Emergence of Cyber Physical System and IoT in Smart Automation and Robotics

Global research and developments in robotics and IoT have received noteworthy consideration in the present years. The chapter highlights some efforts of researchers in robotics and artificial intelligence using IoT applications and advancements. The intelligent robotics structures exploit the physical shapes of robotics and have the ability to think and perform duties like human beings. Artificial intelligence focusses on the aspects like how the robot or machine performs duties, such as reasoning, learning, and problem solving. The IoT of robotics is an emerging area of research and development that brings together universal sensors and autonomous systems. The fusion of robotics and IoT technologies will increase the capabilities of new creation in both the existing IoT and the robotics systems. Integration of the IoT and robotics gives birth to new concept titled “Internet of Robotic Things (IoRT)”; it talks about the beginning of cloud robotics and its support toward robotic functions like sensing, manipulation, and mobility. The IoRT-aided systems are very useful in various applications of every domain in life like medical, defense, farming, industrial plants, and rescue operations. Moreover, the track to an established evolution of IoT-aided robotics products needs several essential issues to be resolved, designing methods to be associated, and strong structural choices to be deliberated. This chapter covers scientific consequences, open problems, challenges, and target applications in the IoRT area. In today’s scenario, IoT-aided robotics has diverse fields and services like: communication networks, distributed and pervasive computing, semantic-oriented approaches to consensus, network security, and many others.

With the expeditious growth of technology, robotics seems to be the new literature of the world. The idea of digitalizing machines, automation and computers is making robotics to grow at a faster velocity. In accordance with the Internet of things (IoT) and cyber-physical system (CPS), a new hypothesis of robotics is emerging. IoT cooperates with devices through wireless or wired medium to create new applications and gadgets to reach specific goals. If CPS is the viaduct for the emerging advancement of technology, then IoT is an upright for the technology. There are numerous amounts of fields where convergence is evident, such as driverless cars, decision-making, agriculture and many more. This chapter focuses on how two different aspects IoT and CPS converge together in the robotics industry making it more efficient and pleasing to adapt by other organizations, institutions, etc.

In recent years, new concepts as IoT, industrial IoT, and cyber-physical systems have emerged with the active penetration of information and communication technologies into industrial processes. Interrelationships between these conceptions and the degree of integration between them are considered the apotheosis of modern days. As a result, this chapter focuses on the integration of IoT, industrial IoT, and cyber-physical systems. It provides analytical data on the industrial revolution and Industry 4.0, information about IoT, IIoT, and cyber-physical systems for smart environments, their history, development trends, definitions, architectures, components, applications, and characteristics. Also, IoT, IIoT, and cyber-physical systems were compared in terms of origin, application, architecture, characteristics, and the degree of integration between them was determined. Studied following issues of integrated IoT, IIoT, and cyber-physical systems—control issues, network construction issues, computing issues, and security issues.

In this chapter, we aim to aid the development of Cyber-Physical Systems (CPS) in automated understanding of events and activities in various applications of video-surveillance. These events are mostly captured by drones, CCTVs or novice and unskilled individuals on low-end devices. Being unconstrained in nature, these videos are immensely challenging due to a number of quality factors. We present an extensive account of the various approaches taken to solve the problem over the years. This ranges from methods as early as Structure from Motion (SFM) based approaches to recent solution frameworks involving deep neural networks. We show that the long-term motion patterns alone play a pivotal role in the task of recognizing an event. Consequently each video is significantly represented by a fixed number of key-frames using a graph-based approach. Only the temporal features are exploited using a hybrid Convolutional Neural Network (CNN + Recurrent Neural Network (RNN)) architecture. The results we obtain are encouraging as they outperform standard temporal CNNs and are at par with those using spatial information along with motion cues. Further exploring multistream models, we conceive a multi-tier fusion strategy for the spatial and temporal wings of a network. A consolidated representation of the respective individual prediction vectors on video and frame levels is obtained using a biased conflation technique. The fusion strategy endows us with greater rise in precision on each stage as compared to the state-of-the-art methods, and thus a powerful consensus is achieved in classification. Results are recorded on four benchmark datasets widely used in the domain of action recognition, namely Columbia Consumer Videos (CCV), Human Motion Database (HMDB), UCF-101 and Kodak’s Consumer Video (KCV). It is inferable that focusing on better classification of the video sequences certainly leads to robust actuation of a system designed for event surveillance and object cum activity tracking.

