Editorial of Cyber-Physical Social Systems and Smart Environments

Cisco defines the internet of everything (IoE) as the networked connection of people, processes, data, and things [1]. This goes beyond the concept of the Internet of Things (IoT) of connected devices alone transforming the way people live their lives. It is through this combination of people, processes, data, and things that the future of many fields in computing (such as smart cities) can be realized. Smart environments are physical worlds interwoven with sensors, actuators, displays, and computational elements, embedded seamlessly into everyday objects and connected through a continuous network [2]. A smart city/environment, by definition, needs a modern technological backbone but also relies on the natural resources of its inhabitants. The intersection of people, processes, and things is the area explored in this research. Things and people are combining to enable smart environments to become smarter, and smarter here is defined as optimizing/improving the environment's use of resources or the occupant's comfort. In parallel to research into the IoE, there is also a history of research into embedded systems, and this has evolved into cyber-physical systems (CPSs) and now cyber-physical social systems (CPSSs). The main difference between CPSs and IoT systems lies in the fact that IoT systems are aimed at interconnecting all the things in the physical world, while CPSs sense the physical world but are normally closed-loop systems [3].

Cyber-physical systems comprise of physical systems and their corresponding cyber systems that are tightly integrated at all levels and scales. Cyber-physical systems offer opportunities for improving efficiency, monitoring, controllability, and reliability of constructed facilities. These constructed facilities systems are used and maintained by human beings in the social and natural environments. To fully realize the benefits of cyber-physical systems, the social aspect needs to be considered. Necessary mechanisms need to be put in place for accommodating the “human in the loop.” The control of heating, ventilation and air-conditioning systems in a sharable space is a key example, as individual occupants seek to achieve what they perceive to be their own comfort level, which is often not aligned with what benefits the entire occupants at a given point in time. Addressing facility management from the cyber, physical and social perspectives constitute the cyber-physical-social system, a complex system, and challengeable problems to control and manage it under traditional methods. This chapter presents a framework for the application of cyber-physical social systems in facility management. It describes the role of social systems in the facility management process and advocates the inclusion of social systems in the current and future cyber-physical facility management systems. The chapter describes deployment scenarios to show the potential benefits of cyber-physical social systems in facility management. The authors also present challenges to achieving cyber-physical social systems in facility management.

Cyber-physical systems (CPSs) are related to the integration of computing and communication capabilities into physical systems. An example of CPSs is the smart city model, which is growing around the prototype of an urban (physical) environment with a new generation of innovative services for transportation, energy distribution, healthcare, environmental monitoring, business, emergency response, and social activities developed in its digital twins. Smart cities are also an example of how CPSs must include the presence of people, which can't be neglected in the loop of producing, collecting and consuming data, information and services.

Cyber physical systems integrate actuators or sensors with networking technologies. Latest innovations in the area lead to cyber social systems or cyber physical social systems. Industry 4.0 amalgamates all major technologies including internet of things, big data, cloud computing, and smart systems under CPS. Cyber physical systems comprise of physical layer devices connected to the internet. It has vast applications in the areas like manufacturing, healthcare, energy, automation, robotics, smart building, meteorology, and transportation. Cyber and physical components interaction, training and adaptation ability, interoperability using IoT devices, information security using firewalls and cryptosystems, system robustness, and intervention of human inside and out of the loop are the major focusing areas in any CPS. In this chapter, application areas and challenges faced by cyber physical systems are discussed in detail.

Cyber-Physical System (CPS) is an important part of the Internet of Things concept. CPS is based on seamless integration of computational algorithms into the physical environment. Users can interact with CPS by means of various interfaces to get some specified services. This creates conditions for implementing a Smart Environment based on the CPS concept within an enterprise or production site. One of the urgent services in such a Smart Environment is Localization and Navigation service. The paper suggests Proactive Localization System for tracking and predicting location of users, as well as mobile robotics, which is a part of Cyber-Physical Smart Environment. This service allows tracking every mobile entity within the CPS: a user, an autonomous mobile robot, etc. Also, this service makes it possible to predict the activity of the tracking object by means of several machine learning techniques. The paper compares various machine learning models for our system, and present the concept of Proactive Localization system.

