Green Industrial Applications Of Artificial Intelligence And Internet Of Things

DOWNLOAD

Download Green Industrial Applications Of Artificial Intelligence And Internet Of Things PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Green Industrial Applications Of Artificial Intelligence And Internet Of Things book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Green Industrial Applications Of Artificial Intelligence And Internet Of Things

DOWNLOAD
Author : Biswadip Basu Mallik
language : en
Publisher: Bentham Science Publishers
Release Date : 2024-07-22

Green Industrial Applications Of Artificial Intelligence And Internet Of Things written by Biswadip Basu Mallik and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-22 with Computers categories.

This book explores the intersection of the Internet of Things (IoT) and Artificial Intelligence (AI) in sustaining a green environment, sustainable societies, and thriving industries. It offers a comprehensive exploration of how these technologies intersect and transform various sectors to enhance environmental conservation, societal well-being, and industrial progress. The book features a diverse array of case studies, methodologies, and notes on technological advancements. Readers will gain valuable insights into the impact of AI and IoT on sustainable initiatives through real-world examples, research findings, and discussions on future directions. Key themes AI in complex and versatile scenarios: Chapters 1 and 4 explore AI applications in combatant identification and COVID-19 monitoring IoT for efficiency and data-driven decision-making: Chapters 2, 3, and 7 focus on IoT implementations in battery monitoring for electric vehicles, healthcare systems, and precision farming AI for diagnostics and computer vision: Chapters 5, 9, and 13 highlight AI-driven solutions for plant disease detection, fetal spine disorder detection, and defect detection Industry applications: Chapters 6, 8, 10, 11, 12, 14, 15, 16, and 17 cover AI and IoT in healthcare, transportation, supply chain management, endangered species protection, crop management, and pollution detection, showcasing their transformative potential across various domains. This book is ideal for readers with multidisciplinary backgrounds, including researchers, academics, professionals, and students interested in IoT, AI, environmental sustainability, healthcare, agriculture, smart technologies, and industrial innovation.

Green Industrial Applications Of Artificial Intelligence And Internet Of Things

DOWNLOAD
Author : Biswadip Basu Mallik
language : en
Publisher:
Release Date : 2024

Green Industrial Applications Of Artificial Intelligence And Internet Of Things written by Biswadip Basu Mallik and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.

Scalable Artificial Intelligence For Healthcare

DOWNLOAD
Author : Houneida Sakly
language : en
Publisher: CRC Press
Release Date : 2025-05-06

Scalable Artificial Intelligence For Healthcare written by Houneida Sakly and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-06 with Computers categories.

This edited volume examines the transformative impact of AI technologies on global healthcare systems, with a focus on enhancing efficiency and accessibility. The content provides a comprehensive exploration of the principles and practices required to scale AI applications in healthcare, addressing areas such as diagnosis, treatment, and patient care. Key topics include data scalability, model deployment, and infrastructure design, highlighting the use of microservices, containerization, cloud computing, and big data technologies in building scalable AI systems. Discussions cover advancements in machine learning models, distributed processing, and transfer learning, alongside critical considerations such as continuous integration, data privacy, and ethics. Real-world case studies depict both the successes and challenges of implementing scalable AI across various healthcare environments, offering valuable insights for future advancements. This volume serves as a practical and theoretical guide for healthcare professionals, AI researchers, and technology enthusiasts seeking to develop or expand on AI-driven healthcare solutions to address global health challenges effectively.

Intelligent Urban Mobility

DOWNLOAD
Author : Muhammet Deveci
language : en
Publisher: Academic Press
Release Date : 2025-07-04

Intelligent Urban Mobility written by Muhammet Deveci and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-04 with Transportation categories.

Intelligent Urban Mobility: Decision Support Systems for Sustainable Transportation explores the role of technology in enabling greener, more accessible transportation in cities worldwide. This book provides insights into leveraging decision support systems to drive positive change by focusing on applied soft computing techniques, artificial intelligence, and algorithms for fuzzy systems. Researchers and professionals will find actionable information on mitigating congestion and emissions through sustainable mobility initiatives, which bridges the gap between theory and real-world practice.The book also offers technical guidance and expert perspectives on the application of decision support systems to evaluate and optimize planning for sustainable transit options. The book highlights innovative models and frameworks for analyzing mobility options and planning sustainable transport systems. It is an essential resource for researchers, graduate students, and professionals in transportation, urban planning, civil engineering, and decision sciences who aim to redesign city transportation to reduce environmental impact and carbon emissions. - Provides an overview of the most recent advances in the development of decision support systems for the implementation of sustainable urban mobility - Presents various urban mobility applications using artificial intelligence, applied soft computing techniques, and other decision support systems - Offers solutions for the design, development, and integration of sustainable urban transport options

Digital Tools And Data For Innovative Healthcare

DOWNLOAD
Author : Patricia Ordonez de Pablos
language : en
Publisher: Academic Press
Release Date : 2025-10-13

Digital Tools And Data For Innovative Healthcare written by Patricia Ordonez de Pablos and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-13 with Science categories.

