IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety Enables readers to understand a broad area of state-of-the-art research in physical IoT-enabled security IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety describes new techniques in unobtrusive surveillance that enable people to act and communicate freely, while at the same time protecting them from malevolent behavior. It begins by characterizing the latest on surveillance systems deployed at smart campuses, miniatures of smart cities with more demanding frameworks that enable learning, social interaction, and creativity, and by performing a comparative assessment in the area of unobtrusive surveillance systems for smart campuses. A proposed taxonomy for IoT-enabled smart campus unfolds in five research dimensions: (1) physical infrastructure; (2) enabling technologies; (3) software analytics; (4) system security; and (5) research methodology. By applying this taxonomy and by adopting a weighted scoring model on the surveyed systems, the book presents the state of the art and then makes a comparative assessment to classify the systems. Finally, the book extracts valuable conclusions and inferences from this classification, providing insights and directions towards required services offered by unobtrusive surveillance systems for smart campuses. IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety includes specific discussion of: Smart campus’s prior work taxonomies and classifications, a proposed taxonomy, and an adopted weight scoring model Personal consumer benefits and potential social dilemmas encountered when adopting an unobtrusive surveillance system Systems that focus on smart buildings, public spaces, smart lighting and smart traffic lights, smart labs, and smart campus ambient intelligence A case study of a spatiotemporal authentication unobtrusive surveillance system for smart campus safety and emerging issues for further research directions IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety is an essential resource for computer science and engineering academics, professionals, and every individual who is working and doing research in the area of unobtrusive surveillance systems and physical security to face malevolent behavior in smart campuses.

IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety Enables readers to understand a broad area of state-of-the-art research in physical IoT-enabled security IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety describes new techniques in unobtrusive surveillance that enable people to act and communicate freely, while at the same time protecting them from malevolent behavior. It begins by characterizing the latest on surveillance systems deployed at smart campuses, miniatures of smart cities with more demanding frameworks that enable learning, social interaction, and creativity, and by performing a comparative assessment in the area of unobtrusive surveillance systems for smart campuses. A proposed taxonomy for IoT-enabled smart campus unfolds in five research dimensions: (1) physical infrastructure; (2) enabling technologies; (3) software analytics; (4) system security; and (5) research methodology. By applying this taxonomy and by adopting a weighted scoring model on the surveyed systems, the book presents the state of the art and then makes a comparative assessment to classify the systems. Finally, the book extracts valuable conclusions and inferences from this classification, providing insights and directions towards required services offered by unobtrusive surveillance systems for smart campuses. IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety includes specific discussion of: Smart campus’s prior work taxonomies and classifications, a proposed taxonomy, and an adopted weight scoring model Personal consumer benefits and potential social dilemmas encountered when adopting an unobtrusive surveillance system Systems that focus on smart buildings, public spaces, smart lighting and smart traffic lights, smart labs, and smart campus ambient intelligence A case study of a spatiotemporal authentication unobtrusive surveillance system for smart campus safety and emerging issues for further research directions IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety is an essential resource for computer science and engineering academics, professionals, and every individual who is working and doing research in the area of unobtrusive surveillance systems and physical security to face malevolent behavior in smart campuses.

The rapid growth of IoT and its applications in smart cities pose significant challenges for academic scholars. The increasing number of interconnected devices and the massive amounts of data they generate strain traditional networks, leading to inefficiencies and security vulnerabilities. Additionally, the centralized control plane in Software Defined Networks (SDN) presents a single point of failure, hindering network performance, while IoT devices themselves are susceptible to attacks, compromising user data and privacy. To address these pressing issues, Network-Enabled IoT Applications for Smart City Services offers a compelling solution. Edited by Dr. K. Hemant Kumar Reddy, Dr. Diptendu SinhaRoy, and Tapas Mishra, this book advocates leveraging SDN to handle high-frequency data streams effectively. It also proposes the integration of blockchain technology to enhance security and reliability in IoT applications, offering a roadmap for scholars to improve network efficiency, security, and reliability in IoT and smart city domains. With their extensive expertise, the authors provide academic scholars with a comprehensive and innovative resource that inspires further research and development in this evolving field, enabling them to make significant contributions to the advancement of IoT and smart city technologies.

This book provides an insight on the importance that the Internet of Things (IoT) and Information and Communication Technology (ICT) solutions can offer towards smart city and healthcare applications. The book features include elaboration of recent and emerging developments in various specializations of curing health problems; smart transportation systems, traffic management for smart cities; energy management, deep learning and machine learning techniques for smart health and smart cities; and concepts that incorporate the Internet of Everything (IoE). The book discusses useful IoE applications and architectures that cater to critical knowledge creation towards developing new capacities and outstanding economic opportunities for businesses and the society.

Internet of Things (IoT) is a recent technology paradigm that creates a global network of machines and devices that are capable of communicating with each other. Security cameras, sensors, vehicles, buildings, and software are examples of devices that can exchange data between each other. IoT is recognized as one of the most important areas of future technologies and is gaining vast recognition in a wide range of applications and fields related to smart homes and cities, military, education, hospitals, homeland security systems, transportation and autonomous connected cars, agriculture, intelligent shopping systems, and other modern technologies. This book explores the most important IoT automated and smart applications to help the reader understand the principle of using IoT in such applications.

This book covers all the emerging trends in artificial intelligence (AI) and the Internet of Things (IoT). The Internet of Things is a term that has been introduced in recent years to define devices that are able to connect and transfer data to other devices via the Internet. While IoT and sensors have the ability to harness large volumes of data, AI can learn patterns in the data and quickly extract insights in order to automate tasks for a variety of business benefits. Machine learning, an AI technology, brings the ability to automatically identify patterns and detect anomalies in the data that smart sensors and devices generate, and it can have significant advantages over traditional business intelligence tools for analyzing IoT data, including being able to make operational predictions up to 20 times earlier and with greater accuracy than threshold-based monitoring systems. Further, other AI technologies, such as speech recognition and computer vision can help extract insights from data that used to require human review. The powerful combination of AI and IoT technology is helping to avoid unplanned downtime, increase operating efficiency, enable new products and services, and enhance risk management.

The book aims to provide a broad overview of various topics of the Internet of Things (IoT) from the research and development priorities to enabling technologies, architecture, security, privacy, interoperability and industrial applications. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC ? Internet of Things European Research Cluster from technology to international cooperation and the global state of play. The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level.Today we see the integration of Industrial, Business and Consumer Internet which is bringing together the Internet of People, Internet of Things, Internet of Energy, Internet of Vehicles, Internet of Media, Services and Enterprises in forming the backbone of the digital economy, the digital society and the foundation for the future knowledge and innovation based economy in supporting solutions for the emerging challenges of public health, aging population, environmental protection and climate change, the conservation of energy and scarce materials, enhancements to safety and security and the continuation and growth of economic prosperity.Penetration of smartphones and advances in machine to machine and wireless communication technology will be the main drivers for IoT development. The IoT contribution is in the increased value of information created by the number of interconnections among things and the transformation of the processed information into knowledge shared into the Internet of Everything.