Artificial Intelligence and Computer Vision for Ecological Informatics
1st Edition
Published on 26. August 2025
Book
Hardback
396 pages
978-1-032-83643-0 (ISBN)
Description
Ecological informatics, more commonly known as Ecoinformatics, is the study of environmental sciences and ecological information. It is an emerging interdisciplinary framework for the management, analysis, and synthesis of ecological data with the help of advanced computational intelligence algorithms. Management in this context is data acquisition, preprocessing, and sharing the data. Analysis and synthesis are the process of extracting useful information and forecasting with the help of intelligent algorithms.
The aim of this book is to encapsulate concepts and theories of artificial intelligence and computer vision algorithms used for the evaluation of various ecological informatics applications. It focuses on soft computing, machine learning, deep learning, artificial intelligence, bio-inspired algorithms, data analysis tools, data visualization tools, and computer vision algorithms used in ecological informatics. The book covers remote sensing applications, water bodies evaluation, agriculture mapping, aquatic mapping, forest management, and terrestrial ecosystems.
The book will be useful to students, researchers, scientists, and field experts in directing their work towards this domain, to deliver and design models and prototypes for the benefit of society and the environment.
The aim of this book is to encapsulate concepts and theories of artificial intelligence and computer vision algorithms used for the evaluation of various ecological informatics applications. It focuses on soft computing, machine learning, deep learning, artificial intelligence, bio-inspired algorithms, data analysis tools, data visualization tools, and computer vision algorithms used in ecological informatics. The book covers remote sensing applications, water bodies evaluation, agriculture mapping, aquatic mapping, forest management, and terrestrial ecosystems.
The book will be useful to students, researchers, scientists, and field experts in directing their work towards this domain, to deliver and design models and prototypes for the benefit of society and the environment.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Academic and Postgraduate
Illustrations
58 s/w Zeichnungen, 10 farbige Zeichnungen, 42 s/w Tabellen, 6 s/w Photographien bzw. Rasterbilder, 6 Farbfotos bzw. farbige Rasterbilder, 16 farbige Abbildungen, 64 s/w Abbildungen
42 Tables, black and white; 10 Line drawings, color; 58 Line drawings, black and white; 6 Halftones, color; 6 Halftones, black and white; 16 Illustrations, color; 64 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 26 mm
Weight
769 gr
ISBN-13
978-1-032-83643-0 (9781032836430)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Siddharth Singh Chouhan | Uday Pratap Singh | Akash Saxena
Artificial Intelligence and Computer Vision for Ecological Informatics
E-Book
08/2025
CRC Press
€73.99
Available for download
Siddharth Singh Chouhan | Uday Pratap Singh | Akash Saxena
Artificial Intelligence and Computer Vision for Ecological Informatics
E-Book
08/2025
CRC Press
€73.99
Available for download
Persons
Dr. Siddharth Singh Chouhan is an Assistant Professor in School of Computing Science and Engineering, VIT Bhopal University, Kothri-Kalan, Sehore, India. He has a PhD in Computer Science and Engineering from Shri Mata Vaishno Devi University Katra, India. He is a PostDoctorate from the University of Malta, Malta. He has a BTech degree (2010) and a MTech (2013) in Computer Science and Engineering from RGPV University, Bhopal, India. His areas of interest include Soft Computing, Computer vision, Drone Technology, Deep Learning, and Precision Agriculture. He had authored several research papers in many reputed journals and conferences.
Prof. Uday Pratap Singh is a Professor in the Department of Mathematics, Central University of Jammu, Jammu, India. He completed his BSc and MSc (Mathematics and Statistics) from Dr. R.M.L. (Avadh) University, Ayodhya, India, and again did his MSc (Mathematics and Computing) from Indian Institute of Technology, Guwahati, India, and a PhD in Computer Science from Barkatullah University, Bhopal. His areas of interest include Soft Computing, Nonlinear Systems, and Image Processing. He had authored several research papers in the many reputed journals and conferences. He is a life member of Soft Computing Research Society (SCRC), Barata Ganita Parishad, Computer Society of India and Member of IEEE and AMS.
Prof. Akash Saxena has a PhD and Master of Technology degree (with Honours) in Electrical Engineering from Malaviya National Institute of Technology, Jaipur in 2015 and 2008 respectively and a Bachelor of Engineering degree (with Honours) in Electrical Engineering from Engineering College Kota in 2001. Prof Saxena is working as (Director of Training and Placement) and Professor in Department of Electrical Engineering Central University of Haryana, India with almost two decades of teaching experience. As an academician, he has been associated with numerous institutions. He is a member of Doctoral Research Committee and a member of the Board of Studies. He has presented his research work at various platforms to showcase his findings to fellow researchers and provide a pathway to the future researchers. His works have been published in leading journals in the form of short communication/letters /articles/research papers.
