13
Applications of Cyber-Physical Systems

Amandeep Kaur1* and Jyotir Moy Chatterjee2

1Department of Computer Engineering, Punjabi University, Patiala, India

2Department of IT, Lord Buddha Education Foundation, Kathmandu, Nepal

Abstract

Cyber-Physical System (CPS) has recently gained intense popularity in the digital world. It has defined a new generation of digital system that mainly focuses on complex interconnectedness and amalgamation of virtual and physical worlds. CPS comprises of highly integrated computation, communication, control, and physical elements. The idea of Industry 4.0 has further surged the demand of CPS as one of the important components. So, in order to understand CPS more precisely, this study presents a detailed survey of the varied CPS application areas with more focus on features/architecture and related work. There are numerous interdisciplinary areas pertaining to CPS but this article is limited to Healthcare, Education, Agriculture, Energy Management, Smart Transportation, Smart Manufacturing and Smart Buildings. The other interesting CPS application areas are Military, Robotics, Decision Making, Process Control, Diagnostics, Aeronautics, and Civil Infrastructure Monitoring.

Keywords: Cyber-physical systems, application areas of cyber-physical systems, CPS applications, Industry 4.0, smart manufacturing, smart buildings, healthcare

13.1 Introduction

Cyber-Physical Systems (CPSs) refer to integration of computational systems with the physical world objects. CPS provides collaboration of physical and virtual environments that requires additional computational power, computing resources, communication channels and storage for monitoring and controlling the physical world entities. CPS represents a wave of advanced digital systems, that exhibit following functionalities:

  1. (1) Establishing advanced connectivity that would confirm real-time acquisition of data from the physical world and interpretation of information by virtual environment.
  2. (2) Constructing a virtual environment with intelligent data management, analytics and computational abilities. The use of CPS aims to increase the implementation of large-scale systems by improving the adaptability, autonomy, efficiency, functionality, reliability, safety, and usability of such systems [13].

At high level of abstraction, CPS has six major building blocks, as shown in Figure 13.1, consisting of physical entities (sensors, actuators, embedded and/or physical systems) and cyber entities that ensure effective communication, control and computation over the cyber world [11, 27].

These, physical and virtual components are deeply coupled to be able to operate on different temporal and spatial dimensions, while exhibiting numerous and unique behavioral methodologies and interact with each other in ways that change with context [16].

Although CPS related research started way back in 2006 [20] when this term was first coined in the National Workshop on Cyber-physical Systems. But, with the commencement of Industry 4.0 i.e. the fourth industrial revolution, CPS has attracted researchers in a different perspective in which CPS has been defined as one of the key technologies of Industry 4.0.

Schematic illustration of building blocks of cyber-physical systems.

Figure 13.1 Building blocks of cyber-physical systems.

13.2 Applications of Cyber-Physical Systems

Cyber-physical systems (CPSs) have attracted a lot of attention these days and considered to be a prominent technology. Many researchers have explored and presented studies related to collaboration of CPS with varied domains. CPS application domain covers varied areas including agriculture, energy, education, healthcare, manufacturing, transportation, military, smart environment, etc. In this section we will discuss some CPS applications with focus on architecture, features and related works.

13.2.1 Healthcare

CPS has been found to be a strong competitor for the technologies used to develop healthcare applications including on-site and off-site patient care. CPS provides ability to monitor patients remotely and give feedback despite of patient’s location. Extensive research is carried out for the medical sensors [30, 51] deployed in healthcare sector. These advanced sensors aid in remote patients’ data collection. This collected data is further sent to a gateway through wireless communication for safe storage and timely availability for the physicians.

Primarily, healthcare CPS, also known as Medical CPS (MCPS), research focuses on intelligent sensor embedded systems for real time patient health observation, telemedicine systems that help in providing medical services remotely and autonomous robots to coordinate with patient’s physical activities [5]. As per author [13], MCPS are extensively being used in hospitals and other medical care services to provide high quality and ceaseless medical aid to patients, but there are numerous challenges being faced from safety view point [35].

