Artificial Intelligence And Data Science In Environmental Sensing
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Artificial Intelligence And Data Science In Environmental Sensing
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Author : Mohsen Asadnia
language : en
Publisher: Academic Press
Release Date : 2022-02-09
Artificial Intelligence And Data Science In Environmental Sensing written by Mohsen Asadnia and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-09 with Computers categories.
Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. - Presents tools, connections and proactive solutions to take sustainability programs to the next level - Offers a practical guide for making students proficient in modern electronic data analysis and graphics - Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery
Artificial Intelligence Methods In The Environmental Sciences
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Author : Sue Ellen Haupt
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-11-28
Artificial Intelligence Methods In The Environmental Sciences written by Sue Ellen Haupt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-28 with Science categories.
How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.
Machine Learning And Data Science In The Oil And Gas Industry
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Author : Patrick Bangert
language : en
Publisher: Gulf Professional Publishing
Release Date : 2021-03-04
Machine Learning And Data Science In The Oil And Gas Industry written by Patrick Bangert and has been published by Gulf Professional Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-04 with Science categories.
Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. - Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful - Gain practical understanding of machine learning used in oil and gas operations through contributed case studies - Learn change management skills that will help gain confidence in pursuing the technology - Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)
Artificial Intelligence And Data Science For Sustainability Applications And Methods
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Author : Syafrudin, Muhammad
language : en
Publisher: IGI Global
Release Date : 2025-02-07
Artificial Intelligence And Data Science For Sustainability Applications And Methods written by Syafrudin, Muhammad and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-07 with Computers categories.
The integration of artificial intelligence (AI) and data science (DS) into sustainability efforts is increasingly crucial as the world faces environmental and resource challenges. By leveraging advanced AI and DS techniques, we can create innovative solutions for sectors like energy, agriculture, and waste management, promoting long-term sustainability. These technologies have the potential to optimize processes, reduce environmental footprints, and support smarter decision-making across industries. Ultimately, AI and DS are key to advancing both the efficiency and impact of sustainability efforts, contributing to a more sustainable future for society at large. Artificial Intelligence and Data Science for Sustainability: Applications and Methods explores the application of AI and DS techniques and methodologies in addressing various sustainability challenges. It brings together cutting-edge research, case studies, and practical applications that demonstrate how AI can be leveraged to promote sustainable development across diverse domains. Covering topics such as structural optimization, drone imagery, and development financing, this book is an excellent resource for computer scientists, computer engineers, urban planners, sustainability professionals, government officials, policymakers, researchers, professionals, scholars, academicians, and more.
Prospects Of Artificial Intelligence In The Environment
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Author : Ajitanshu Vedrtnam
language : en
Publisher: Springer Nature
Release Date : 2025-07-19
Prospects Of Artificial Intelligence In The Environment written by Ajitanshu Vedrtnam and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-19 with Technology & Engineering categories.
This book gives readers insight into the state-of-the-art use of artificial intelligence for the environment. It encompasses most of the significant facets of current breakthroughs in the fields of conceptions, methodologies, resources, and leading artificial intelligence solutions for the environment. This book presents research at the forefront on applications of artificial intelligence in combating climate change, natural hazards, and textile dyeing pollution (water pollution), for forecasting, assessing air quality trends, and air pollution monitoring. It explains how machine learning can prove to be an efficient technique to forecast the consumption of energy and how AI can be effective for renewable energy systems. Research in this book widens its scope to present the problems, opportunities, and directives for the application of AI systems in engine exhaust prediction. One of the new and interesting things explored is to provide and predict the rate of decay of human lung tissue (due to Particulate Matter exposure) with the help of AI in this book. Likewise, the book opens its scope to various environmental problems and focuses on giving the best solutions with an application of artificial intelligence; this feature makes this book an indispensable guide for environmental scientists and AI researchers of all levels. The book is written comprehensively so that engineering professionals, programmers, environmentalists, graduates, postgraduates, and researchers from beginning/intermediate level to advance level can be enlightened.
Environmental Monitoring Using Artificial Intelligence
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Author : A. Suresh
language : en
Publisher: John Wiley & Sons
Release Date : 2025-02-19
Environmental Monitoring Using Artificial Intelligence written by A. Suresh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-19 with Computers categories.
Environmental Monitoring Using Artificial Intelligence is a vital resource for anyone looking to leverage cutting-edge technologies in artificial intelligence and sensor systems to effectively address environmental challenges, offering innovative solutions and insights essential for creating a sustainable future. Environmental Monitoring Using Artificial Intelligence provides a comprehensive exploration of the cutting-edge technologies transforming environmental monitoring. This book bridges the gap between artificial intelligence (AI), natural language processing (NLP), and sensor-based systems, highlighting their potential to revolutionize the way we address pressing environmental challenges. Each chapter presents innovative case studies, real-world applications, and the latest research on how these technologies are being utilized to monitor and manage ecosystems, water resources, air quality, and urban sustainability. From advanced sensor networks to machine learning models, this book covers a broad spectrum of topics, including smart water solutions, biodiversity conservation, waste management, and agricultural sustainability. It offers an interdisciplinary approach, making it an essential resource for environmental engineers, data scientists, researchers, and policymakers. Whether you’re exploring smart city innovations, renewable energy monitoring, or AI-driven solutions for environmental protection, Environmental Monitoring Using Artificial Intelligence equips readers with the knowledge and tools to leverage technology for a sustainable future.