The importance of agriculture to the economic growth in sub-Saharan Africa suffers from several challenges. One of the major problems faced by the sector is the lack of suitable technology to optimize yield and profit to reduce the reliance of farmers on manual techniques of farming which is accompanied by drudgery, wastage, and low yields. Precision agriculture has been applied to maximize agricultural outputs while minimizing inputs. This study presents the design of an Internet of things (IoT)-based autonomous robot system that can be used for precision agricultural operations in maize crop production. The robot consists of a camera for remotely monitoring of the environment and a tank incorporated with a liquid level sensor which can be used for irrigation and herbicide application. The real-time feed from the camera as well as the output from the liquid level sensor is accessed from a cloud database via a Web application. This system can be adopted for improved crop production which in turn will increase crop yield, profit, and revenue generated from agriculture.

A recent evolution in the field of Internet of Things (IoT) is the interdisciplinary domain involving smart automation and robotics implemented by the techniques of Internet of Things (IoT), famously known as Internet of Robotic Things (IoRT). This emerging technology is adopted in various sectors such as health care, manufacturing industries, economic, information technology and several other fields. Persistent sensors and actuators involved in robotics and automation are brought together by the emerging vision of Internet of Robotic Things. The domains of robotics and Internet of Things (IoT) cannot be viewed separately hence integrated together to form the novel domain—Internet of Robotic Things where the technologies of robotics are implemented in the scenarios of IoT. This chapter aims to provide an overview of possible solutions for various issues in smart automation environment and applications of robotics using Internet of Things (IoT). Envisioning dense heterogeneous devices communicating with each other to accomplish various objectives in the field of automation and robotics using Internet of Things (IoT) is the aim of this chapter. This technology can increase efficiency at reduced cost, significantly reducing manual intervention by increasing automation process visioning by SCADA systems. Industrial automation involving Internet of Things (IoT) has the goal of self-configuration, self-organization, self-healing system, scalability with less power consumption compatible to global standards. Involvement of robotics in the field of Internet of Things (IoT) potentially changes the process of production where the operations are performed rapidly in an accurate way leading to tremendous value in the field of automation. These two domains are converged and developed to provide the concept, architecture, involved technologies, challenges and applications and future work in order to cover (Internet of Robotic Things) IoRT comprehensively.

The Internet of things (IoT) idea is advancing quickly and affecting new advancements in different application areas. For example, the Internet of mobile things (IoMT), autonomous Internet of things (An IoT), autonomous system of things (ASoT), Internet of autonomous things (IoAT), Internet of things clouds (IoT-C) and the Internet of robotic things (IoRT) that are regressing/progressing by utilizing IoT innovation. The IoRT speaks to new assembly challenges, and there should be tended to, in one surface the programmability and correspondence of various heterogeneous versatile/self-ruling/mechanical things for participating, their coordination, set up, trade of data, security, well-being and insurance. Advancements in IoT heterogeneous equal preparing/correspondence and dynamic frameworks dependent on parallelism and simultaneousness require new thoughts for coordinating the astute “gadgets”, community robots (COBOTS) and keen on IoT appliance. Dynamic viability, identity mending, self-fix of assets, varying asset condition system and setting support IoT frameworks. Administration usage and reconciliation through IoT organize administration creation are of vital significance when original “intellectual gadgets” are turning out to be dynamic members in IoT applications.

Being one of the most populous countries in the world, India has a healthcare delivery system that consists of both public and private concerns in four levels, i.e., Central, State, District, and Panchayati Raj level. The healthcare system of these levels has a separate database to store the patient history in large numbers and one has to carry his or her medical history in physical form for treatment in separate health centers. Each center has to send noticeable diseases to the health ministry. The objectives of this study are to search for a new area in our healthcare delivery system where digitalization can play a pivotal role, can mitigate any epidemic and pandemic disaster with ease, maintain single cloud-based medical records using single identity card anywhere in India, use biometrics or card number to access the medical history of the patient for a clinical, emergency, preventive, and mitigation using unique identity number (UID), viz. Aadhaar in India.

