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| cloud-based battery management system: Advanced Battery Management System for Electric Vehicles Shichun Yang, Xinhua Liu, Shen Li, Cheng Zhang, 2022-09-19 The battery management system (BMS) optimizes the efficiency of batteries under allowable conditions and prevents serious failure modes. This book focuses on critical BMS techniques, such as battery modeling; estimation methods for state of charge, state of power and state of health; battery charging strategies; active and passive balancing methods; and thermal management strategies during the entire lifecycle. It also introduces functional safety and security-related design for BMS, and discusses potential future technologies, like digital twin technology. |
| cloud-based battery management system: Battery Management Systems Valer Pop, Henk Jan Bergveld, Dmitry Danilov, Paul P. L. Regtien, Peter H. L. Notten, 2008-05-28 This book describes the field of State-of-Charge (SoC) indication for rechargeable batteries. An overview of the state-of-the-art of SoC indication methods including available market solutions from leading semiconductor companies is provided. All disciplines are covered, from electrical, chemical, mathematical and measurement engineering to understanding battery behavior. This book will therefore is for persons in engineering and involved in battery management. |
| cloud-based battery management system: IoT based Battery Management System using Solar Energy V Suma Deepthi , |
| cloud-based battery management system: Battery Management System and its Applications Xiaojun Tan, Andrea Vezzini, Yuqian Fan, Neeta Khare, You Xu, Liangliang Wei, 2022-11-29 BATTERY MANAGEMENT SYSTEM AND ITS APPLICATIONS Enables readers to understand basic concepts, design, and implementation of battery management systems Battery Management System and its Applications is an all-in-one guide to basic concepts, design, and applications of battery management systems (BMS), featuring industrially relevant case studies with detailed analysis, and providing clear, concise descriptions of performance testing, battery modeling, functions, and topologies of BMS. In Battery Management System and its Applications, readers can expect to find information on: Core and basic concepts of BMS, to help readers establish a foundation of relevant knowledge before more advanced concepts are introduced Performance testing and battery modeling, to help readers fully understand Lithium-ion batteries Basic functions and topologies of BMS, with the aim of guiding readers to design simple BMS themselves Some advanced functions of BMS, drawing from the research achievements of the authors, who have significant experience in cross-industry research Featuring detailed case studies and industrial applications, Battery Management System and its Applications is a must-have resource for researchers and professionals working in energy technologies and power electronics, along with advanced undergraduate/postgraduate students majoring in vehicle engineering, power electronics, and automatic control. |
| cloud-based battery management system: Battery Management Algorithm for Electric Vehicles Rui Xiong, 2019-09-23 This book systematically introduces readers to the core algorithms of battery management system (BMS) for electric vehicles. These algorithms cover most of the technical bottlenecks encountered in BMS applications, including battery system modeling, state of charge (SOC) and state of health (SOH) estimation, state of power (SOP) estimation, remaining useful life (RUL) prediction, heating at low temperature, and optimization of charging. The book not only presents these algorithms, but also discusses their background, as well as related experimental and hardware developments. The concise figures and program codes provided make the calculation process easy to follow and apply, while the results obtained are presented in a comparative way, allowing readers to intuitively grasp the characteristics of different algorithms. Given its scope, the book is intended for researchers, senior undergraduate and graduate students, as well as engineers in the fields of electric vehicles and energy storage. |
| cloud-based battery management system: ICCAP 2021 A Mohan, D. S. Vijayan, 2021-12-22 This proceeding constitutes the thoroughly refereed proceedings of the 1st International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8, 2021. This event was organized by the group of Professors in Chennai. The Conference aims to provide the opportunities for informal conversations, have proven to be of great interest to other scientists and analysts employing these mathematical sciences in their professional work in business, industry, and government. The Conference continues to promote better understanding of the roles of modern applied mathematics, combinatorics, and computer science to acquaint the investigator in each of these areas with the various techniques and algorithms which are available to assist in his or her research. We selected 257 papers were carefully reviewed and selected from 741 submissions. The presentations covered multiple research fields like Computer Science, Artificial Intelligence, internet technology, smart health care etc., brought the discussion on how to shape optimization methods around human and social needs. |
| cloud-based battery management system: Advanced Battery Management Technologies for Electric Vehicles Rui Xiong, Weixiang Shen, 2019-02-26 A comprehensive examination of advanced battery management technologies and practices in modern electric vehicles Policies surrounding energy sustainability and environmental impact have become of increasing interest to governments, industries, and the general public worldwide. Policies embracing strategies that reduce fossil fuel dependency and greenhouse gas emissions have driven the widespread adoption of electric vehicles (EVs), including hybrid electric vehicles (HEVs), pure electric vehicles (PEVs) and plug-in electric vehicles (PHEVs). Battery management systems (BMSs) are crucial components of such vehicles, protecting a battery system from operating outside its Safe Operating Area (SOA), monitoring its working conditions, calculating and reporting its states, and charging and balancing the battery