Artificial Intelligence and Computer Vision for Ecological Informatics (eBook, PDF)

Redaktion: Chouhan, Siddharth Singh; Jain, Sanjeev; Tiwari, Akhilesh; Saxena, Akash; Singh, Uday Pratap

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 402
• Erscheinungstermin: 27. August 2025
• Englisch
• ISBN-13: 9781040453025
• Artikelnr.: 74943030

Autorenporträt

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.

Inhaltsangabe

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.