Digital Tools and Data for Innovative Healthcare: A Vision for Healthier and More Inclusive Societies is an invaluable resource for addressing the critical needs of healthcare professionals and researchers. In 6 sections, it provides an in-depth exploration of digital health technologies, offering practical applications and ethical guidelines that are essential for the effective use of health data. By focusing on the integration of AI and machine learning in clinical environments, the book equips its audience with the knowledge necessary to enhance patient outcomes and optimise healthcare operations. This comprehensive approach ensures that readers are well-prepared to navigate and leverage the rapidly evolving landscape of digital healthcare. - Provides understanding to the potential of digital tools in the field of healthcare and how these tools can build stronger national health systems - Include cases with experiences of applications of health data, tools and services for the digital transformation of healthcare sector - Give views and insights for the transition towards stronger healthcare models and infrastructures

Learning Techniques For The Internet Of Things

DOWNLOAD
Author : Praveen Kumar Donta
language : en
Publisher: Springer Nature
Release Date : 2024-02-19

Learning Techniques For The Internet Of Things written by Praveen Kumar Donta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-19 with Computers categories.

The book is structured into thirteen chapters; each comes with its own dedicated contributions and future research directions. Chapter 1 introduces IoT and the use of Edge computing, particularly cloud computing, and mobile edge computing. This chapter also mentions the use of edge computing in various real-time applications such as healthcare, manufacturing, agriculture, and transportation. Chapter 2 motivates mathematical modeling for federated learning systems with respect to IoT and its applications. Further Chapter 3 extends the discussion of federated learning for IoT, which has emerged as a privacy-preserving distributed machine learning approach. Chapter 4 provides various machine learning techniques in Industrial IoT to deliver rapid and accurate data analysis, essential for enhancing production quality, sustainability, and safety. Chapter discusses the potential role of data-driven technologies, such as Artificial Intelligence, Machine Learning, and Deep Learning, focuses on their integration with IoT communication technologies. Chapter 6 presents the requirements and challenges to realize IoT deployments in smart cities, including sensing infrastructure, Artificial Intelligence, computing platforms, and enabling communications technologies such as 5G networks. To highlight these challenges in practice, the chapter also presents a real-world case study of a city-scale deployment of IoT air quality monitoring within Helsinki city. Chapter 7 uses digital twins within smart cities to enhance economic progress and facilitate prompt decision-making regarding situational awareness. Chapter 8 provides insights into using Multi-Objective reinforcement learning in future IoT networks, especially for an efficient decision-making system. Chapter 9 offers a comprehensive review of intelligent inference approaches, with a specific emphasis on reducing inference time and minimizing transmitted bandwidth between IoT devices and the cloud. Chapter 10 summarizes the applications of deep learning models in various IoT fields. This chapter also presents an in-depth study of these techniques to examine new horizons of applications of deep learning models in different areas of IoT. Chapter 11 explores the integration of Quantum Key Distribution (QKD) into IoT systems. It delves into the potential benefits, challenges, and practical considerations of incorporating QKD into IoT networks. In chapter 12, a comprehensive overview regarding the current state of quantum IoT in the context of smart healthcare is presented, along with its applications, benefits, challenges, and prospects for the future. Chapter 13 proposes a blockchain-based architecture for securing and managing IoT data in intelligent transport systems, offering advantages like immutability, decentralization, and enhanced security.

Industry 5 0

DOWNLOAD
Author : Indranil Sarkar
language : en
Publisher: Springer Nature
Release Date : 2025-07-17

Industry 5 0 written by Indranil Sarkar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-17 with Computers categories.

This edited book aims to comprehensively examine the current research trend, state-of-the-art IoT applications, deployment issues, potential challenges, and future research scopes related to Industry 5.0 and Industry 5.0-enabled technologies such as Blockchain, edge computing, 5G, and cloud computing. The book aims to provide a thorough understanding of the application specifications and related issues of IoT in the fields of healthcare 5.0, predictive maintenance, sustainable cities, and transportation systems. Readers of the book will gain valuable insights into applying the concepts to real-world applications and will be introduced to the latest tools, software, and simulations available for experimenting with Industry 5.0 and ideas about diverse IIoT data analysis. The book will also provide valuable insights into the use of AI tools and algorithms for designing intelligent systems to tackle Industry 5.0 issues. It is of great value to readers interested in understanding the integration of Blockchain, edge computing, 5G, and its sister technologies with IIoT and the research scope to solve Industry 5.0 issues.

Intelligent Internet Of Things For Healthcare And Industry

DOWNLOAD
Author : Uttam Ghosh
language : en
Publisher: Springer Nature
Release Date : 2022-02-12

Intelligent Internet Of Things For Healthcare And Industry written by Uttam Ghosh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-12 with Technology & Engineering categories.

This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures. This book is focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives. The data analytics discussed are relevant for healthcare and industry to meet many technical challenges and issues that need to be addressed to realize this potential. The IoT discussed helps to design and develop the intelligent medical and industry solutions assisted by data analytics and machine learning. At the end of every chapter readers are encouraged to check their understanding by means of brainstorming summary, discussion, exercises and solutions.