Prof. Akhilesh Tiwari is a Professor in Department of Information Technology, MITS Gwalior, MP, India. He has a Bachelor degree and Master's degree in Information Technology from RGPV Bhopal, India, and a PhD in Information Technology. His area of research interests includes Knowledge Discovery in Databases & Data Mining, Terrorist Network Mining, Hesitation Mining and Pattern Warehousing. He has published more than 80 research papers in reputed journals and conferences published by leading publishers with SCI, SCIE and SCOPUS indexing.
Prof. Sanjeev Jain is a Vice Chancellor of the Central University of Jammu, India. He has a Master's degree in Computer Science and Engineering from IIT Delhi, India, in 1992, and a PhD in Computer Science and Engineering. He has over 35 years of experience in teaching, research and administration. He has the credit of making a significant contribution to research and development in the area of image processing, soft computing, IoT and mobile ad-hoc network. He had authored several research papers in the many reputed journals and conferences. He has undertaken a number of major research and development government sponsored and private projects. He is a member of various societies like the Computer Society of India, IEEE.
Prof. Uday Pratap Singh is a Professor in the Department of Mathematics, Central University of Jammu, Jammu, India. He completed his BSc and MSc (Mathematics and Statistics) from Dr. R.M.L. (Avadh) University, Ayodhya, India, and again did his MSc (Mathematics and Computing) from Indian Institute of Technology, Guwahati, India, and a PhD in Computer Science from Barkatullah University, Bhopal. His areas of interest include Soft Computing, Nonlinear Systems, and Image Processing. He had authored several research papers in the many reputed journals and conferences. He is a life member of Soft Computing Research Society (SCRC), Barata Ganita Parishad, Computer Society of India and Member of IEEE and AMS.
Prof. Akash Saxena has a PhD and Master of Technology degree (with Honours) in Electrical Engineering from Malaviya National Institute of Technology, Jaipur in 2015 and 2008 respectively and a Bachelor of Engineering degree (with Honours) in Electrical Engineering from Engineering College Kota in 2001. Prof Saxena is working as (Director of Training and Placement) and Professor in Department of Electrical Engineering Central University of Haryana, India with almost two decades of teaching experience. As an academician, he has been associated with numerous institutions. He is a member of Doctoral Research Committee and a member of the Board of Studies. He has presented his research work at various platforms to showcase his findings to fellow researchers and provide a pathway to the future researchers. His works have been published in leading journals in the form of short communication/letters /articles/research papers.
Prof. Akhilesh Tiwari is a Professor in Department of Information Technology, MITS Gwalior, MP, India. He has a Bachelor degree and Master's degree in Information Technology from RGPV Bhopal, India, and a PhD in Information Technology. His area of research interests includes Knowledge Discovery in Databases & Data Mining, Terrorist Network Mining, Hesitation Mining and Pattern Warehousing. He has published more than 80 research papers in reputed journals and conferences published by leading publishers with SCI, SCIE and SCOPUS indexing.
Prof. Sanjeev Jain is a Vice Chancellor of the Central University of Jammu, India. He has a Master's degree in Computer Science and Engineering from IIT Delhi, India, in 1992, and a PhD in Computer Science and Engineering. He has over 35 years of experience in teaching, research and administration. He has the credit of making a significant contribution to research and development in the area of image processing, soft computing, IoT and mobile ad-hoc network. He had authored several research papers in the many reputed journals and conferences. He has undertaken a number of major research and development government sponsored and private projects. He is a member of various societies like the Computer Society of India, IEEE.
Content
Preface. Drone Importance and their Necessity in Future Generation Agriculture. Advances in Wildfire Spread Detection and Prediction: Techniques, Challenges, and Applications. Leveraging Remote Sensing for Agriculture Mapping: Techniques, Applications, and Future Directions. Basil Crop Detection Using Computer Vision and Deep Learning Approach. Remote Sensing for Agriculture Mapping. Advances of Remote Sensing Technologies in Agriculture: Current Progress and Future Perspectives. Remote Sensing for Sustainable Agriculture: A Machine Learning Approach to Optimizing Farm Yield and Economic Returns. Leveraging AI and CV Technologies to Advance Water Quality Assessment in Ecological Informatics. Tracing Plant Growth Patterns: Employing Artificial Intelligence and Computer Vision for Explicit Mapping. AI-Driven Circular Economy: Innovations in Agro and Food Waste Management. Advancements in Machine Learning for Water Quality Assessment. Enhancing Agricultural Support with AI in the Farmer ChatBot Framework. Federated Learning: A Game-Changer in Agricultural Decision-Making and Precision Farming. Clean Streams, Clear Futures: AI Innovations in Water Quality Monitoring. Transforming Waste into Resources: AI's Impact on Wastewater Treatment. Soil Moisture Evaluation by Artificial Intelligence and Computer Vision. Crop Yield Estimation. Soil Fertility Evaluation. Advancements in Soil Moisture Evaluation: Sensors, Remote Sensing and Artificial Intelligence. Sustainable Agriculture: Economic Perspectives on AI and ML in Crop Yield Estimation. Index.