In [22], authors have presented a classification of CPS perspectives based on the service being provided with following categories:

  1. 1) Application—CPS in healthcare offers varied applications/services related to deployment in hospitals, assisted living, and elderly care. Depending upon the services being offered by MCPS, the elements of architecture vary. For instance, in hospitals where the medical aid is readily available, the intensive care unit (ICU) and Operation Theater (OT) require more complex and safety-critical CPS architecture. In a controlled environment, a networked closed-loop CPS is suggested that works by involving medical professionals in the working to ensure patient safety and effective workflows. On the contrary, in the assisted living environment, health monitoring without intervening the patient’s normal living routine is desirable. The MCPS for such environments would be very useful in providing support and care both in elderly living and individual homes [22].
  2. 2) Framework—The framework of a CPS is delineated by three major components namely, infrastructure, data requirement and composition. From the infrastructure viewpoint, CPS architecture can be server based or cloud based. Server based infrastructure is considered more appropriate for small architecture whereas cloud-based offers more scalability and accessibility and are more economical [58]. CPS architectures also depend on the type of data to be used. In healthcare, we deal with variety of data ranging from simple textual data like temperature, blood pressure to complex data like MRI images, CT scans, etc. [63] stated that depending on applications, the data gathering techniques and data transmission procedures vary. In addition, CPS architecture also needs to incorporate the computational and communicational requirements of the service.
  3. 3) Sensing ability—The primary functionality of every CPS is sensing. The biomedical sensors collect data from patients as input and fed to controllers for further processing and use. The major elements governing sensing ability of CPS are types of sensors (homogenous and/or heterogeneous), sensing methodology (active or passive) and sensor parameters (single or multiple) to be used during patient data collection.
  4. 4) Data management—Another important perspective for CPS architectures is the management of data collected in the data acquisition phase which involves data integration, storage and processing. Data integration involves collection of data from sensors and its processing to obtain vital information. This process reduces the amount of information to be shared over communicational channels. The data is then stored in the real-time database for its timely availability [17]. Data processing can be performed in distributed manner, in base station or in cloud. The most crucial part of a MCPS is real time processing of data [32].
  5. 5) Computation—Computational processes in MCPS are executed for two major parameters: modeling (identification of necessary methodology to implement) and monitoring (observing patients from anywhere and at any time). Therefore, physicians need to access the required patient data accurately and timely [22].
  6. 6) Communicational channels—In MCPS, the communicational channels involves collection of patient data through sensors and delivering it over the cloud [23]. Recent developments in image processing as mentioned in [4] have presented ways for extracting and compressing images to be shared over communicational channels with higher efficiency.
  7. 7) Security—It is of utmost importance to ensure the security of patient data for any kind of unethical access and theft. So, MCPS architecture must inculcate high security features.
  8. 8) Control—To bring effectiveness in dealing with emergency patients and calling the appropriate medical physician, the Medical CPSs must be aided with control and actuation resulting in appropriate decision making.

13.2.1.1 Related Work

A number of research studies have proposed different CPS architectures in healthcare sector with their respective features and limitations.

[44] delineated an MCPS that facilitates physicians for diagnosing local and remote residents. It is based on cloud computing and facilitates physicians in collection, evaluation and diagnosis patient’s data. The operability of this system is highly dependent on high speed internet connectivity which is quite difficult to be ensured in remote areas.

[46] investigated the technique for an efficient retrieval of the dental images from the databases in real time. Image attributes were used to recover and depict these images. The process includes identification of images and then classification into different teeth categories. The system has been found to be robust and provides accurate results. However, the implementation of this system requires a huge teeth model database.

In [39], authors have developed a system to be implemented in the operating room through integration of information technology and cybernetics. The CPS developed consisted of a robotic nurse that would provide assistance to surgeons during surgeries by passing surgical instruments. In addition, it would also keep a count of surgical instruments used as a personal health record.

