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This book presents smart energy management in the context of energy transition. It presents the motivation, impacts and challenges related to this hot topic. Then, it focuses on the use of techniques and tools based on artificial intelligence (AI) to solve the challenges related to this problem. A global diagram presenting the general principle of these techniques is presented. Then, these techniques are compared according to a set of criteria in order to show their advantages and disadvantages with respect to the conditions and constraints of intelligent energy management applications in the context of energy transition. Several examples are used throughout the white paper to illustrate the concepts and methods presented. An intelligent electrical network (smart grid—SG) includes heterogeneous and distributed electricity production, transmission, distribution and consumption components. It is the next generation of electricity network able to manage electricity demand (consumption/production/distribution) in a sustainable, reliable and economical way taking into account the penetration of renewable energies (solar, wind, etc.). Therefore, a (SG) smart grid also includes an intelligent layer that analyzes the data provided by consumers as well as that collected from the production side in order to optimize consumption and production according to weather conditions, the profile and habits of the consumer. In addition, this system can improve the use of green energy through renewable energy penetration and demand response.
As the application of smart technologies for monitoring environmental activities becomes more widespread, there is a growing demand for solutions that can help analyze the risk factors and impacts on the environment by focusing on energy consumption, storage, and management. This book is designed to serve as a knowledge-sharing platform, focusing on the emerging models, architectures, and algorithms being developed for smart computational technologies that can lead to efficient energy conservation and environmental sustainability.
#1 NEW YORK TIMES BEST SELLER • In this urgent, authoritative book, Bill Gates sets out a wide-ranging, practical—and accessible—plan for how the world can get to zero greenhouse gas emissions in time to avoid a climate catastrophe. Bill Gates has spent a decade investigating the causes and effects of climate change. With the help of experts in the fields of physics, chemistry, biology, engineering, political science, and finance, he has focused on what must be done in order to stop the planet's slide to certain environmental disaster. In this book, he not only explains why we need to work toward net-zero emissions of greenhouse gases, but also details what we need to do to achieve this profoundly important goal. He gives us a clear-eyed description of the challenges we face. Drawing on his understanding of innovation and what it takes to get new ideas into the market, he describes the areas in which technology is already helping to reduce emissions, where and how the current technology can be made to function more effectively, where breakthrough technologies are needed, and who is working on these essential innovations. Finally, he lays out a concrete, practical plan for achieving the goal of zero emissions—suggesting not only policies that governments should adopt, but what we as individuals can do to keep our government, our employers, and ourselves accountable in this crucial enterprise. As Bill Gates makes clear, achieving zero emissions will not be simple or easy to do, but if we follow the plan he sets out here, it is a goal firmly within our reach.
This book discusses the design and practice of environmental resources management for smart cities. Presenting numerous city case studies, it focuses on one specific environmental resource in each city. Environmental resources are commonly owned properties that require active inputs from the government and the people, and in any smart city their management calls for a synchronous combination of e-democracy, e-governance and IOT (Internet of Things) systems in a 24/7 framework. Smart environmental resources management uses information and communication technologies, the Internet of Things, internet of governance (e-governance) and internet of people (e-democracy) along with conventional resource management tools to achieve coordinated, effective and efficient management, development, and conservation that equitably improves ecological and economic welfare, without compromising the sustainability of development ecosystems and stakeholders.
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.
The world faces escalating environmental and healthcare challenges, from climate change to managing natural resources and providing efficient medical services. These issues are complex, often requiring intricate modeling and intervention from domain experts. Traditional analytical methods need help to cope with the complexity and scale of these challenges, leading to inefficiencies and suboptimal outcomes. There is a pressing need for innovative solutions that can enhance our ability to address these issues effectively. Advancements in Climate and Smart Environment Technology present a compelling solution to these pressing problems. By leveraging the power of artificial intelligence (AI) techniques, we offer a path toward more efficient and effective solutions in environmental engineering, healthcare management, and natural resource conservation. AI provides the tools to model complex systems, optimize processes, and make informed decisions without constant expert intervention, thus revolutionizing these fields. This book is a comprehensive guide for scholars, researchers, and practitioners in various fields related to environmental and healthcare sciences. It explores the applications of AI in areas such as innovative environments, sustainable agriculture, climate change mitigation, and healthcare delivery.
Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.