У контексті розгортання Концепції 4.0 в Україні запропоновано системну модель інформаційної безпеки “розумного міста” на рівні: його сегментів; складових – “розумних об’єктів” та багаторівневих кіберфізичних систем (КФС) “фізичний простір (ФП) – комунікаційне середовище (КС) – кібернетичний простір (КП)”; загроз рівням КФС, компонентам рівня та процесам, що відповідають рівню: відбиранню інформації, передаванню/прийманню, обробленню, управлінню; технологій забезпечення безпеки структури та функціоналу сегменту “розумного міста” за профілями – конфіденційність, цілісність, доступність. Модель розгорнута для сегментів: “розумна енергетика”, “розумне довкілля”, “розумна медицина”, “розумна інфраструктура” і побудована за принципами системного аналізу – цілісності, ієрархічності, багатоаспектності. Системна модель на основі КФС дозволяє створювати комплексні системи безпеки (КСБ) “розумних об’єктів” відповідно до: концепції “об’єкт – загроза – захист”, універсальної платформи “загрози – профілі безпеки – інструментарій”, методологічних підходів до багаторівневого захисту інформації, функціональних процесів захищеного обміну. Така системна структура може бути використана також для забезпечення гарантоздатності системи “розумний об’єкт – кіберфізична технологія” у просторі функціональної та інформаційної безпеки. Проаналізовано безпеку МЕМS-давачів як компоненти інтернету речей у ФП кіберфізичних систем: загрози – лінійні навантаження, власні шуми елементів схеми, температурні залежності, зношуваність; технології захисту – лінійні стабілізатори, термотривкі елементи, охолодження, покращання технології виготовлення, методи отримання нових матеріалів та покращання властивостей. На протидію перехопленню інформації в безпровідних каналах зв’язку, характерної розумним об’єктам, розглянуто алгоритм блокового шифрування даних AES в сенсорних мережах з програмною реалізацією мовою програмування C#. Проаналізовано безпеку хмарних технологій як компоненти КС кіберфізичних систем на апаратно-програмному рівні та наведено особливості криптографічних систем шифрування даних в хмарних технологіях відповідно до нормативного забезпечення.

Summary form only given. Rapid advancements in smartphones, wireless sensors and mobile communications have led to the development of cyber-physical systems, pervasive computing and smart environments with important applications in environmental, civilian, military, industry, and government sectors. Sensor networks and smartphones play significant roles in this context as they not only act as effective interface between physical and cyber worlds, but also bring in human social aspects. However, increasing scale and heterogeneity at all levels - users, devices, networking and computing technologies, information and services - implies a high degree of uncertainty in distributed control and operations of pervasive and cyber-physical systems, thereby posing significant challenges in providing desired information quality, assurance, and reliability for intelligent decision making. This is particularly important for critical applications like smart health care and pervasive security. This talk will examine uncertainty-driven unique challenges and opportunities in cyber-physical and pervasive computing systems and their inter-winding relationships with smart environments. The talk will be concluded with provocative thoughts, open issues and future directions of research.

This study intends to develop Hat Yai's Smart ICT model. IoT, Big Data, Cloud, etc. This study will help Hat Yai's governor create a Smart City and Smart ICT solution. It helps discover the Smart City component that will benefit residents most while maintaining faithfully to the city's original development goal. This research will also help create Smart ICT solutions for Smart City development. A Smart Society, Smart Environment, and Smart Economy fit Hat Yai City's development strategy. The project aims to find a relationship between IoT, Big Data, Cyber-Physical systems, and Cloud Computing. The researcher surveyed 565 respondents in Hat Yai, Thailand, both those whose world is important to Smart ICT or the Internet of Things, Big Data, Cyber-Physical systems, and Cloud Computing and those who are not, and evaluated the data using Pearson Correlation. Internet of Things (IoT) technology is linked to a Smart Society, Smart Environment, and Smart Economy. Big Data helps build a Smart Society. Cyber-Physical System result demonstrates a relationship between a Smart Society and Smart Environment, and Cloud Computing shows a relationship.