Artificial Intelligence Machine Learning And Deep Learning For Sustainable Industry 5 0

DOWNLOAD
Author : Nitin Liladhar Rane
language : en
Publisher: Deep Science Publishing
Release Date : 2024-10-14

Artificial Intelligence Machine Learning And Deep Learning For Sustainable Industry 5 0 written by Nitin Liladhar Rane and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-14 with Computers categories.

This book offers an insight into the applications of Artificial Intelligence (AI)- Machine Learning Algorithms and Deep Learning (DL) in Bigdata Analytics to Industry 4.0/5.0 and Society 5.0 with transformative power responsibly. It has delved into how these technologies are disrupting industries, fostering innovation, and solving age-old social problems-so that readers have an understanding of where the digital world is headed. These chapters cover the big picture subjects of using AI with Big data analytics aimed mostly at increasing industrial efficiency, healthcare optimization, retail transformation, construction industry transformation, autonomous vehicles development and environmental sustainability improvement. The book covers each of these technologies extensively applied to full chapters devoted to detail studies, methodologies and practical usages. One of the central concepts in the book is how we evolve from industry 4.0 to industry 5.0. Therefore, Industry 4.0 relies on the automation and data exchange in manufacturing technologies using cyber-physical systems, the Internet of Things and cloud computing route to intelligent factories. During this phase, it improves operational efficiency, predictive maintenance and real-time monitoring which lowers down time and other operating costs by considerable amount. As industries move towards Industry 5.0, a lot has been noted-human-oriented solutions that combine human creativity and intelligence with highly automated and distributed technological tools. More cooperation between humans and machines during such times will, therefore, result in more customized production aimed at sustainable processes. The book details how, thanks to digital twins-that is, innumerable virtual replicas of physical systems-the further step is taken, allowing for real-time data analysis and, consequently innovative ways of manufacturing where the interests of the workers and customers come first. The present book discusses how AI and big data analytics transcend industrial applications to meet more societal ends as society ushers in its fifth revolution. Society 5.0 postulates that a super-smart digital society will drive transformation in all aspects of life, ranging from health and education to planning urban resources and infrastructure and ensuring public safety. The combination of AI with Big Data makes personalized healthcare services possible, competent resource planning in cities, and environmental sustainability in place via predictive analytics or simulation models. One such industry in which significant changes are coming, according to AI and Big Data analytics, is healthcare. This book shows how these technologies improve diagnostic accuracy, enable personalized treatment plans, and optimize resource allocations. Predictive insights can predict outbreaks and admissions, which helps better preparedness against diseases and also optimizes health resource utilization. AI in medical imaging and anomaly detection strengthens the efficiency of professional health experts, thus delivering better patient outcomes. AI and big data analytics have further remodelled the retail industry by providing retailers profound insights into consumer behaviour and preferences. With this information, retailers can adopt person-segmented marketing techniques and optimize inventory levels while enabling high levels of customer service using AI-fuelled chatbots and virtual assistants. These technologies help retailers stay competitive in an ever-developing market environment by offering solutions structured based on individual needs expressed by customers. AI and big data analytics combine to form one synergy connected with autonomous vehicles. It further goes on to discuss the huge amount of data needed for training these AI models and big data analytics in refining the accuracy and safety of autonomous driving systems. Another critical area in which AI and Big Data Analytics make a considerable impact is environmental sustainability. By applying these analyses to large data sets relating to climatic changes, energy consumption, and natural resources, AI models can establish trends and recognize patterns indicating future changes. This predictive ability equips organizations and governments with tools to develop lower environmental footprints and promote sustainable practices proactively. It further explains AI-enabled energy management systems that drive optimized energy use in buildings to reduce carbon emissions and save on associated costs. This certainly looks like something for a vast readership: it speaks more to academics, professionals working in the industry, and decision-makers-but, really, to anybody who seeks to grasp the transformative powerfulness of AI and big data analytics. This source will provide information on overall guidance and a rich source of inspiration in using these technologies to enable innovation and sustainable development across different sectors. Actual case examples and practical applications are given to convey the knowledge and elements that readers need to know as they go about using AI and big data analytics. This book also includes discussions concerning the dynamic policy and regulatory scenes of AI, pointing out that it is necessary to have standard policies that should be implemented to have ethical deployment of AI that reduces risks. This book also focuses on challenges in implementing AI for intelligent and sustainable industries, meaning technical, ethical, and operational barriers. It outlines high costs, low-quality data, and the need for skilled professionals; ethical concerns and robust cybersecurity measures become necessary. As such, this book will engross an audience ranging from academics to industry professionals and policymakers working toward understanding and using AI and big data for sustainable development and technological advancement.

Artificial Intelligence For Digitising Industry Applications

DOWNLOAD
Author : Ovidiu Vermesan
language : en
Publisher: CRC Press
Release Date : 2022-09-01

Artificial Intelligence For Digitising Industry Applications written by Ovidiu Vermesan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-01 with Medical categories.

This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI project, including an overview of industrial use cases, research, technological innovation, validation, and deployment. This book’s sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation. The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin. AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection. The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport. This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.