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Computational Intelligence for Wireless Sensor Networks: Principles and Applications provides an integrative overview of the computational intelligence (CI) in wireless sensor networks and enabled technologies. It aims to demonstrate how the paradigm of computational intelligence can benefit Wireless Sensor Networks (WSNs) and sensor-enabled technologies to overcome their existing issues.This book provides extensive coverage of the multiple design challenges of WSNs and associated technologies such as clustering, routing, media access, security, mobility, and design of energy-efficient network operations.It also describes various CI strategies such as fuzzy computing, evolutionary computing, reinforcement learning, artificial intelligence, swarm intelligence, teaching learning-based optimization, etc. It also discusses applying the techniques mentioned above in wireless sensor networks and sensor-enabled technologies to improve their design.The book offers comprehensive coverage of related topics, including: Emergence of intelligence in wireless sensor networks Taxonomy of computational intelligence Detailed discussion of various metaheuristic techniques Development of intelligent MAC protocols Development of intelligent routing protocols Security management in WSNs This book mainly addresses the challenges pertaining to the development of intelligent network systems via computational intelligence. It provides insights into how intelligence has been pursued and can be further integrated in the development of sensor-enabled applications.

This book provides an understanding of the evolution of digitization in our day to day life and how it has become a part of our social system. The obvious challenges faced during this process and how these challenges were overcome have been discussed. The discussions revolve around the solutions to these challenges by leveraging the use of various advanced technologies. The book mainly covers the use of these technologies in variety of areas such as smart cities, healthcare informatics, transportation automation, digital transformation of education. The book intends to be treated as a source to provide the systematic discussion to the bouquet of areas that are essential part of digitized societies. In light of this, the book accommodates theoretical, methodological, well-established, and validated empirical work dealing with various related topics.

This book presents scientific and technological innovations and advancements already developed or under development in academia, industry, and research communities. It includes fundamental ideas and advancement in terahertz technology covering high intensity terahertz wave generation, THz detection, different modes of THz wave generation, THz modulation system, and terahertz propagation channel modeling. It highlights methodologies for the design of terahertz components and system technologies including emerging applications. The chapter contents are based on theoretical, methodological, well-established, and validated empirical work dealing with different topics in the terahertz domain. The book covers a very broad audience ranging from basic sciences to experts and learners in engineering and technology. It would be a good reference for advanced ideas and concepts in THz technology which will best suit microwave, biomedical, and electrical and communication engineers workingtowards next-generation technology.

This book highlights emerging trends in terahertz engineering and system technologies, mainly, devices, advanced materials, and various applications in THz technology. It includes advanced topics such as terahertz biomedical imaging, pattern recognition and tomographic reconstruction for THz biomedical imaging by use of machine learning and artificial intelligence, THz imaging radars for autonomous vehicle applications, THZ imaging system for security and surveillance. It also discusses theoretical, experimental, established and validated empirical work on these topics and the intended audience is both academic and professional.

This book addresses the challenges for developing and emerging trends in Internet-of-Things (IoT) for smart agriculture platforms. It also describes data analytics & machine learning, cloud architecture, automation & robotics and aims to overcome existing barriers for smart agriculture with commercial viability. It discusses IoT-based monitoring systems for analyzing the crop environment, and methods for improving the efficiency of decision-making based on the analysis of harvest statistics. The book explores a range of applications including intelligent field monitoring, intelligent data processing and sensor technologies, predictive analysis systems, crop monitoring, and weather data-enabled analysis in IoT agro-systems. This volume will be helpful for engineering and technology experts and researchers, as well as for policy-makers.