Robotics involves design, construction, operation, and use of intelligent machines that possess the ability to sense, compute, manipulate, and navigate environments to monitor events and execute an appropriate course of action. Internet of Things (IoT) on the other hand is a fast-developing novel technology consisting of group of uniquely addressable heterogeneous smart objects or tiny devices (things) interconnected via the Internet to share and process data from different sources. IoT is designed with the goal to “connect everything and everyone everywhere to everything and everyone else.” The two technologies, IoT and robotics, have evolved into Internet of Robotic Things (IoRT) by the creation of a synergy between the two. IoRT aims at enhancing the current IoT with active sensing and actuation from robotics. This idea opened a novel opportunity for collaboration between IoT and robotics applications and research communities. However, most application domains of IoT and robotics have not fully explored the use of IoRT. This chapter discusses the (potential) applications of IoT-aided robotics in different domains, explaining how robots can extend the capabilities of existing IoT architectures to make them more knowledgeable and smarter; discuss some of the challenges in the full realization and application of IoRT; and lastly proposes an IoRT architecture for smart library management, an area that has not received much attention in the research community.

Nowadays, signal processing algorithms are simulated generally using MATLAB. Their hardware implementation requires either application-specific IC (ASICs) or system on chip (SoCs). But there are severe constraints on producing such chips. Therefore, hardware implementation on graphical processing unit (GPUs) or field programmable gate array (FPGA) can provide the answer to the problem. Signal processing involves mathematical calculations in the form of algorithms, which are required to be implemented finally as stand-alone hardware to be used as a system. Recently, GPUs have increasingly being used for hardware implementation of signal processing algorithms. This is because they can be programmed easily with the help of open-source coding languages like Python, CUDA, or OpenCL providing cost benefits in terms of lower costs and generic programming. Also, they possess, in general, a greater number of cores as compared to ASICs or SoCs making GPUs multi-application platforms that can solve the problem of the lower yield factor of the ASICs. They are also better than ASICs and SoCs in terms of performance since it has a dedicated processor to handle 2D and 3D graphics, which comprises of polygons and polygonal transformations involving computationally dearer multiple floating-point operations. Hence, more complex signal analysis can be performed using them. Additionally, the massively parallel architecture of GPUs further enhances their high computing performance. There exist many GPU-accelerated applications that provide an easy way to high-performance computing (HPC). In light of the above discussion, this chapter intends to inform and help readers know properly about the hardware implementations of different signal processing algorithms, by showcasing appropriate hardware platforms and different open-source coding languages along with their implementation methodologies. Therefore, they will be able to appreciate the difference between hardware implementations using ASICs/SoCs or GPUs/FPGAs. As GPUs or FPGAs take a faster time-to-market approach, as no layout, masks, or other steps are required for the manufacturing, they possess a simpler design cycle and the most important, the feature of field reprogram ability.

Internet of things (IoT) and its improved version narrow band Internet of things (NB-IoT) use smart networks to meet the needs of the modern world. These components are very important for collecting data from the environment and correctly managing the related scenarios, and thus more use of wireless networks in IoT-supported heterogeneous networks. Decision making is the main component in the IoT universe, and this function’s consistency depends on the accuracy of the data obtained from the sensor nodes. IoT and NB-IoT are the most exciting cutting-edge technologies for solving above-mentioned problems. IoT supports many revolutionary commercial and social solutions, including food production, wearable or inconspicuous medical sensors, Industry 4.0, power, water grids, smart cities, education, transportation and road infrastructure needs. Industry 4.0 symbolizes the beginning of the Fourth Industrial Revolution. Industry 4.0 represents the current trend of automation technologies in the manufacturing industry and primarily covers cyber-physical systems (CPS), IoT and cloud computing at the moment, low power wide area network (LPWAN) is a promissory and highly effective solution for IoT and machine-to-machine (M2M) communication-based applications with long range and low power consumption. With the eagerly awaited developments in artificial intelligence, machine learning, data analysis, and block chain technologies, LPWAN applications have the potential to undergo epic expansion in nearly every area of society, business, and industry. This chapter aims to stimulate a discussion about the role of IoT and NB-IoT which can play in overcoming the limitations of a wide-ranging deployment of autonomous networks and their usage in real-world phenomena.