system. Advanced Battery Management Technologies for Electric Vehicles is a compilation of contemporary model-based state estimation methods and battery charging and balancing techniques, providing readers with practical knowledge of both fundamental concepts and practical applications. This timely and highly-relevant text covers essential areas such as battery modeling and battery state of charge, energy, health and power estimation methods. Clear and accurate background information, relevant case studies, chapter summaries, and reference citations help readers to fully comprehend each topic in a practical context. Offers up-to-date coverage of modern battery management technology and practice Provides case studies of real-world engineering applications Guides readers from electric vehicle fundamentals to advanced battery management topics Includes chapter introductions and summaries, case studies, and color charts, graphs, and illustrations Suitable for advanced undergraduate and graduate coursework, Advanced Battery Management Technologies for Electric Vehicles is equally valuable as a reference for professional researchers and engineers. |
| cloud-based battery management system: Innovations in Energy Management and Renewable Resources Madhumita Pal, |
| cloud-based battery management system: Computing, Internet of Things and Data Analytics Fausto Pedro García Márquez, |
| cloud-based battery management system: Innovation and Competitiveness in Industry 4.0 Based on Intelligent Systems Luis Carlos Méndez-González, Luis Alberto Rodríguez-Picón, Iván Juan Carlos Pérez Olguín, 2023-06-16 This book presents a series of applications of different techniques found in Industry 4.0 with relation to productivity, continuous improvement, quality, decision systems, software development, and automation systems. The techniques used throughout this book allow the reader to replicate the results obtained towards different types of companies that wish to undertake in the new era of the digital industrial revolution. This book can also help students from different areas of engineering to understand how the use of new technologies is applied to solve current relevant problems and how they give the possibility of constant innovation in the different industrial sectors. This is accomplished through the analysis of illustrative case studies, descriptive methodologies and structured insights that are provided through the different considered techniques. |
| cloud-based battery management system: Encyclopedia of Machine Learning Claude Sammut, Geoffrey I. Webb, 2011-03-28 This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references. |
| cloud-based battery management system: Soft Computing for Security Applications G. Ranganathan, Xavier Fernando, Fuqian Shi, Youssouf El Allioui, 2021-10-25 This book features selected papers from the International Conference on Soft Computing for Security Applications (ICSCS 2021), held at Dhirajlal Gandhi College of Technology, Tamil Nadu, India, during June 2021. It covers recent advances in the field of soft computing techniques such as fuzzy logic, neural network, support vector machines, evolutionary computation, machine learning and probabilistic reasoning to solve various real-time challenges. The book presents innovative work by leading academics, researchers, and experts from industry. |
| cloud-based battery management system: Smart Battery Management for Enhanced Safety Zhongbao Wei, |
| cloud-based battery management system: Artificial Intelligence Applications in Battery Management Systems and Routing Problems in Electric Vehicles Angalaeswari, S., Deepa, T., Kumar, L. Ashok, 2023-02-10 In today’s modern society, to reduce the carbon dioxide gas emission from motor vehicles and to save mother nature, electric vehicles are becoming more practical. As more people begin to see the benefits of this technology, further study on the challenges and best practices is required. Artificial Intelligence Applications in Battery Management Systems and Routing Problems in Electric Vehicles focuses on the integration of renewable energy sources with the existing grid, introduces a power exchange scenario in the prevailing power market, considers the use of the electric vehicle market for creating cleaner and transformative energy, and optimizes the control variables with artificial intelligence techniques. Covering key topics such as artificial intelligence, smart grids, and sustainable development, this premier reference source is ideal for government officials, industry professionals, policymakers, researchers, scholars, practitioners, academicians, instructors, and students. |
| cloud-based battery management system: Sustainable Science and Intelligent Technologies for Societal Development Mishra, Brojo Kishore, 2023-09-18 In today's world, the pressing challenges of sustainable development and societal progress demand innovative solutions that harness the power of science and technology. From climate change to resource depletion and social inequalities, the urgency to find sustainable, intelligent, and ethical approaches has never been greater. Academic scholars and researchers play a crucial role in driving these advancements but often struggle to find comprehensive resources that bridge the gap between theory and real-world applications. The need of the hour is a definitive guide that unites expertise from diverse disciplines and offers practical insights into leveraging sustainable science and intelligent technologies to create meaningful societal development. Sustainable Science and Intelligent Technologies for Societal Development, edited by Brojo Kishore Mishra of GIET University, India, is the much-awaited solution to the challenges faced by academic scholars and researchers. This persuasive book brings together an esteemed collection of leading experts, academics, and industry professionals, all dedicated to addressing global challenges through the lens of applied sciences and intelligent technology applications. By presenting a wide range of innovative topics, such as renewable energy, smart healthcare, sustainable finance, and more, the book serves as a comprehensive resource that empowers scholars with actionable knowledge and innovative ideas. The book not only covers the theoretical aspects but also delves into