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The Fourth Industrial Revolution has revealed some emerging concepts and technologies. In the framework of Industry 4.0, the Internet of things (IoT) is one of the key concepts as well as an evolving paradigm that creates opportunities of integration between the things and the physical world which has an unprecedented influence in our lives, particularly in the lives of those with disabilities. It is a groundbreaking way of providing independent living opportunities to individuals with disabilities, such as academic and learning aids (e.g. computer-based software, portable word processors), communication aids (e.g. captioning devices, smart glasses, augmentative communication devices), mobility aids (e.g. smart canes, smart wheelchairs), and smart systems (e.g. smart home, smart city, smart workplace), which increase the amount of their participation in the society, thus, empowering individuals with disabilities. This chapter aims to present the IoT technologies for individuals with disabilities and consists of five sections. The first section presents background information about the IoT and how it relates to individuals with disabilities. The second section introduces key technologies and applications that drive the IoT concept of Industry 4.0 in terms of the subject of disability in five domains which are mobility, smart environments, monitoring, communication, and education. The third section illustrates the importance of the IoT technologies and its relevance to the universal approach. The fourth section presents the implications of global business and implications of COVID-19 for IoT technologies. Finally, the chapter concludes with suggestions.

As the size of the population is growing and the capacity of the planet Earth is limited, human beings are searching for sustainable and technology-enabled solutions to support society, ecology and economy. One of the solutions has been developing smart sustainable cities. Smart sustainable cities are cities as systems, where their infrastructure, different subsystems and different functional domains are virtually connected to the information and communication technologies (ICT) and internet via sensors and devices and the Internet of Things (IoT), to collect and process real-time Big Data and make efficient, effective and sustainable solutions for a democratic and liveable city for its various stakeholders. This chapter explores the concepts and practices of sustainable smart cities across the globe and explores the use of technologies such as IoT, Blockchain technology and Cloud computing, etc. their challenges and then presents a view on business models for sustainable smart cities.

Globalization has increased the consumer's demand for safe and quality foods. To make food available to consumers from farm to fork, packaging plays a crucial role. The objective of packaging is to shield the foodstuff from degrading and to serve as the medium of communication between the processing industry and the consumers. Conventionally, several materials are used in the packaging such as laminates, plastics, glass, metal, etc., but with the advent of technology, newer and novel smart packaging technologies have entered this field. Smart packaging in the form of active and intelligent packaging not only acts as a barrier to external influences but also prevents internal deterioration. Oxygen scavengers, moisture controllers, antioxidants, CO₂ absorber/emitter, antimicrobial agents, etc., are some of the vital active packaging systems. On the other hand, an intelligent packaging system contains internal or external indicators and sensors that monitor the condition of packed food and gives information about its quality during storage and transportation. It seems that these interventions in packaging have very positive effects on the whole industry, but it is observed that this advancement in the packaging has also raised questions about its disposal. To overcome this issue, industries have started using smart packaging design along with the sustainable packaging trend. Communication with the recycling bodies at the time of development will ensure the smart packaging fit to be recycled. Considering such standards for smart packaging will not only create a healthy bond between industries and consumers but will also help in sustainable development. This chapter mainly focuses on the advancement of the packaging system associated with the agri-food sector. It also discusses how the implementation of these technological advancements will help the industries toward sustainable development.

This chapter presents a novel human arm gesture tracking and recognition technique based on fuzzy logic and nonlinear Kalman filtering with applications in crane guidance. A Kinect visual sensor and a Myo armband sensor are jointly utilised to perform data fusion to provide more accurate and reliable information on Euler angles, angular velocity, linear acceleration and electromyography data in real time. Dynamic equations for arm gesture movement are formulated with Newton–Euler equations based on Denavit–Hartenberg parameters. Nonlinear Kalman filtering techniques, including the extended Kalman filter and the unscented Kalman filter, are applied in order to perform reliable sensor fusion, and their tracking accuracies are compared. A Sugeno-type fuzzy inference system is proposed for arm gesture recognition. Hardware experiments have shown the efficacy of the proposed method for crane guidance applications.

The ROV ground control simulator (Fig. 1) used in this multi-sensory research consists of two workstations: pilot and SO. At the left workstation, the pilot controls ROV flight (via stick-and-throttle inputs as well as invoking auto-holds), manages subsystems, and handles external communications. From the right workstation, the SO is responsible for locating and identifying points of interest on the ground by controlling cameras mounted on the ROV. Each station has an upper and a head-level 17″ color CRT display, as well as two 10″ head-down color displays. The upper CRT of both stations displays a ‘God's Eye’ area map (fixed, north up) with overlaid symbology identifying current ROV location, flight waypoints, and current sensor footprint. The head-level CRT (i.e., “camera display”) displays simulated video imagery from cameras mounted on the ROV. Head-up display (HUD) symbology is overlaid on the pilot's camera display and sensor specific data are overlaid on the SO's camera display. The head-down displays present subsystem and communication information as well as command menus. The simulation is hosted on four dual-Pentium PCs. The control sticks are from Measurement Systems Inc. and the throttle assemblies were manufactured in-house.

Satellite images can be a powerful source of data for analyses of conflict dynamics and social movements, but sociology has been slow to develop methods and metadata standards for transforming those images into data. We ask: How can satellite images become useful data? What are the key methodological and ethical considerations for incorporating high-resolution satellite images into conflict research? Why are metadata important in this work? We begin with a review of recent developments in satellite-based social scientific work on conflict, then discuss the technical and epistemological issues raised by machine processing of satellite information into user-ready images. We argue that high-resolution images can be useful analytical tools provided they are used with full awareness of their ethical and technical parameters. To support our analysis, we draw on two novel studies of satellite data research practices during the Syrian war. We conclude with a discussion of specific methodological procedures tried and tested in our ongoing work.

This chapter provides an overview of the Department of Defense (DoD) laboratory structure to help equipment designers, modelers, and manufacturers determine where research, testing programs, or relevant findings can be found. The chapter includes a discussion of the performance measures and metrics typically used in DoD laboratories and concludes by considering the current state-of-the-art as well as the state-of-the-possible for human performance measurement.