To aid physicians in their routine tasks, [3] proposed a system that provides electronic checklist. This system was also built with the feature to interconnection with other devices and software applications. The major features offered by this system consisted of supporting medical staff in intensive care units to prepare medication for patients, data gathering, and other routine activities. Although this system offers multiple advanced features like time and profile based analysis of patients, patient care monitoring, etc., this system is not found yet to be applicable to all medical domains.

The research study in [57] is based on detection of varied falling postures. A particular falling posture is depicted by measuring the variation in numerical values between the body contact on ground and the body on rest at a specific time interval. It also identifies different types of daily activities such as jumping, walking, jogging, sitting, standing, movement on a staircase, etc.

[28] presented a study based on analysis of posture for predicting the recovery period post hip replacement surgery. The proposed system is an interconnection of seven sensors installed at some specific locations near surgery part. System detects the hip position and evaluates the load applied on the affected area by collecting information sent through these sensors. Furthermore, it also raises an alarm to notify the physicians in case of any unfavorable conditions.

The authors in [34] developed a system that collects data from wearable devices in order to monitor the medical profile of the people. The system is meant to capture audio and video signals to initiate early response to accidents.

[60] is a research article based on wireless bio-sensor network system, developed to predict heartbeat rate, pulse rate and oxygen saturation in the patient’s body. The implementation is based on spatial contextual data collected from environmental parameters like temperature, and precipitation. This system also offered an interactive interface for medical professionals to help them monitor important signs from patients.

[40] proposed MCPS for collecting and accessing real time data through sensor networks. The major components of the proposed architecture were medical sensors for data collection, monitoring facility, cloud storage and a healthcare official for regulating security policies.

13.2.2 Education

On one side, where corona lockdown has hit the economy of the world badly but on the other side drastic rise in E-learning has been experienced. The need of Virtual learning Environments have gained popularity during this time of crisis. Furthermore, the collaboration of physical environments and virtual learning environments proposed as an Educational Cyber-Physical Systems (ECPSs) has also attracted researchers.

Based on related studies, it has been observed that an ECPS paradigm must follow a set of mandatory requirements to provide effective communicational channels to help students and faculty interact in a better way. Moreover, administrative, assessment and pedagogical tools for managing learning process effectively as also desirable.

The essential components of an ECPS are:

  • Virtual elements: This is required to enhance student involvement in learning process. Different virtual elements can be images, videos, project based learning, demonstrations, etc.
  • Interfacing: involving students in virtual activities through the physical modules.
  • Physical modules: physical resources for providing interactions among students.
  • Feedback modules: monitoring student progression.
  • Networking capabilities: sharing of data and information among students and faculty [48].

13.2.2.1 Related Works

The idea of collaborating CPSs with Education has gained popularity over the years and various researchers have contributed in this experimentation along with case studies. One of the studies focused on describing the use of Quartz language along with Averest toolset to implement cyber-physical system for educational purposes. The methodology was implemented for a post graduation course and focused on evaluation through practical work assignments given to students [7].

In another study, a smart laboratory was created through a cyber-physical system which included procedures related to habit based control, less audible communications and statistical analysis [36, 37].

The authors in [24] and [15] delineated their ideology related to offering cyber-physical systems as a mandatory course with theory and practical in the curriculum of undergraduate students. The idea is to provide an insight to students about the relevance and need of cyber-physical systems.

Student engagement for evaluation and testing of CPS has also been encouraged by different researchers. In one of the studies, a programming model was developed that encouraged students to implement and test CPS control programs. Students modeled and programmed a CPS application through a web page. As a case study, students applied the proposed model in an embedded system design lab work [45].

13.2.3 Agriculture

Through technologies such as precision agriculture, smart water management, and efficient food circulation, CPS research can enhance gross food productivity and availability, thereby playing a vital role in agricultural development. Sustained monitoring of the environment and its consequences on crops is used in agriculture to attain optimal output. Furthermore, contemporary tools and technologies can integrate information technology and agricultural science to boost crop output in a way that is both economically and environmentally sustainable.