the ethical considerations essential in shaping the future. In a world increasingly dependent on technology, it is vital to ensure that societal development aligns with principles of inclusivity, fairness, and environmental responsibility. With a focus on the United Nations Sustainable Development Goals (SDGs), the book provides a clear roadmap for scholars to contribute meaningfully to global progress. By offering concrete examples and real-world case studies, the book enables researchers to grasp the potential impact of their work, fostering collaborations that transcend traditional disciplinary boundaries. Sustainable Science and Intelligent Technologies for Societal Development is the go-to resource for academic scholars, scientists, researchers, innovators, industry professionals, and students who seek to be effective in the world. As a comprehensive guide that blends sustainable science and intelligent technologies with ethical considerations, this book equips its readers to create tangible solutions that address pressing global challenges. Through collective knowledge and interdisciplinary collaboration, this book stands as a beacon of hope and inspiration for driving meaningful societal development, paving the way for a more sustainable and prosperous future. |
| cloud-based battery management system: 19. Internationales Stuttgarter Symposium Michael Bargende, Hans-Christian Reuss, Andreas Wagner, Jochen Wiedemann, 2019-05-24 In einer sich rasant verändernden Welt sieht sich die Automobilindustrie fast täglichmit neuen Herausforderungen konfrontiert: Der problematischer werdende Rufdes Dieselmotors, verunsicherte Verbraucher durch die in der Berichterstattungvermischte Thematik der Stickoxid- und Feinstaubemissionen, zunehmendeKonkurrenz bei Elektroantrieben durch neue Wettbewerber, die immer schwierigerwerdende öffentlichkeitswirksame Darstellung, dass ein großer Unterschiedzwischen Prototypen, Kleinserien und einer wirklichen Großserienproduktion besteht.Dazu kommen noch die Fragen, wann die mit viel finanziellem Einsatz entwickeltenalternativen Antriebsformen tatsächlich einen Return of Invest erbringen, wer dienotwendige Ladeinfrastruktur für eine Massenmarkttauglichkeit der Elektromobilitätbauen und finanzieren wird und wie sich das alles auf die Arbeitsplätzeauswirken wird.Für die Automobilindustrie ist es jetzt wichtiger denn je, sich den Herausforderungenaktiv zu stellen und innovative Lösungen unter Beibehaltung des hohenQualitätsanspruchs der OEMs in Serie zu bringen. Die Hauptthemen sind hierbei,die Elektromobilität mit höheren Energiedichten und niedrigeren Kosten der Batterienvoranzutreiben und eine wirklich ausreichende standardisierte und zukunftssichereLadeinfrastruktur darzustellen, aber auch den Entwicklungspfad zum schadstofffreienund CO2-neutralen Verbrennungsmotor konsequent weiter zu gehen. Auch dasautomatisierte Fahren kann hier hilfreich sein, weil das Fahrzeugverhalten dann –im wahrsten Sinne des Wortes - kalkulierbarer wird.Dabei ist es für die etablierten Automobilhersteller strukturell nicht immer einfach,mit der rasanten Veränderungsgeschwindigkeit mitzuhalten. Hier haben Start-upseinen großen Vorteil:Ihre Organisationsstruktur erlaubt es, frische, unkonventionelleIdeen zügig umzusetzen und sehr flexibel zu reagieren. Schon heute werdenStart-ups gezielt gefördert, um neue Lösungen im Bereich von Komfort, Sicherheit,Effizienz und neuen Kundenschnittstellen zu finden. Neue Lösungsansätze,gepaart mit Investitionskraft und Erfahrungen, bieten neue Chancen auf dem Weg derElektromobilität, der Zukunft des Verbrennungsmotors und ganz allgemein für dasAuto der Zukunft. |
| cloud-based battery management system: Smart Electric and Hybrid Vehicles Arif I. Sarwat, Mohd Tariq, 2025-02-05 Thorough reference on technologies, designs, and strategies for electric and hybrid electric vehicles, featuring contributions from international experts Designed for readers who need to review different types of electric and hybrid vehicle designs and strategies in a single book, Smart Electric and Hybrid Vehicles: Advancements in Materials, Design, Technologies, and Modeling provides a broad overview of the field with additional resources to explore individual topics in greater depth. Abstracts, case studies, references to key data, and relevant numerical simulations are included throughout the text to aid in reader comprehension. This book introduces the global landscape of hybrid and electric vehicles, covering the available technologies from both a mechanical and electrical engineering perspective, presenting mathematical aspects of modeling and analysis, and surveying emerging trends and economic impacts. It also explains all fundamentals, regulations, policies, perceptions, and market competition aspects of intelligent electric vehicles, as well as how smart electric and hybrid vehicles can be utilized to reduce harmful emissions and reliance on fossil fuels over the lifecycle of a vehicle. Edited by a team of highly qualified academics, with contributions by an array of international experts, Smart Electric and Hybrid Vehicles: Advancements in Materials, Design, Technologies, and Modeling includes information on: Electric machine and inverter designs, maximum speed considerations, component cooling, power density, and material performance Battery systems, fuel cells, plug-in vehicles, mechanical drives and storage systems, and the role of power electronics tools The impact of trends and technologies like AI, machine vision, and digital twins, as well as related cyber security considerations Optimization of manufacturing waste, charging stations, sensing control, road trajectory prediction, and navigation systems Electrical interfaces to protect against electric shock and cost effectiveness compared to gasoline-powered vehicles Smart Electric and Hybrid Vehicles: Advancements in Materials, Design, Technologies, and Modeling is an essential reference on the subject for mechanical engineers, industrial engineers, and academic researchers working in the automotive sector. It is also an ideal learning resource for post-graduate students in the automotive field. |