A smart city is considered a sustainable city that manages needed resources and makes autonomous decisions to improve the quality of life of its citizens. On the other hand, Cyber-Physical Systems (CPS) have been implemented as isolated systems inside the city. For instance, the traffic lights, autonomous navigation for cars, and so on. Instead, consider a smart city with an integrated CPS for independent blocks that can be interconnected in a central unit. However, when a CPS makes decisions about the integration of ethical concepts based on human perception, social space must be added, and so a CPS must be transformed into a Cyber-Physical Social System (CPSS). Furthermore, a new type of social interaction between all the elements in a CPSS within a smart city presents human behavioral challenges such as virtual-morality. This paper first proposes an Artificial Moral Agent with machine learning algorithms to regulate the interaction within the CPSS, adding itself to all the subsystems’ communication. Additionally, a moral agent structure is proposed with a morality filter as its fundamental component.KeywordsCyber-physical systemsCPSSSocial featureSmart CityMoral agentAI

Cyber Physical Social Systems (CPSS) has been rapidly developing in recent years because of the dramatic growth of mobile techniques and Internet-based technologies. As an emerging novel technical paradigm, cloud computing is becoming an efficient mechanism that has been broadly implemented in multiple fields with using Internet-enabled devices. Telehealth system is one of the crucial domains in applications of Cyber Physical Systems (CPS), which is also considered an important component in smart city. However, Personalized Cloud-based Telehealth (PCTH) is still facing a great challenge due to restrictions deriving from various perspectives, such as cloud resource allocations and real-time information transfers. This paper concentrates on the issue of optimizing the performance of the resource allocation for achieving smart tele-health with obtaining and analyzing real-time data within the dynamic application environment in cloud computing. The dynamic data environment is mainly associated with social connections generated by physicians or health organizations. Along with this focus, we propose a novel approach, entitled Smart Cloud-based Telehealth Cyber Physical Social Systems (SCT-CPSS), to enable mobile CPSS to offer users a real-time health information service based on the social networking behaviors and inputs. Main algorithms used in this proposed mechanism include Real-Time Matching with Dynamic Programming Algorithm (RTM-DPA) and Monte Carlo-based Real-Time Analysis Algorithm (MC-RTAA). Our experiment examination has evaluated the performance of the proposed paradigm.

Cyber-Physical Systems (CPS) are composed of heterogeneous devices, communicating with each other and interacting with the physical world. Fostered by the growing use of smart devices that are permanently connected to the Internet, these CPS can be found in smart environments such as smart buildings, pavilions or homes. CPS must cope with the complexity and heterogeneity of their connected devices while supporting end-users with limited technical background to configure and manage their system. To deal with these issues, in this paper we introduce SmartyCo, our approach based on Dynamic Software Product Line (DSPL) principles to configure and manage CPS for smart environments. We describe its underlying architecture and illustrate in the context of smart homes how end-users can use it to define their own CPS in an automated way. We then explain how such an approach supports the reconfiguration of smart devices based on end-users rules, thus adapting the CPS w.r.t. environment changes. Finally, we show that our approach is well-suited to handle the addition and removal of CPS devices while the system is running, and we report on our experience in enabling home inhabitants to dynamically reconfigure their CPS.

Enormous developments and innovations in cyber physical systems (CPS) moved this paradigm to a new stage of our daily life that is called cyber physical social systems (CPSS). The main concern in CPSS is managing social requirements and concerns by potential abilities of CPS. Agricultural Supply Chain Systems (ASCS) study the process of food and agricultural products circulation for the purpose of improving performance and profit of the entities. Indeed, ASCS have a great influence on social developments due to role and population of farmers in most of the countries. Improving the financial status of farmers and reducing final price in market are reachable by eliminating or optimizing the middle entities in ASCS, as many as possible, between farmers and consumers. To this end, we propose a new conceptual framework for integrating CPSS into ASCS by studying potentialities and challenges. Advancements are being analyzed along with discussion for future works.