A CPS built and used to agriculture, the Agricultural Cyber-Physics System (ACPS), may collect crucial information on climate, soil, and crops in a high-granularity and timely manner to achieve a more accurate agricultural management system. ACPS may also continually monitor various resources, including as irrigation, humidity, plant health, and so on, using sensors in order to maintain ideal environmental values using actuators and devices.

A typical ACPS system is composed of:

  • Sensors—Sensors are installed physically in different regions across the fields for monitoring environmental variables like temperature, pressure, humidity and so on. Further, data collection occurs and distributed across the network.
  • Network—Data is sent from the receiving node to the control center using network communication equipment.
  • Control center—The data collected by the sensor nodes is evaluated by the remote control center, to determine the directives of target agricultural facility.
  • Farming tasks—Agricultural activities like fertilizing, irrigating, spraying insecticides, and so on are controlled remotely [2].

13.2.3.1 Related Work

In [53], authors shared a cost effective greenhouse observation system for scientific farming by observing different atmospheric properties such as temperature, humidity and illuminance.

Irrigation schedules can be improved based on soil water monitoring. There have been a variety of methodologies used to study geographical variance of irrigation water amount. For this purpose, [1] experimented by installing sensors with in the areas to monitor the amount of irrigation water required. It is observed that electrical conductivity of soil and field elevation parameters can be used to distinguish the field areas as per different levels of water requirements.

Researchers in [55] used soil moisture data derived from sensors put in the field, along with crop reflectance measurements, to calculate wheat yield potential and nitrogen fertilizer rate is required.

Profitability of fruit farming is always a concern for modern agriculture systems. An autonomous infield monitoring system was created by [29] to efficiently collect long-term and current environmental variations in a fruit field, with the goal of improving integrated pest management program. Using WSNs, a remote observatory system was developed to provide precision farming services that can collect large-scale, long-distance and long-term infield data.

Based on multitemporal and multispectral satellite photos [10] provided a procedure for estimating groundwater required for irrigation. The procedure starts by classifying the crop, then this data is entered into the CPS, along with an accurate estimation of the crop’s water needs, and rectified as per farming exercises in the area.

Smart Pest Control system has been developed by [43] for efficient monitoring of rats in the fields to avoid crop loss. Using this approach, one can save a ton of money to be spent on pest control, agricultural waste, and pollution.

On the basis of CPS architecture and design technologies consisting of four levels, namely physical, network, decision and application layer, [47] developed a precision agriculture observatory system to capture the vegetation status of potato crop. In order to boost agricultural output, farmers can use the proposed system to track the evolution of particular metrics of interest and make suitable decisions.

13.2.4 Energy Management

Cyber-Physical Energy Systems (CPESs) are special embedded systems that manage physical and virtual variables such as battery life, power flow, computational process and network limits that constitute basic requirements for the bulk of existing energy systems [65]. Most of the current energy systems are large and distributed to adhere with new challenges and futuristic energy demands. Moreover, these systems should be flexible, efficient, sustainable, reliable, and secure. Because of this, Cyber-Physical Energy Systems (CPESs) have been deemed to be a suitable option for adaptive performance. CPES can achieve this level of performance by incorporating virtual technologies to monitor, communicate and control the growing physical systems in a systematic manner [42].

Listed below are the desirable characteristics of a CPES:

  • Reliability: These systems should not compromise with system failures and environmental changes.
  • Autonomies: Unexpected situations and subsystem breakdowns must be accommodated by CPES’s robustness. It should be self-adapting and self-repairing in the event of a problem, i.e. it should be self-reliant.
  • Integrated: By using network connectivity or embedded real-time systems, CPES should be able to integrate compute and physical energy processes;
  • Networked: In distributed systems, CPES makes use of networks. These internal networks include wired/wireless networks, Wireless LAN, Bluetooth, and other technologies to accommodate variety of devices and services.