| cloud-based battery management system: State Estimation Strategies in Lithium-ion Battery Management Systems Kailong Liu, Yujie Wang, Daniel-Ioan Stroe, Carlos Fernandez, Josep M. Guerrero, Shunli Wang, 2023-07-14 State Estimation Strategies in Lithium-ion Battery Management Systems presents key technologies and methodologies in modeling and monitoring charge, energy, power and health of lithium-ion batteries. Sections introduce core state parameters of the lithium-ion battery, reviewing existing research and the significance of the prediction of core state parameters of the lithium-ion battery and analyzing the advantages and disadvantages of prediction methods of core state parameters. Characteristic analysis and aging characteristics are then discussed. Subsequent chapters elaborate, in detail, on modeling and parameter identification methods and advanced estimation techniques in different application scenarios. Offering a systematic approach supported by examples, process diagrams, flowcharts, algorithms, and other visual elements, this book is of interest to researchers, advanced students and scientists in energy storage, control, automation, electrical engineering, power systems, materials science and chemical engineering, as well as to engineers, R&D professionals, and other industry personnel. - Introduces lithium-ion batteries, characteristics and core state parameters - Examines battery equivalent modeling and provides advanced methods for battery state estimation - Analyzes current technology and future opportunities |
| cloud-based battery management system: Neural Network-Based State-of-Charge and State-of-Health Estimation Qi Huang, Shunli Wang, Yujie Wang, Chao Wang, Carlos Fernandez, Josep M. Guerrero, 2023-11-16 To deal with environmental deterioration and energy crises, developing clean and sustainable energy resources has become the strategic goal of the majority of countries in the global community. Lithium-ion batteries are the modes of power and energy storage in the new energy industry, and are also the main power source of new energy vehicles. State-of-charge (SOC) and state-of-health (SOH) are important indicators to measure whether a battery management system (BMS) is safe and effective. Therefore, this book focuses on the co-estimation strategies of SOC and SOH for power lithium-ion batteries. The book describes the key technologies of lithium-ion batteries in SOC and SOH monitoring and proposes a collaborative optimization estimation strategy based on neural networks (NN), which provide technical references for the design and application of a lithium-ion battery power management system. The theoretical methods in this book will be of interest to scholars and engineers engaged in the field of battery management system research. |
| cloud-based battery management system: Harnessing High-Performance Computing and AI for Environmental Sustainability Naim, Arshi, 2024-05-15 The world is addressing the insistent challenge of climate change, and the need for innovative solutions has become paramount. In this period of technical developments, artificial intelligence (AI) has emerged as a powerful instrument with enormous prospects to combat climate change and other environmental subjects. AI's ability to process vast amounts of data, identify patterns, and make intelligent predictions offers unprecedented opportunities to tackle this global crisis. High-Performance Computing (HPC) or super-computing environments address these large and complex challenges with individual nodes (computers) working together in a cluster (connected group) to perform massive amounts of computing in a short period. Creating and removing these clusters is often automated in the cloud to reduce costs. Computer networks, communication systems, and other IT infrastructures have a growing environmental footprint due to significant energy consumption and greenhouse gas emissions. To address this seemingly self-defeating conundrum, and create a truly sustainable environment, new energy models, algorithms, methodologies, platforms, tools, and systems are required to support next-generation computing and communication infrastructures. Harnessing High-Performance Computing and AI for Environmental Sustainability navigates through AI-driven solutions from sustainable agriculture and land management to energy optimization and smart grids. It unveils how AI algorithms can analyze colossal datasets, offering unprecedented insights into climate modeling, weather prediction, and long-term climate trends. Integrating AI-powered optimization algorithms revolutionizes energy systems, propelling the transition towards a low-carbon future by reducing greenhouse gas emissions and enhancing efficiency. This book is ideal for educators, environmentalists, industry professionals, and researchers alike, and it explores the ethical dimensions and policies surrounding AI's contribution to environmental development. |
| cloud-based battery management system: Intelligent Interactions and Knowledge Discovery in Future Based Advance Computing Anand Rajavat, A.S. Rathore, Sachin Chirgaiya, 2023-10-23 Human society is ushering into an intelligent society from an information society, in which computing has become a key element in formulating and promoting the development of society. In the new era of digital civilization with the internet of all things, traditional computing on data is far from being able to meet the growing endevour for a higher level of intelligence by humans. The growing interest in intelligent computing, coupled with the development of computing science, the intelligent perception of the physical world, and the understanding of the cognitive mechanism of human consciousness, has collectively elevated the intelligence level of computing and accelerated the discovery and creation of knowledge. Intelligent computing is task-oriented; it matches computing resources and realizes automatic demand calculation and precise system reconstruction. The system architecture is constantly adjusted to the task execution. Directed coupling reconstruction is performed at the software and hardware levels. Automation of the computing process includes automatic resource management and scheduling, automatic service creation and provision, and automatic management of the task life cycle, which is the key to evaluating the friendliness, availability, and service of intelligent computing. The precision of computing results anchors computing services; besides, it solves difficulties, including fast processing of computing tasks and timely matching of computing resources. The book is collection of selected papers accepted for presentation during Avdharan-2023. The objective is to highlight the research pursued by scholars these days in India. It is likely that these researches may give insight for future research and fraternity of researchers is benefitted. |