In recent decades, the Internet of things (IoT) has had a huge impact on various domains, such as logistics, health care, robotics, and manufacturing, coping with an enormous amount of data transferred by different resource-constrained IoT network devices. For diverse applications, IoT can be seen as a network of devices comprising hardware, software, sensors, actuators, and connectivity allowing the networked system to link, communicate, and share information. In IoT configurations, billions of devices can be connected to the Internet to transfer data quickly, efficiently, and securely. Though there are great advancements in IoT technologies, certain limitations are still to be considered. Firstly, IoT devices have limited resources like memory, computing power, and energy (Khanpara and Lavingia in Multimedia big data computing for IoT applications. Springer, Singapore, pp. 37–57, 2020). Besides, IoT devices may link the behavior of a person to their identity which challenges the privacy of a person. Many researchers have made numerous successful attempts to integrate reliable protocols with IoT devices that can function efficiently in a resource-constrained environment and robustly against data transmission security and privacy issues. IoT integrates with the wireless sensor network (WSN) and the mobile ad hoc network (MANET) in smart environments and is becoming much more desirable and economically efficient. The MANET is not only ideal for disaster situations but can also be used for robotic communication. Interaction with the IoT systems between WSNs and MANETs enables the development of new MANET-based IoT systems which give the consumer more mobility and lower costs. At the same time, the networking aspects open up new challenging issues. Hence, this chapter discusses various existing secure MANET protocols that provide secure data transmission and can also be used in the IoT environment to provide robustness in the presence of a variety of threats and vulnerabilities. This chapter also presents some major challenges in the emerging domain of MANET-based IoT systems for robotics.

The technology, which is behind this drastically changing world, is the Internet of things (IoT) and Internet of things connected devices. These devices are capable of communicating over the Internet by using various protocols designed for wireless networks. In recent years, IoT devices have flooded the market, and their services to the society and the world infrastructure are becoming vital. The growing demand for automation has accelerated the deployment of IoT devices across the world. Not only the intelligent IoT devices and sensors but the robots also have become the backbone of smart automation systems such as home automation, industrial automation, and city automation (smart cities). The increasing number of these smart devices and growing infrastructure is creating security and privacy challenges, but at the same time, a number of leading companies have extended their support to curb the threat that may be fatal if not taken seriously. Startups have also started working in fields like healthcare, transportation, and delivery of goods via IoT devices across smart cities. Monitoring of streetlights, air quality, noise and traffic of a city, security, and optimal use of home appliances in a home and development of innovative technologies and increasing the production in an industry are some of the IoT and robotic services that the world is already exploiting. This chapter discusses the importance of intelligent IoT devices and robotics today and in future in the domains like home automation, industrial automation, and city automation.

The advent of Industry 4.0 has moved the manufacturing industry to recent models of Internet of Things (IoT), cyber physical systems (CPS), cloud manufacturing, fog computing, big data analytics, among others. Data has become more ubiquitous with the increase in the development of mobile and wireless networking technologies. Also, due to high expectations for productivity improvement, efficiency, and enabling innovative service through collaborative means, IoT is attracting much attention. CPS is the integration of computational objects in fitting together with the corporal biosphere and its procedures. CPSs are complicated manufacturing systems with the goal to combine and harmonize mechanism biosphere and industrial capability to the cyber computational space. Nevertheless, having thorough interconnectivity and a computational platform is essential for a practicable application of CPSs and smart factories. Smart manufacturing, also known as Industry 4.0 or Industry Internet of Things (IIoT), is increasingly becoming the common goal of various industrial and national strategies. For a better implementation of smart manufacturing, smart interconnection is one of the most significant issues. Current technologies, however, are not yet completely equipped for smart interconnection while working with heterogeneous hardware, fast setup, and delivery, as well as online service generation. In this chapter, the effects of IoT technology and CPS in the advancement and awareness of real-life smart manufacturing is addressed. An integrated IoT and CPS framework is recommended as a specification for researchers and industries toward the full realization of the potentials of IoT with CPS in the development of Industry 4.0 smart manufacturing technologies.