Smart Grids (SGs) are emerging as the next-generation electrical power grid, capable of adaptive and optimal power generation, distribution, and consumption. They intend to intelligently integrate the behaviors and actions of all stakeholders in the energy supply chain in order to efficiently deliver sustainable, economic, and secure electric energy, as well as to ensure economical and environmentally sustainable use. The seamless integration and interaction of power network infrastructure as physical systems and information sensing, processing, intelligence, and control as cyber systems is critical to the success of SGs. Furthermore, the emerging new technology platform known as cyber–physical energy systems (CPESs) and cyber–physical power systems (CPSSs) is the perfect solution to address the specific integration and interaction issues in SGs, focusing on effective and efficient interaction and integration of physical and cyber systems. Adopting CPS technologies in SGs will improve their operational efficiency, responsiveness to prosumers, economic viability, and environmental sustainability [64].

13.2.4.1 Related Work

[56] created a cyber-physical power system application that can collect real time power consumption statistics and shared the need of autonomous electric vehicles and charging stations in the smart grid. The energy management framework presented also observed reduction in energy consumption, allowing for more efficient power supply and distribution.

[38] developed a distributed model cyber-physical power systems that are vulnerable to data attacks. They mentioned dynamic state estimators based on a 9-bus power system for optimum control of large scale distributed systems.

[42] presented a cyber-physical smart grid model based on an incremental approach across micro grid. CPS components, as well as cyber and physical networks that indicate linkages, are incorporated into this schematic model. The cyber and physical components of these CPS modules were combined. In the cyber world, each physical component has a virtual counterpart. Microsource (DG) and loads, on the other hand, are present in each microgrid component. Microsources are controlled by a micro source controller, and each load is controlled by a local controller. In the cyber realm, these controllers have a matching component. The communication network is used to communicate between the local controllers and the Micro grid Central Controller. At the physical layer, energy is exchanged. Authors have also recommended future study topics such as de-centralized load management, closed loop voltage control, and small signal stabilization applied to smart grids.

[18] described the innovative INSPIRE co-simulation environment for both power and ICT systems, which is intended for assessing smart grid applications. The study evaluated the substantial influence of ICT scenarios on the performance of CPES applications for identifying a critical power system condition and recovering from the disturbed state by executing suitable countermeasures.

The goal of [50] is to comprehensively describe the interaction models and accompanying solution approaches in current CPPS research. The interactive characteristics of CPPSs are explored, as well as their modeling methods, which are thoroughly evaluated and described from the visual, mechanism, probability, and simulation perspectives. Furthermore, the applicability and features of these models that are appropriate for certain study topics are explored. Various CPSS-related problem-solving techniques are also examined and addressed.

Authors proposed the idea of Energy Internet Cyber-Physical Systems (EI-CPS) in this research study [14]. Different morphological characteristics have been studied, such as dynamic property of multi energy flow, efficient and fast information processing capability, and coupling between energy and information flow, as well as technical challenges encountered in the implementation of EI-CPS.

13.2.5 Smart Transportation

Intelligent transportation aims to provide better transport services to society by enhancing public safety, reducing wait time, better traffic management, avoid congestion of traffic, etc. through sophisticated sensing, communication, computing, and control techniques. Researchers aim to achieve zero traffic death rate through implementation of autonomous vehicles.

Intelligent cars have improved their skills in highly and even completely autonomous driving. Before shifting to completely autonomous driving, it’s crucial to study driving so that an improved vehicle performance and traffic throughput could be achieved.

Smart transportation cyber-physical systems, also known as Cyber-physical vehicle systems (CPVS) or Vehicular cyber-physical systems (VCPS), are made up of the following subsystems:

  • Controller—The cyber world
  • Physical vehicle plant
  • Driver
  • Human Intervention
  • Environment.

The behavior and final performance of the vehicle are determined by these strongly linked components. The co-design process in CPVS enables us to fully explore the system’s potential by optimizing physical architecture and parameters in collaboration with the controller [31]. We must examine the “Human” of an autonomous car in addition to the cyber and physical worlds. In addition, the interaction effects of the vehicle plant, controlling factors and driving styles should be thoroughly studied [41].