| cloud-based battery management system: Future of Digital Technology and AI in Social Sectors Ertu?rul, Duygu Çelik, Elçi, Atilla, 2024-10-11 In a rapidly evolving digital landscape, integrating emerging technologies presents unprecedented opportunities and complex challenges across various disciplines. As society navigates this transformation, there is a growing need for comprehensive insights into the implications of these advancements. This book serves as a vital resource, offering a multidimensional exploration of how emerging technologies are reshaping the social sciences, education, law and policy, tourism, health, environment, communication, business and management, and security. Focusing on the intersection of technology and society, the Future of Digital Technology and AI in Social Sectors addresses pressing issues such as ethical dilemmas in technological advancement, the impact of automation on employment, and the moral and legal challenges of AI and data analytics. By providing a platform for researchers and practitioners to delve into these topics, the book aims to foster a deeper understanding of emerging technologies' implications and opportunities across diverse fields. |
| cloud-based battery management system: Intelligent Solutions for Sustainable Power Grids Ashok Kumar, L., Angalaeswari, S., Mohana Sundaram, K., Bansal, Ramesh C., Patil, Arunkumar, 2024-05-01 In the environment of energy systems, the effective utilization of both conventional and renewable sources poses a major challenge. The integration of microgrid systems, crucial for harnessing energy from distributed sources, demands intricate solutions due to the inherent intermittency of these sources. Academic scholars engaged in power system research find themselves at the forefront of addressing issues such as energy source estimation, coordination in dynamic environments, and the effective utilization of artificial intelligence (AI) techniques. Intelligent Solutions for Sustainable Power Grids focuses on emerging research areas, this book addresses the uncertainty of renewable energy sources, employs state-of-the-art forecasting techniques, and explores the application of AI techniques for enhanced power system operations. From economic aspects to the digitalization of power systems, the book provides a holistic approach. Tailored for undergraduate and postgraduate students as well as seasoned researchers, it offers a roadmap to navigate the intricate landscape of modern power systems. Dive into a wealth of knowledge encompassing smart energy systems, renewable energy integration, stability analysis of microgrids, power quality enhancement, and much more. This book is not just a guide; it is the solution to the pressing challenges in the dynamic field of energy systems. |
| cloud-based battery management system: Semantic Web Technologies and Applications in Artificial Intelligence of Things Ortiz-Rodriguez, Fernando, Leyva-Mederos, Amed, Tiwari, Sanju, Hernandez-Quintana, Ania R., Martinez-Rodriguez, Jose L., 2024-05-16 The confluence of Artificial Intelligence of Things (AIoT) and Semantic Web technologies is nothing short of revolutionary. The profound impact of this synergy extends far beyond the realms of industry, research, and society; it shapes the very fabric of our future. Semantic Web Technologies and Applications in Artificial Intelligence of Things is a meticulously crafted reference that not only acknowledges this significance but also serves as a guide for those navigating the complexities of Industry 4.0 and AIoT. This curated compendium of cutting-edge technologies acts as a veritable knowledge base for future developments. As academics, scholars, and industry professionals, the ideal audience of this book, will find meticulously curated content that caters to their diverse interests and expertise, covering topics ranging from smart agriculture, manufacturing, industry, health sciences, and government. Seasoned academics, students, and visionary industry leaders, will find this book to be an indispensable guide that paves the way for innovation and progress. |
| cloud-based battery management system: The Convergence of Self-Sustaining Systems With AI and IoT Rajappan, Roopa Chandrika, Gowri Ganesh, N.S., Daniel, J. Alfred, Ahmad, Awais, Santhosh, R., 2024-04-26 Picture a world where autonomous systems operate continuously and intelligently, utilizing real-time data to make informed decisions. Such systems have the potential to revolutionize agriculture, urban infrastructure, and industrial automation. This transformation, often termed the Internet of Self-Sustaining Systems (IoSS), is a pivotal topic that demands academic attention and exploration. Addressing this critical issue head-on is The Convergence of Self-Sustaining Systems With AI and IoT, which offers an in-depth examination of this transformative convergence. It serves as a guiding light for academic scholars seeking to unravel the vast potential of self-sustaining systems coupled with AI and IoT. Inside its pages, readers will delve into AI-driven autonomous agriculture, eco-friendly transportation solutions, and intelligent energy management. Moreover, the book explores emerging technologies, security concerns, ethical considerations, and governance frameworks. Join us on this intellectual journey and position yourself at the forefront of the AI and IoT revolution that promises a sustainable, autonomous future. |