The papers in this special section focus on cyber-physical man-machine systems with particular emphasis on situation, activity, and goal awareness deployed in these systems. Recent advances in sensing technologies, the Internet of Things, pervasive computing, smart environments have transformed traditional embedded ICT systems into an ecosystem of interconnected and collaborating smart objects, devices, embedded systems, and most importantly humans. Such systems, often referred to as cyber-physical systems (CPS), are usually human user-driven or user-centered, and are aimed at providing people and businesses with a wide range of innovative applications and services. For example, a “smart home” can monitor and analyze the daily activities of its inhabitants, usually the elderly or individuals with disabilities, so that personalized context-aware assistance can be provided. A “smart city” can monitor, manage, and potentially control all basic city functionalities such as transport, energy supply, and waste collection, at a higher level of automation by collecting and harnessing sensor data across a large geographic expanse. In order to respond in real-time to an individual user’s specific needs in dynamic and complex situations, and to support ergonomics and user-friendliness through consideration of human factors such as privacy, dignity, and behavior characteristics, cyber-physical human–machine systems need to be aware of the physical environment and human participant behavior. This awareness enables effective and fast feedback loops between sensing and actuation, possibly with cognitive and learning capabilities adapting to participant preferences, capabilities, and the modality of human–machine interaction as well as dynamic situations.

Research on Cyber Physical Systems (CPS) has led to quite a number of astonishing technical solutions that are becoming standard in many application domains affecting our everyday life. The technical innovations range from control theory concepts to real-time wireless communication to networked control. Some of the most challenging applications include cooperative autonomous driving and industry automation. Despite all these great findings, our research community frequently lost track on the impact of individual human beings that are an integral part of the systems - both as a user as well as a source of disruption. We thus need a paradigm shift from classical CPS to Cyber Physical Social Systems (CPSS). Studying the impact of CPS on humans and vice versa, hybridization, i.e., machines and human users covering parts of the system function in deep interaction, is required as a novel core concept. This is also a basis for final public acceptance as a key to success of new technologies. We investigate these ideas based on the application domain of cooperative autonomous driving and identify core research challenges of such hybridized CPSS.

Integration of computing and networking systems has recently been actively considered as an effective method of offering intelligent services to end-users and maximizing resource utilization. This convergence established the path for the Internet of Things (IoT) to arise. The IoT refers to a modern world in which billions of smart devices connect automatically and interact with each other. One of the most significant subjects in today's digital world is the Social Internet of Things (SIoT), a new exemplary class of the cyber physical social system (CPSS) that combines IoT and social networks. SIoT refers to a social network paradigm that involves both human-to-human communications and object-to-object interactions. Human beings are believed to be intellectual and sociable creatures. They developed a social network to attain shared objectives, including increasing performance, social behavior, security, and efficiency, in addition to offering the essential services they demand. This social structure, which allows people and things to form trust-based social relationships, can enhance object navigation and limit the object's capacity to a controllable social network of the whole thing, similar to standard social network services (SNS). SIoT, on the other hand, inherits features from several networking and computing contexts such as IoT and SNS, which significantly surge the volume and diversity of contextual information that must be managed for SIoT's adaptive service provisioning; this is the chapter's key issue. The major goal of this chapter is to give a detailed examination of the SIoT system to examine and evaluate current work in this field. As an outcome, we focus on SIoT architecture, relation management, trust management, a security framework for smart environments that integrates smoothly with diverse IoT applications, and privacy paradigm problems. This chapter focuses on the smart environment for SIoT security architecture, the framework designed to function easily with a variety of IoT applications. It aids in the separation of security and practical privacy disputes and discusses how to isolate modules that offer functionality for each layer (for example, internet, interface, and IoT device).