This multidisciplinary book provides insights into the applications of the Internet of Things (IoT) to combined sewer overflows (CSO) and stormwater management (SWM) systems. It explores technical challenges and presents recent results to improve sewer and drainage system management using wireless underground communications and sensing in IoT. The book addresses both existing sensing network technologies and those currently in development in three major areas of CSO: combined sewer overflow management, subsurface sensing, and antennas in the layered medium. It explores new applications of IoT in sewer systems to improve public health, foster economic growth, and enhance environmental quality and responsibility for the community. Internet of Things in Smart Sewer and Drainage Systems: Theory and Applications will be a valuable reference for graduate students and academic researchers, as well as a hands-on guide for wastewater technicians, sanitary engineers, environmental specialists, and related industry practitioners.

The main objective of this book is to provide a multidisciplinary overview of methodological approaches, architectures, platforms, and algorithms for the realization of an Internet of Things (IoT)-based Smart Urban Ecosystem (SUE). Moreover, the book details a set of real-world applications and case studies related to specific smart infrastructures and smart cities, including structural health monitoring, smart urban drainage networks, smart grids, power efficiency, healthcare, city security, and emergency management. A Smart Urban Ecosystem (SUE) is a people-centric system of systems that involves smart city environments, applications, and infrastructures. SUEs require the close integration of cyber and physical components for monitoring, understanding and controlling the urban environment. In this context, the Internet of Things (IoT) offers a valuable enabling technology, as it bridges the gap between physical things and software components, and empowers cooperation between distributed, pervasive, and heterogeneous entities.

The conference on ‘Interdisciplinary Research in Technology and Management” was a bold experiment in deviating from the traditional approach of conferences which focus on a specific topic or theme. By attempting to bring diverse inter-related topics on a common platform, the conference has sought to answer a long felt need and give a fillip to interdisciplinary research not only within the technology domain but across domains in the management field as well. The spectrum of topics covered in the research papers is too wide to be singled out for specific mention but it is noteworthy that these papers addressed many important and relevant concerns of the day.

This book presents the select proceedings of the International Conference on Recent Advances in Materials, Manufacturing and Thermal Engineering (RAMMTE 2022). It broadly covers the topics of manufacturing and thermal engineering. Various topics covered in this book include alternative fuels, automation, mechatronics and robotics, CAD, CAM, FMS, CIM, CN, CFD, failure and fracture mechanics, friction, wear, tribology, and surface engineering, heat treatment, microstructure and refrigeration and cryogenics, heating ventilation and air conditioning system, heat transfer, internal combustion engines, machinability and formability of materials, mechanisms and machines, rapid manufacturing technologies and prototyping, turbo machinery, thermal engineering, and traditional and non-traditional machining processes. This book is useful for researchers and professionals working in the areas of manufacturing and thermal engineering.

This book provides an investigative approach to how machine learning is helping to maintain and secure smart cities, including principal uses such as smart monitoring, privacy, reliability, and public protection. The authors cover important areas and issues around implementation roadblocks, ideas, and opportunities in smart city development. The authors also include new algorithms, architectures and platforms that can accelerate the growth of smart city concepts and applications. Moreover, this book provides details on specific applications and case studies related to smart city infrastructures, big data management, and prediction techniques using machine learning.

This book covers how Internet of Things (IoT) has a role in shaping the future of our communities. The author shows how the research and education ecosystem promoting impactful solutions-oriented science can help citizenry, government, industry, and other stakeholders to work collaboratively in order to make informed, socially-responsible, science-based decisions. Accordingly, he shows how communities can address complex, interconnected socio-environmental challenges. This book addresses the key inter-related challenges in areas such as the environment, climate change, mining, energy, agro-economic, water, and forestry that are limiting the development of a sustainable and resilient society -- each of these challenges are tied back to IoT based solutions. Presents research into sustainable IoT with respect to wireless communications, sensing, and systems Provides coverage of IoT technologies in sustainability, health, agriculture, climate change, mining, energy, water management, and forestry Relevant for academics, researchers, policy makers, city planners and managers, technicians, and industry professionals in IoT and sustainability

A smart city utilizes ICT technologies to improve the working effectiveness, share various data with the citizens, and enhance political assistance and societal wellbeing. The fundamental needs of a smart and sustainable city are utilizing smart technology for enhancing municipal activities, expanding monetary development, and improving citizens’ standards of living. The Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities discusses new mathematical models in smart and sustainable cities using big data, visualization tools in mathematical modeling, machine learning-based mathematical modeling, and more. It further delves into privacy and ethics in data analysis. Covering topics such as deep learning, optimization-based data science, and smart city automation, this premier reference source is an excellent resource for mathematicians, statisticians, computer scientists, civil engineers, government officials, students and educators of higher education, librarians, researchers, and academicians.