| cloud-based battery management system: Improving Security, Privacy, and Trust in Cloud Computing Goel, Pawan Kumar, Pandey, Hari Mohan, Singhal, Amit, Agarwal, Sanyam, 2024-02-02 Cloud computing adoption has revolutionized how businesses and individuals harness the power of technology. The cloud's scalability, accessibility, and cost-efficiency have propelled it to the forefront of modern computing paradigms. However, as organizations increasingly rely on cloud services to store, process, and manage their data and applications, an intricate web of challenges has emerged, casting shadows over the very foundations of cloud computing. Improving Security, Privacy, and Trust in Cloud Computing unravels the complexities surrounding the cloud landscape, delving into the core concerns of security, privacy, and trust that have come to define its evolution. It aims to equip readers with the insights, knowledge, and practical strategies needed to navigate the intricate realm of cloud computing while safeguarding their most valuable assets. This book's exploration into security, privacy, and trust in cloud computing takes a holistic approach. Throughout the chapters of this book, readers will embark on a multidimensional expedition. This book will take them through real-world case studies of successful cloud security implementations and unfortunate breaches that underscore the urgency of robust defenses. From data encryption techniques to incident response protocols, this book offers practical insights and actionable strategies that can be implemented by IT professionals, security experts, and decision-makers alike. |
| cloud-based battery management system: Engineering Trustworthy Software Systems Jonathan P. Bowen, Zhiming Liu, Zili Zhang, 2020-07-31 This book constitutes the refereed proceedings of the 5th International School on Engineering Trustworthy Software Systems, SETSS 2019, held in Chongqing, China, in April 2019. The five chapters in this volume provide lectures on leading-edge research in methods and tools for use in computer system engineering. The topics covered in these chapter include Seamless Model-based System Development: Foundations; From Bounded Reachability Analysis of Linear Hybrid Automata to Verification of Industrial CPS and IoT; Weakest Preexpectation Semantics for Bayesian Inference: Conditioning, Continuous Distributions and Divergence; K – A Semantic Framework for Programming Languages and Formal Analysis Tools; and Software Abstractions and Human-Cyber-Physical Systems Architecture Modelling. |
| cloud-based battery management system: Deep Learning Approaches to Cloud Security Pramod Singh Rathore, Vishal Dutt, Rashmi Agrawal, Satya Murthy Sasubilli, Srinivasa Rao Swarna, 2022-01-26 DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Deep learning is the fastest growing field in computer science. Deep learning algorithms and techniques are found to be useful in different areas like automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delay in children. However, applying deep learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of deep learning in these areas, including areas of detection and prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, deep learning approaches, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems, thereby bringing a newer dimension to this rapidly evolving field. This groundbreaking new volume presents these topics and trends of deep learning, bridging the research gap, and presenting solutions to the challenges facing the engineer or scientist every day in this area. Whether for the veteran engineer or the student, this is a must-have for any library. Deep Learning Approaches to Cloud Security: Is the first volume of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches Covers these important new innovations, such as AI, data mining, and other evolving computing technologies in relation to cloud security Is a useful reference for the veteran computer scientist or engineer working in this area or an engineer new to the area, or a student in this area Discusses not just the practical applications of these technologies, but also the broader concepts and theory behind how these deep learning tools are vital not just to cloud security, but society as a whole Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas |
| cloud-based battery management system: Handbook of Research on AI and ML for Intelligent Machines and Systems Gupta, Brij B., Colace, Francesco, 2023-11-27 The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths. |
| cloud-based battery management system: IoT Enabled Multi-Energy Systems Mohammadreza Daneshvar, Behnam Mohammadi-Ivatloo, Kazem Zare, Amjad Anvari-Moghaddam, 2023-02-20 IoT-Enabled Multi-Energy Systems: From Isolated Energy Grids to Modern Interconnected Networks proposes practical solutions for the management and control of energy interactions throughout the interconnected energy infrastructures of the future multi-energy grid. The book discusses a panorama of modeling, planning and optimization considerations for IoT technologies, their applications across grid modernization, and the coordinated operation of multi-vector energy grids. The work is suitable for energy, power, mechanical, chemical, process and environmental engineers, and highly relevant for researchers and postgraduate students who work on energy systems. Sections address core theoretical underpinnings, significant challenges and opportunities, how to support IoT-based developed expert systems, and how AI can empower IoT technologies to sustainably develop fully renewable modern multi-carrier energy networks. Contributors address artificial intelligence technology and its applications in developing IoT-based technologies, cloud-based intelligent energy management schemes, data science and multi-energy big data analysis, machine learning and deep learning techniques in multi-energy systems, and much more. - Reviews core applications of IoT technologies in grid modernization of multi-energy networks - Develops practical solutions for optimal integration of renewable energy resources in modern multi-vector energy networks - Analyzes the reliable integration, sustainable operation and accurate planning of multi-carrier energy grids in highly penetrated stochastic energy resources |
