing units (CPUs)402A,402B,402C, and402D, herein generically referred to as the CPU402. In some embodiments, the computer system401may contain multiple processors typical of a relatively large system; however, in other embodiments the computer system401may alternatively be a single CPU system. Each CPU402may execute instructions stored in the memory subsystem404and may include one or more levels of on-board cache.

One or more programs/utilities428, each having at least one set of program modules430may be stored in memory404. The programs/utilities428may include a hypervisor (also referred to as a virtual machine monitor), one or more operating systems, one or more application programs, other program modules, and program data. Each of the operating systems, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment. Programs428and/or program modules430generally perform the functions or methodologies of various embodiments.

Although the memory bus403is shown inFIG.4as a single bus structure providing a direct communication path among the CPUs402, the memory subsystem404, and the I/O bus interface410, the memory bus403may, in some embodiments, include multiple different buses or communication paths, which may be arranged in any of various forms, such as point-to-point links in hierarchical, star or web configurations, multiple hierarchical buses, parallel and redundant paths, or any other appropriate type of configuration. Furthermore, while the I/O bus interface410and the I/O bus408are shown as single respective units, the computer system401may, in some embodiments, contain multiple I/O bus interface units410, multiple I/O buses408, or both. Further, while multiple I/O interface units are shown, which separate the I/O bus408from various communications paths running to the various I/O devices, in other embodiments some or all of the I/O devices may be connected directly to one or more system I/O buses.

It is noted thatFIG.4is intended to depict the representative major components of an exemplary computer system401. In some embodiments, however, individual components may have greater or lesser complexity than as represented inFIG.4, components other than or in addition to those shown inFIG.4may be present, and the number, type, and configuration of such components may vary.