The design optimization of a CPVS, by considering process duration, actuator properties, energy consumption, and controller workload, was explored in [8].

The co-design of a typical CPVS utilizing platform-based design approach has been addressed in [41], which comprises of an autonomous vehicle with multiple driving behaviors. The study aimed to identify best design variable values to optimize the performance of system while fulfilling a number of restrictions.

13.2.5.1 Related Work

In the area of transportation engineering, traffic measurement is one of the core functionalities as mentioned in [66]. The study discussed the implementation of road CPS for autonomous traffic data collection by counting the number of vehicles moving across different physical locations.

In addition to general circuitry in a cyber-physical system, CPVS includes wireless and satellite monitoring techniques to handle complicated traffic flows, assure safety, and expand situational awareness. CPS research related to autonomous vehicles also tends to enhance communication between vehicles and infrastructures [33].

Computer vision algorithms based on convolutional neural networks (CNN) are utilized to automate the detection and re-identification of trucks utilizing traffic cameras in order to correlate vehicle weights to bridge responses [26].

[62] investigates the characteristics of cyber-physical vehicle system such as heterogeneity and distributedness, and then proposed a model with extended hybrid automata in CPVS. Finally, an experimental study based on the proposed model has been discussed for vehicle speed control system.

13.2.6 Smart Manufacturing

Because of factors such as mass production, local and international marketing, economic expansion, and so on, smart manufacturing has become an emerging area.

Nowadays, it is widely acknowledged that the primary difficulties in the design of production systems are flexibility, modularity, and reconfigurability. Smart manufacturing involves integration of software and hardware techniques to enhance efficiency in the manufacturing [21]. Another term that is commonly used to describe next-generation smart manufacturing is “smart factory”. CPS is a critical technology for understanding Smart Manufacturing.

One of the results of the Industrie 4.0 initiative is Smart Manufacturing. Industry 4.0 is a strategic project launched by Germany that provides a significant potential for future production [25]. The goal of Industrie 4.0 is to be a trailblazer in future production. The Smart Manufacturing Leadership Coalition (SMLC), a non-profit organization, was founded in the United States comprising of manufacturing suppliers, practitioners, and consortia, as well as technology firms, educational institutions and government labs for achieving future smart manufacturing [52].

This fourth industrial revolution has impacted a wide range of industries, including manufacturing, education, and the military. There are four key elements at the heart of Industry 4.0 that make it the most powerful revolution in history. The Internet of Things (IoT), Internet of Services (IoS), Smart Factory, and Cyber-Physical Systems are the main aspects. According to the authors, Smart Factory is a component of Smart Manufacturing and hence a key feature of Industry 4.0. The architecture of Cyber-Physical Manufacturing Systems (CPMS) proposed by [61] comprises of following modules:

  • System Input—includes customer product requirements, man power, raw materials, funds, etc.
  • Internet of Services—to handle virtual service related activities connectivity, interoperatability, virtualization, cloud computing, web service, etc.
  • Internet of Things—sensors and actuators, etc.
  • Cyber-Physical System—for integrating physical and virtual environments as per defined standards for data exchange, processing, and communications.
  • Internet of Content and Knowledge—for efficient processing of data to be transformed into useful information during manufacturing process.
  • Interconnection—how all components are collaborating among themselves.
  • Factory—place representing physical manufacturing of products where process is controlled by all other components as per interconnection in manufacturing process.
  • Output—manufactured goods, products, services.

13.2.6.1 Related Work

To deal with changes in the industrial environment, the author suggested a paradigm and technology for building a Cyber-Physical Manufacturing System (CPMS). These CPMSs are biologically inspired engineered systems that exhibit the behavior of being self-adjusting and auto-recovering as well as highly responsive to changing manufacturing demands. The architecture of CPMS is mainly based on Internet of Things (IoT) paradigm comprising of wireless and sensor networks [54].