| cloud-based battery management system: Reshaping Environmental Science Through Machine Learning and IoT Gupta, Rajeev Kumar, Jain, Arti, Wang, John, Pateriya, Rajesh Kumar, 2024-05-06 In the face of escalating environmental challenges such as climate change, air and water pollution, and natural disasters, traditional approaches to understanding and addressing these issues have yet to be proven sufficient. Academic scholars are compelled to seek innovative solutions that marry digital intelligence and natural ecosystems. Reshaping Environmental Science Through Machine Learning and IoT serves as a comprehensive exploration into the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) to address critical environmental challenges. The book establishes a robust foundation in ML and IoT, explaining their relevance to environmental science. As the narrative unfolds, it delves into diverse applications, providing theoretical insights alongside practical knowledge. From interpreting weather patterns to predicting air and water quality, the book navigates through the intricate web of environmental complexities. Notably, it unveils approaches to disaster management, waste sorting, and climate change monitoring, showcasing the symbiotic relationship between digital intelligence and natural ecosystems. This book is ideal for audiences from students and researchers to data scientists and disaster management professionals with a nuanced understanding of IoT, ML, and Artificial Intelligence (AI). |
| cloud-based battery management system: Handbook on Battery Energy Storage System Asian Development Bank, 2018-12-01 This handbook serves as a guide to deploying battery energy storage technologies, specifically for distributed energy resources and flexibility resources. Battery energy storage technology is the most promising, rapidly developed technology as it provides higher efficiency and ease of control. With energy transition through decarbonization and decentralization, energy storage plays a significant role to enhance grid efficiency by alleviating volatility from demand and supply. Energy storage also contributes to the grid integration of renewable energy and promotion of microgrid. |
| cloud-based battery management system: Convergence Strategies for Green Computing and Sustainable Development Jain, Vishal, Raman, Murali, Agrawal, Akshat, Hans, Meenu, Gupta, Swati, 2024-04-01 Convergence Strategies for Green Computing and Sustainable Development presents a comprehensive exploration of the potential of emerging technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), fog computing, and cloud computing, to aid in fostering a sustainable future. It examines how these technologies can reduce the impact of unsustainability in societies, the environment, and natural resources, offering invaluable insights into harnessing their power for positive change. Convergence Strategies for Green Computing and Sustainable Development serves as a comprehensive strategy that holistically understands, transforms, and develops technological systems in society. This book caters to a diverse range of readers, including graduate students, researchers, working professionals seeking knowledge, and industry experts seeking information about new trends. With its recommended topics and comprehensive table of contents, readers can gain in-depth knowledge about sustainable cloud computing, artificial intelligence and machine learning for sustainable development, sustainable wireless systems and networks, and the crucial role of green IoT and Edge-AI in driving a sustainable digital transition. |
| cloud-based battery management system: Asia Pacific Advanced Network Damayanthi Herath, Susumu Date, Upul Jayasinghe, Vijaykrishnan Narayanan, Roshan Ragel, Jilong Wang, 2024-01-02 This book constitutes the refereed proceedings of the 56th International Conference on Asia Pacific Advanced Network, APANConf 2023, held in, Colombo, Sri Lanka,during August 24–25, 2023. The 10 full papers and 1 short papers included in this book were carefully reviewed andselected from 37 submissions. They are organized in topical sections as follows: artificial intelligence and machine learning, accelerated computing and distributed systems and communications and networking. |
| cloud-based battery management system: Technological Advancements in Data Processing for Next Generation Intelligent Systems Sharma, Shanu, Prakash, Ayushi, Sugumaran, Vijayan, 2024-03-18 Technological Advancements in Data Processing for Next Generation Intelligent Systems presents an in-depth exploration of cutting-edge data processing technologies that drive the development of next-generation intelligent systems in the context of the digital transformation era. This comprehensive book delves into the role data plays as a critical asset for organizations across diverse industries, and how recent technological breakthroughs have unlocked unprecedented potential for handling vast data volumes and real-time analysis. The book begins by providing a thorough overview of novel technologies such as artificial intelligence (AI) or machine learning (ML), edge computing, federated learning, quantum computing, and more. These revolutionary technologies, when integrated with big data frameworks, in-memory computing, and AI/ML algorithms, have transformed data processing capabilities, enabling the creation of intelligent systems that fuel innovation, optimize operations, and deliver personalized experiences. The ultimate aim of this integration is to empower devices with the ability to make autonomous intelligent decisions, maximizing computing power. This book serves as a valuable resource for research scholars, academicians, and industry professionals working towards the future advancement of optimized intelligent systems and intelligent data processing approaches. The chapters encompass a wide range of topics, including architecture and frameworks for intelligent systems, applications in diverse domains, cloud-based solutions, quantum processing, federated learning, in-memory data processing, real-time stream processing, trustworthy AI for Internet of Things (IoT) sensory data, and more. |