Artificial Intelligence Driven Models For Environmental Management
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Author : Shrikaant Kulkarni
language : en
Publisher: John Wiley & Sons
Release Date : 2025-08-19
Artificial Intelligence Driven Models For Environmental Management written by Shrikaant Kulkarni and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-19 with Science categories.
Step-by-step guidelines for the development of artificial neural network-based environmental pollution models Artificial Intelligence-Driven Models for Environmental Management delves into the application of AI across a plethora of areas in environmental management, including climate forecasting, natural resource optimization, waste management, and biodiversity conservation. This book shows how AI can help in monitoring, predicting, and mitigating environmental impacts with tremendous accuracy and speed by leveraging machine learning, deep learning, and other data-driven models. The methodologies explored in this volume reflect a synthesis of computational intelligence, data science, and ecological expertise, underscoring how AI-driven systems have been making strides in managing and preserving our planet's natural resources. The text is structured to guide readers through numerous AI models and their practical environmental management applications, showcasing theoretical foundations as well as case studies. This book also addresses the challenges and ethical considerations related to deploying AI in ecological contexts, underscoring the importance of transparency, inclusivity, and alignment with sustainability goals. Sample topics discussed in Artificial Intelligence-Driven Models for Environmental Management include: Tools and methods for monitoring and predicting environmental pollutants faster and more accurately AI technology for the protection of water supplies from contamination to produce healthier foods Use of AI for the evaluation of the impacts of environmental pollution on human health AI and waste management technologies for sustainable agriculture and soil management The role of AI in environmental research and sustainability and key social and economic aspects of natural resource management through AI Artificial Intelligence-Driven Models for Environmental Management is a timely, forward-thinking resource for a diverse readership, including researchers, policymakers, environmental scientists, and AI practitioners.
Mobile Crowdsensing And Remote Sensing In Smart Cities
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Author : Chaker Abdelaziz Kerrache
language : en
Publisher: Springer Nature
Release Date : 2024-12-27
Mobile Crowdsensing And Remote Sensing In Smart Cities written by Chaker Abdelaziz Kerrache and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-27 with Technology & Engineering categories.
This book focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities, particularly in creating an intelligent context-aware environment, especially in cases of infectious diseases that cause widespread loss of life. The authors first introduce the concepts of MCS and remote sensing in smart cities. The authors go on to discuss topics such as power of mobile edge and cloud computing for data analytics; strategies to effectively manage and mitigate data redundancy; crowd management during the Covid-19 pandemic; techniques to detect communities in complex data through social sensing; and much more. The authors also aim to show that the efficient implementation of MCS and remote sensing in various applications comes with several challenging issues that need to be addressed, including data quality and reliability, security and privacy, and ethical considerations. Focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities; Covers technical details of remote sensing starting from the communication support to the application; Includes overcoming challenges including data quality and reliability, security and privacy, and ethical considerations.
Technological Innovation And Ai For Sustainable Development In Events And Festivals
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Author : Anukrati Sharma
language : en
Publisher: CABI
Release Date : 2025-05-30
Technological Innovation And Ai For Sustainable Development In Events And Festivals written by Anukrati Sharma and has been published by CABI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-30 with Business & Economics categories.
From sustainable event planning to the influence of VR, AI, and mobile applications on tourist behaviour, this book explores the dynamic landscape where innovation meets tradition. It studies the intersection of green technologies, sustainable infrastructure, and the delicate balance between cutting-edge tools and the intrinsic emotional aspects of human engagement. Aligned with the United Nations' 17 Sustainable Development Goals, the book highlights AI's potential to drive meaningful contributions to a sustainable future. It anticipates the imminent transformation of festivals and events through technological innovation and AI implementation. It will allow the reader to gain insights into how automation streamlines logistics, optimizes marketing efforts, and enhances the overall attendee experience.
Human Centric Integration Of Next Generation Data Science And Blockchain Technology
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Author : Amit Kumar Tyagi
language : en
Publisher: Academic Press
Release Date : 2025-03-17
Human Centric Integration Of Next Generation Data Science And Blockchain Technology written by Amit Kumar Tyagi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-17 with Science categories.
Human- Centric Integration of Next Generation Data Science and Blockchain Technology: Advancing Society 5.0 Paradigms focuses on the current technological landscape, addressing the evolving integration of data science and blockchain within the context of Society 5.0. This comprehensive resource explains the convergences between data science, blockchain, and the human-centric vision of Society 5.0, while also filling the gap in understanding and navigating this transformative intersection with recent shifts towards more decentralized and data-driven paradigms.The book introduces the concept of Society 5.0, examining the historical context, and outlines the evolving technological landscape shaping our interconnected future. It discusses the fundamental principles of data science, from data collection and preprocessing to exploratory data analysis and explains the transformative impact of data science and blockchain across industries such as healthcare, finance, education, and transportation. This book is essential to understanding and shaping the future of technology and society from decentralized solutions to predictive analytics/ emerging technologies. - Addresses the evolving integration of data science and blockchain within the context of Society 5.0 - Introduces the basic architecture and taxonomy of blockchain technology - Explores the future urban lives under the concept of "Society 5.0", characterized by the key phrases of data-driven society and knowledge-intensive society - Offers a firm foundation and understanding of recent advancements in various domains such as data analytics, neural networks, computer vision, and robotics, along with practical solutions to existing problems in fields such as healthcare, manufacturing industries, security, and infrastructure management