In [12], authors discussed a logical structure of CPS based smart factory integrated with different technologies like Big data, Digital twin, virtualization and cloud computing. The model presented is way similar to the notion of Industry 4.0 that involves the integration of leading edge technologies to provide better manufacturing solutions. It has also been discovered that the combination of these technologies would also result in an engineered system that would exhibit properties like self-adjusting, self-learning, inferring, etc.

[59] introduced Cyber-Physical Product Service System (CPSS) and its application to industry examples. They asserted that by using CPSS industry can easily understand the change in requirements with respect to service, hardware and software and ultimately would offer better adaptability to changing manufacturing demands.

[6] presented a model of automated warehouse based on cyber-physical system to achieve higher flexibility.

13.2.7 Smart Buildings: Smart Cities and Smart Houses

The growing popularity of CPS-based infrastructure makes the concept of smart buildings a reality. The process of making buildings smart mainly consists of installing a distributed CPS to control and automate different basic building processes like heating, cooling, ventilation, lighting, managing security systems, etc. Smart/Intelligent Building is often mentioned in context to the next-generation building. Moreover, these are required to comprehend the notions of smart grid, smart city and smart homes [21].

Smart city refers to a next-generation urban infrastructure that accounts for smart integration of services including Energy distribution, Medical facilities, Security, Transportation, Environmental monitoring, Business management, and Social Interactions.

One of the important constituents of smart cities are smart homes that too require smart integration of CPS elements to control physical and virtual environment within a house.

The ultimate goal of smart infrastructure, comprising of intelligent buildings, smart houses and smart cities, is to provide ease in lives of residents. Smart infrastructure will also contribute in public protection through implementation of smart transport [13].

13.2.7.1 Related Work

[9] identifies the characteristics of some important definitions of smart cities, explains some lessons learned from this in CPS, and explains some basic research agendas. The author proposed smart cities as a new CPS paradigm that includes strict system requirements to ensure personal information protection, flexibility, environmental considerations and processing large amounts of information.

Different smart house models have been presented by researchers including the Gator Tech Smart House, Duke University Smart House, Smart Home by Iowa State University, and National Institute of Information and Communications Technology (NICT) Ubiquitous Home, etc. [19].

[49] discussed a user-friendly model of a smart house equipped with mobile based control center which was designed to facilitate all types of users with ubiquitous access to control complex components of CPS represented by sensors, actuators, process and robots.

[36] presented the notion of applying CPS for laboratory automation. With the technological advancements, the laboratories’ works have also been revolutionized with inclusion of new equipment setups and services consisting of regularizing environmental conditions, analyzing incidents and other abnormalities, etc.

13.3 Conclusion

The Cyber-Physical Systems (CPSs) has gained popularity over the time to be a good fit for academic research and industry oriented tasks. It has emerged as a best design standard present and future digital systems in collaboration with real world. In fact, the notion of Industry 4.0 has increased the popularity of CPS and made researchers think about the implementation of CPS from different dimensions. CPS has been put forth as one of the main components of Industry 4.0.

The idea behind CPS is not merely focused on the integration of physical and cyber world rather additionally, demands for sophisticated data gathering and management, computation and analysis of the information flow between physical and virtual environment. In addition, CPS are expected to exhibit other desirable properties including, adjustability, efficiency, reliability, security and usability.

In this review, the importance of CPS from interdisciplinary view point has been presented. The major building blocks of the CPS have also been mentioned. Although CPS is a wide research area, it spans over varied interdisciplinary applications in different dimensions. Therefore, each application requires the analysis of related system architecture, features, requirements, reasoning competencies and integration with advanced technologies. Although there are numerous application areas pertaining to implementation of CPS but in this study we have focused majorly on Healthcare, Education, Agriculture, Energy Management, Smart Transportation, Smart Manufacturing and Smart Buildings. The elaborative study about these areas includes features, CPS architecture and related works for each application area. The other interesting CPS application areas are Military, Robotics, Decision Making, Process Control, Diagnostics, Aeronautics, Civil Infrastructure Monitoring, etc. After studying few of the CPS application areas, it has been realized that each of them can be further investigated as a separate research area as it included distinct and multiple sub applications.

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