| cloud-based battery management system: Intelligent Electric Vehicles Dr. Shaoshan Liu, 2024-11-01 Embark on a journey into the future of transportation with Intelligent Electric Vehicles. This comprehensive guide demystifies complex concepts, offering a roadmap to harness the monetization opportunities within the thriving IEV ecosystem. From management strategies to cutting-edge technology, this book provides a holistic perspective on the IEV industry. Explore real-world case studies, learn about emerging trends like cockpit intelligence and connected vehicles, and discover how to navigate the challenges and opportunities of this transformative space. Key Features: • Interdisciplinary approach: Bridges the gap between management and technology. • Real-world case studies: Grounds theoretical knowledge in practical applications. • Future-focused insights: Prepares readers for the next wave of innovations. • Monetization roadmap: Offers strategic advice for capitalizing on IEV advancements. Whether you're an automotive industry professional, technology enthusiast, or investor, Intelligent Electric Vehicles is your essential guide to understanding and succeeding in this exciting new era of transportation. (ISBN 9781468608496, ISBN 9781468608502, ISBN 9781468608519 https://doi.org/10.4271/9781468608502) |
| cloud-based battery management system: Advanced Applications in Osmotic Computing Revathy, G., 2024-03-04 The interaction of various service models, including edge computing and cloud computing, are quickly changing to better support microservices. This intricate weave of technology and information sharing is necessary to build systems that run faster and more efficiently. The interplay between these computing methods and microservices is emerging as the field of Osmotic Computing. Experts can now embark on an intellectual journey into data-driven exploration and ingenuity with the guidance of the book, Advanced Applications in Osmotic Computing. As ethical considerations become rising concerns, the potential biases, privacy encumbrances, and equitable conundrums of osmotic computing are investigated. This book offers judicious strategies to navigate these quandaries conscientiously, adding a layer of responsibility to the discourse. Within these pages, the very fabric of understanding in IoT, Cloud, Edge, Fog, and Machine Learning is redefined, marking a pivotal shift in the paradigm of technological comprehension. This book is an epicenter for the latest evolutions in osmotic computing, unfurling unconventional methodologies that shape the trajectory of data-driven decision-making. Readers will plunge into the theoretical bedrock, simultaneously witnessing pragmatic applications that adeptly bridge the schism between the theoretical constructs and pragmatic realization. The intended audience is multifaceted, encompassing data scientists, machine learning engineers, researchers, academics, educators, students, industry practitioners, interdisciplinary experts, and technology and business leaders. |
| cloud-based battery management system: AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications Angalaeswari, S., Deepa, T., Kumar, L. Ashok, 2023-02-03 Artificial intelligence techniques applied in the power system sector make the prediction of renewable power source generation and demand more efficient and effective. Additionally, since renewable sources are intermittent in nature, it is necessary to predict and analyze the data of input sources. Hence, further study on the prediction and data analysis of renewable energy sources for sustainable development is required. AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications focuses on artificial intelligence techniques for the evolving power system field, electric vehicle market, energy storage elements, and renewable energy source integration as distributed generators. Covering key topics such as deep learning, artificial intelligence, and smart solar energy, this premier reference source is ideal for environmentalists, computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students. |
| cloud-based battery management system: Smart Grids and Internet of Things Sanjeevikumar Padmanaban, Rajesh Kumar Dhanaraj, Malathy Sathyamoorthy, Jens Bo Holm-Nielsen, Balamurugan Balusamy, 2023-06-07 SMART GRIDS AND INTERNET OF THINGS Smart grids and the Internet of Things (IoT) are rapidly changing and complicated subjects that are constantly changing and developing. This new volume addresses the current state-of-the-art concepts and technologies associated with the technologies and covers new ideas and emerging novel technologies and processes. Internet of Things (IoT) is a self-organized network that consists of sensors, software, and devices. The data is exchanged among them with the help of the internet. Smart Grids (SG) is a collection of devices deployed in larger areas to perform continuous monitoring and analysis in that region. It is responsible for balancing the flow of energy between the servers and consumers. SG also takes care of the transmission and distribution power to the components involved. The tracking of the devices present in SG is achieved by the IoT framework. Thus, assimilating IoT and SG will lead to developing solutions for many real-time problems. This exciting new volume covers all of these technologies, including the basic concepts and the problems and solutions involved with the practical applications in the real world. Whether for the veteran engineer or scientist, the student, or a manager or other technician working in the field, this volume is a must-have for any library. Smart Grids and Internet of Things: Presents Internet of Things (IoT) and smart grid (SG)-integrated frameworks along with their components and technologies Covers the challenges in energy harvesting and sustainable solutions for IoTSGs and their solutions for practical applications Describes and demystifies the privacy and security issues while processing data in IoTSG Includes case studies relating to IoTSG with cloud and fog computing machine learning and blockchain |
| cloud-based battery management system: The Sun, Energy, and Climate Change Eklas Hossain, 2023-01-01 The Sun, Energy, and Climate Change conveys one central idea – that we can utilize energy without continuing to harm the planet by increasing our reliance on energy from the sun. This accessible guide stresses the sun’s importance as our ultimate energy source by focusing on climate change from an energy perspective and explains the naturally balanced energy transfer from the sun to the earth and society’s consumption of this energy. This book is for anyone worried about environmental damage from our reliance on fossil fuels and the global fight against climate change. The key message being we do not have to accept the inevitable and can work to prevent the worst. |
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