The pervasive application of Internet of Things (IoT) has been seen in many aspects in human daily life and industrial production. The concept of IoT originates from traditional machine-to-machine (M2M) communications which aimed at solving domain-specific and applicationspecific problems. Today, the rapid progress of communication technologies, the maturation of Internet infrastructures, the continuously reduced cost of sensors, and emergence of more open standards, have witnessed the approaching of the expected IoT era, which envisions full connectivity between the physical world and the digital world via the Internet protocol. The popularity of cloud computing technology has enhanced this IoT transform, benefiting from the superior computing capability and flexible data storage, let alone the security, reliability and scalability advantages. However, there are still a series of obstacles confronted by the industry in deployment of IoT services. First, due to the heterogeneity of hardware devices and application scenarios, the interoperability and compatibility between link-layer protocols, sub-systems and back-end services are significantly challenging. Second, the device management requires a uniform scheme to implement the commissioning, communication, authorization and identity management to guarantee security. Last, the heterogeneity of data format, speed and storage mechanism for different services pose a challenge to further data mining. This thesis aims to solve these aforementioned challenges by proposing a data-centric IoT framework based on public cloud platforms. It targets at providing a universal architecture to facilitate the deployment of IoT services in massive IoT and broadband IoT categories. The framework involves three representative communication protocols, namely WiFi, Thread and Lo-RaWAN, to enable support for local, personal, and wide area networks. A security assessment taxonomy for wireless communications in building automation networks is proposed as a tool to evaluate the security performance of adopted protocols, so as to mitigate potential network flaws and guarantee the security. Azure cloud platform is adopted in the framework to provide device management, data processing and storage, visualization, and intelligent services, thanks to the mature cloud infrastructure and the uniform device model and data model. We also exhibit the value of the study by applying the framework into the digitalization procedure of the green plant wall industry. Based on the framework, a remote monitoring and management system for green plant wall is developed as a showcase to validate the feasibility. Furthermore, three specialized visualization methods are proposed and a neuron network-based anomaly detection method is deployed in the project, showing the potential of the framework in terms of data analytics and intelligence.

Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process. Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful.

Data storage, processing, and management at remote location over dynamic networks is the most challenging task in cloud networks. Users’ expectations are very high for data accuracy, reliability, accessibility, and availability in pervasive cloud environment. It was the core motivation for the Cloud Networks Internet of Things (CNIoT). The exponential growth of the networks and data management in CNIoT must be implemented in fast growing service sectors such as logistic and enterprise management. The network based IoT works as a bridge to fill the gap between IT and cloud networks, where data is easily accessible and available. This book provides a framework for the next generation of cloud networks, which is the emerging part of 5G partnership projects. This contributed book has following salient features, A cloud-based next generation networking technologies. Cloud-based IoT and mobility management technology. The proposed book is a reference for research scholars and course supplement for cloud-IoT related subjects such as distributed networks in computer/ electrical engineering. Sanjay Kumar Biswash is working as an Assistant professor in NIIT University, India. He held Research Scientist position, Institute of Cybernetics, National Research Tomsk Polytechnic University, Russia. He was PDF at LNCC, Brazil and SDSU, USA. He was a visiting researcher to the UC, Portugal. Sourav Kanti Addya is working as an Assistant professor in NITK, Surathkal, India. He was a PDF at IIT Kharagpur, India. He was a visiting scholar at SDSU, USA. He obtained national level GATE scholarship. He is a member of IEEE, ACM.

This book comprehensively discusses the role of cloud computing in artificial intelligence‐based data‐driven systems and hybrid cloud computing for large data‐driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data. The text provides Internet of Things‐based frameworks and advanced computing techniques to deal with online/virtual systems. This book: • Covers the aspects of security, authentication, and prediction for data‐driven systems in heterogeneous environments. • Provides data‐driven frameworks in combination with the Internet of Things, artificial intelligence, and computing to provide critical insights and decision‐making for real‐time problems. • Showcases deep learning‐based computer vision algorithms for enhanced pattern detection in different domains based on data‐centric approaches. • Examines the role of the Internet of Things and machine learning algorithms for data‐driven systems. • Highlights the applications of data‐driven systems and cloud computing in enhancing network performance. This book is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, and computer science engineering.

This book comprises the proceedings of the International Conference on Intelligent Systems and Applications (ICISA 2022). The contents of this volume focus on novel and modified artificial intelligence and machine learning-based methods and their applications in robotics, pharmaceutics, banking & finance, agriculture, food processing, crime prevention, smart homes, transportation, traffic control, and wildlife conservation, etc. This volume will prove a valuable resource for those in academia and industry.

Data storage, processing, and management at remote location over dynamic networks is the most challenging task in cloud networks. Users’ expectations are very high for data accuracy, reliability, accessibility, and availability in pervasive cloud environment. It was the core motivation for the Cloud Networks Internet of Things (CNIoT). The exponential growth of the networks and data management in CNIoT must be implemented in fast growing service sectors such as logistic and enterprise management. The network based IoT works as a bridge to fill the gap between IT and cloud networks, where data is easily accessible and available. This book provides a framework for the next generation of cloud networks, which is the emerging part of 5G partnership projects. This contributed book has following salient features, A cloud-based next generation networking technologies. Cloud-based IoT and mobility management technology. The proposed book is a reference for research scholars and course supplement for cloud-IoT related subjects such as distributed networks in computer/ electrical engineering. Sanjay Kumar Biswash is working as an Assistant professor in NIIT University, India. He held Research Scientist position, Institute of Cybernetics, National Research Tomsk Polytechnic University, Russia. He was PDF at LNCC, Brazil and SDSU, USA. He was a visiting researcher to the UC, Portugal. Sourav Kanti Addya is working as an Assistant professor in NITK, Surathkal, India. He was a PDF at IIT Kharagpur, India. He was a visiting scholar at SDSU, USA. He obtained national level GATE scholarship. He is a member of IEEE, ACM.

The ubiquity of modern technologies has allowed for increased connectivity between people and devices across the globe. This connected infrastructure of networks creates numerous opportunities for applications and uses. The Internet of Things: Breakthroughs in Research and Practice is an authoritative reference source for the latest academic material on the interconnectivity of networks and devices in the digital era and examines best practices for integrating this advanced connectivity across multiple fields. Featuring extensive coverage on innovative perspectives, such as secure computing, regulatory standards, and trust management, this book is ideally designed for engineers, researchers, professionals, graduate students, and practitioners seeking scholarly insights on the Internet of Things.