It has been next to impossible in the past months not to come across the term ‘‘Internet of Things’’ (IoT) one way or another. Especially the past year has seen a tremendous surge of interest in the Internet of Things. Consortia have been formed to define frameworks and standards for the IoT. Companies have started to introduce numerous IoTbased products and services. And a number of IoT-related acquisitions have been making the headlines, including, e.g., the prominent takeover of Nest by Google for $3.2 billion and the subsequent acquisitions of Dropcam by Nest and of SmartThings by Samsung. Politicians as well as practitioners increasingly acknowledge the Internet of Things as a real business opportunity, and estimates currently suggest that the IoT could grow into a market worth $7.1 trillion by 2020 (IDC 2014). While the term Internet of Things is now more and more broadly used, there is no common definition or understanding today of what the IoT actually encompasses. The origins of the term date back more than 15 years and have been attributed to the work of the Auto-ID Labs at the Massachusetts Institute of Technology (MIT) on networked radio-frequency identification (RFID) infrastructures (Atzori et al. 2010; Mattern and Floerkemeier 2010). Since then, visions for the Internet of Things have been further developed and extended beyond the scope of RFID technologies. The International Telecommunication Union (ITU) for instance now defines the Internet of Things as ‘‘a global infrastructure for the Information Society, enabling advanced services by interconnecting (physical and virtual) things based on, existing and evolving, interoperable information and communication technologies’’ (ITU 2012). At the same time, a multitude of alternative definitions has been proposed. Some of these definitions exhibit an emphasis on the things which become connected in the IoT. Other definitions focus on Internet-related aspects of the IoT, such as Internet protocols and network technology. And a third type centers on semantic challenges in the IoT relating to, e.g., the storage, search and organization of large volumes of information (Atzori et al. 2010). The fields of application for IoT technologies are as numerous as they are diverse, as IoT solutions are increasingly extending to virtually all areas of everyday. The most prominent areas of application include, e.g., the smart industry, where the development of intelligent production systems and connected production sites is often discussed under the heading of Industry 4.0. In the smart home or building area, intelligent thermostats and security systems are receiving a lot of attention, while smart energy applications focus on smart electricity, gas and water meters. Smart transport solutions include, e.g., vehicle fleet tracking and mobile ticketing, while in the smart health area, topics such as patients’ surveillance and chronic disease management are being addressed. And in the context of Accepted after one revision by Prof. Dr. Sinz.

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Internet of Things - Technology and Value Added

The Internet of Things (IoT) makes smart objects the ultimate building blocks in the development of cyber-physical smart pervasive frameworks. The IoT has a variety of application domains, including health care. The IoT revolution is redesigning modern health care with promising technological, economic, and social prospects. This paper surveys advances in IoT-based health care technologies and reviews the state-of-the-art network architectures/platforms, applications, and industrial trends in IoT-based health care solutions. In addition, this paper analyzes distinct IoT security and privacy features, including security requirements, threat models, and attack taxonomies from the health care perspective. Further, this paper proposes an intelligent collaborative security model to minimize security risk; discusses how different innovations such as big data, ambient intelligence, and wearables can be leveraged in a health care context; addresses various IoT and eHealth policies and regulations across the world to determine how they can facilitate economies and societies in terms of sustainable development; and provides some avenues for future research on IoT-based health care based on a set of open issues and challenges.

The Internet of Things for Health Care: A Comprehensive Survey

The fourth industrial revolution, a term coined by Klaus Schwab, founder and executive chairman of the World Economic Forum, describes a world where individuals move between digital domains and offline reality with the use of connected technology to enable and manage their lives. (Miller 2015, 3) The first industrial revolution changed our lives and economy from an agrarian and handicraft economy to one dominated by industry and machine manufacturing. Oil and electricity facilitated mass production in the second industrial revolution. In the third industrial revolution, information technology was used to automate production. Although each industrial revolution is often considered a separate event, together they can be better understood as a series of events building upon innovations of the previous revolution and leading to more advanced forms of production. This article discusses the major features of the four industrial revolutions, the opportunities of the fourth industrial revolution, and the challenges of the fourth industrial revolution.

/pdf/the-fourth-industrial-revolution-opportunities-and-3msh3cuzqv.pdf

The Fourth Industrial Revolution: Opportunities and Challenges

The rise of low-cost sensing for managing air pollution in cities.

Smart grids are electric networks that employ advanced monitoring, control, and communication technologies to deliver reliable and secure energy supply, enhance operation efficiency for generators and distributors, and provide flexible choices for prosumers. Smart grids are a combination of complex physical network systems and cyber systems that face many technological challenges. In this paper, we will first present an overview of these challenges in the context of cyber–physical systems. We will then outline potential contributions that cyber–physical systems can make to smart grids, as well as the challenges that smart grids present to cyber–physical systems. Finally, implications of current technological advances to smart grids are outlined.

