Artificial Intelligence And Conservation
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Artificial Intelligence and Conservation
Author: Fei Fang
language: en
Publisher: Cambridge University Press
Release Date: 2019-03-28
Explains how artificial intelligence methods can be used to aid conservation of wildlife, forests, coral reefs, rivers, and other natural resources.
Artificial Intelligence for Renewable Energy Systems
ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.
AI and Machine Learning Techniques for Wildlife Conservation
Author: Raghav, Yogita Yashveer
language: en
Publisher: IGI Global
Release Date: 2025-02-11
As the world grapples with the alarming rate of biodiversity loss, the potential of cutting-edge technologies, namely machine learning (ML) and artificial intelligence (AI), revolutionize the way we approach wildlife conservation. From sophisticated sensor technologies to innovative AI algorithms, foundational tools driving this paradigm shift provide a comprehensive understanding of their applications in safeguarding biodiversity. The navigation of systems such as the Spatial Monitoring and Reporting Tool (SMART) and advanced animal detection systems can be used to delve into the intricacies of feature extraction and precise identification. This exploration of predictive modeling, data ethics, citizen science, and the integration of satellite data offers a holistic perspective on the dynamic intersection of technology and conservation. AI and Machine Learning Techniques for Wildlife Conservation illustrates the tangible impact of these technologies on addressing pressing conservation challenges and advocates for the engagement of citizen science initiatives with AI. It fosters a collaborative approach to wildlife conservation that leverages the power of technology for a sustainable future. Covering topics including Internet of Things (IoT), satellite data, and predictive ecosystem management, this book is an excellent resource for conservationists, computer scientists, researchers, professionals, academicians, scholars, and more.