Smart Grids: A Cyber–Physical Systems Perspective

This book outlines the background and overall vision for the Internet of Things (IoT) and Machine-to-Machine (M2M) communications and services, including major standards. Key technologies are described, and include everything from physical instrumentation of devices to the cloud infrastructures used to collect data. Also included is how to derive information and knowledge, and how to integrate it into enterprise processes, as well as system architectures and regulatory requirements. Real-world service use case studies provide the hands-on knowledge needed to successfully develop and implement M2M and IoT technologies sustainably and profitably. Finally, the future vision for M2M technologies is described, including prospective changes in relevant standards. This book is written by experts in the technology and business aspects of Machine-to-Machine and Internet of Things, and who have experience in implementing solutions. Standards included: ETSI M2M, IEEE 802.15.4, 3GPP (GPRS, 3G, 4G), Bluetooth Low Energy/Smart, IETF 6LoWPAN, IETF CoAP, IETF RPL, Power Line Communication, Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE), ZigBee, 802.11, Broadband Forum TR-069, Open Mobile Alliance (OMA) Device Management (DM), ISA100.11a, WirelessHART, M-BUS, Wireless M-BUS, KNX, RFID, Object Management Group (OMG) Business Process Modelling Notation (BPMN)Key technologies for M2M and IoT covered: Embedded systems hardware and software, devices and gateways, capillary and M2M area networks, local and wide area networking, M2M Service Enablement, IoT data management and data warehousing, data analytics and big data, complex event processing and stream analytics, knowledge discovery and management, business process and enterprise integration, Software as a Service and cloud computing Combines both technical explanations together with design features of M2M/IoT and use cases. Together, these descriptions will assist you to develop solutions that will work in the real world Detailed description of the network architectures and technologies that form the basis of M2M and IoT Clear guidelines and examples of M2M and IoT use cases from real-world implementations such as Smart Grid, Smart Buildings, Smart Cities, Participatory Sensing, and Industrial Automation A description of the vision for M2M and its evolution towards IoT

From Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence

From machine-to-machine to the Internet of Things

Participatory Sensing (PS), also known as Urban, Citizen, or People-Centric Sensing, is a form of citizen engagement for the purpose of capturing the surrounding environment in a city as a first step for contributing to the solution of specific issues such as public health and well-being. Either citizens on their own initiative, or citizens organized through a specific campaign initiated by city authorities, collect sounds, pictures, videos, and other sensor data using their mobile phones as the main tool to monitor the environment and transfer the collected data to a storage space. The collected data are analyzed by citizens or city authorities, conclusions and action plans are drawn, and actions are taken. Although this form of engagement was typical a few years ago, nowadays the PS concept has been enriched to include active citizen journalists or passive social media sensing in the sense that citizen engagement to social media such as Twitter can also be used as additional input to PS campaigns.

Chapter 15 – Participatory Sensing

PART 1 THE EVOLVING IoT LANDSCAPE 1. Introduction 2. Origins and IoT Landscape 3. A Market Perspective 4. An Architectural Perspective PART 2 IoT TECHNOLOGIES AND ARCHITECTURES 5. Technology Fundamentals 6. Security 7. Trust, Identity and Privacy 8. Standards Architecture 9. IoT Architecture and State of the Art Reference Model 10. Real-World Design Constraints PART 3 USE CASES 11. Introduction to Use 12. Asset Management 13. Industrial Automation 14. The Smart Grid 15. Commercial Building Automation 16. Smart Cities 17. Participatory Sensing 18. Robotics 19. Autonomous Vehicles 20. Logistics 21. Conclusions and Looking Ahead Appendix A - Open source software implementations to use IoT

Internet of Things: Technologies and Applications for a New Age of Intelligence

Wireless sensor networking research has been mainly focused on internal wireless sensor network issues such as MAC and routing protocols, energy saving, HW design and to some extent on the architecture of gateways that connect a wireless sensor network with the rest of the world. Wireless sensor networks have been seen as dedicated to one task by one owner. On the other hand, our research is focused on integration of wireless sensor networks into existing networks, primarily mobile ones, and provision of sensor based and/or enhanced services to remote users. Therefore, we have been working on designing an architecture that utilizes the existing infrastructure to interconnect independent wireless sensor networks and to provide data aggregation and actuator control services. In the proposed architecture, sensor networks (small or large, deployed for any purpose and by anyone) represented by their gateways are treated as leaf nodes hanging off a mobile or fixed network that use these networks to interact with remote and local users. Each gateway exposes the capabilities of its sensors, actuators and the sensor network as a whole. This information is used by sensor services middleware to query/command sensor ecosystems on behalf of applications and remote users interested in sensor measurements or actuator control. The details of the interaction between the gateways and its sensors/actuators are of no interest to the remote users. Further, we consider the whole wireless sensor networking landscape as an open market where the underlying mobile and fixed networks facilitate the interaction between the sensor networks and the consumers of the information they produce. Each sensor network is first of all a sensor information provider that offers specific sensor information defined by the type of available sensors and their spatial and temporal conditions to the interested users. Secondly, each sensor network provides actuation services that may potentially affect the information gathered by its sensors. Obviously, in such an environment, where many mobile users are acting as tiny information providers, service discovery, service composition, service provisioning and service authorization are very challenging problems. These problems are addressed in the proposed architecture by introducing a middle layer that aggregates information from all small information providers and provides higher level services to the end users. This layer provides the means to quickly add or remove sensors, actuators, sensor networks, sensor network providers, to modify and enhance the existing or add completely new services utilizing the underlying infrastructure. It could be thought of as a "plug-and-play" functionality for: (a) interconnecting different existing sensor networks; (b) adding new sensor networks which facilitate the expansion of the entire system; and (c) expanding the capability of individual sensor networks.

Mobile Network Supported Wireless Sensor Network Services

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