Precision Agriculture for Sustainability

ISBN-13: 9781774913734 / Twarda / 2024 / 472 str.

Opis

Covers digital technological intervention for precision agriculture for sustainable development. It delves into how modern technologies i.e., GPS, image processing, artificial intelligence, machine learning, Internet of Things, and deep learning are being used in agriculture to make it more farmer-friendly and economically profitable.

Spis treści

PART I: AI IN AGRICULTURE 1. Review of Various Technologies Involved in Precision Farming Automation 2. State-of-the-Art Technologies for Crop Health Monitoring in Modern Precision Agriculture 3. Comprehensive Study of Artificial Intelligence Techniques for Early-Stage Disease Identification System in Plants 4. Understanding the Relationship between Normalized Difference Vegetation Index and Meteorological Attribute Using Clustering Algorithm 5. Agricultural Productivity Improvement: Role of AI and Yield Prediction Using Machine Learning PART II: ROBOTIC-BASED INNOVATIONS IN AGRICULTURE 6. Comprehensive Review of Agricultural Robotics: A Post-Covid Perspective of Advanced Robotics with Smart Farming 7. Autonomous Aerial Robot Application for Crop Survey and Mapping 8. Structural Design and Analysis of 6-DOF Cylindrical Robotic Manipulators for Automated Agriculture 9. Robot-Based Weed Identification and Control System 10. Design and Development of a Quadruped Robot for Precision Agriculture Applications 11. Design and Fabrication of a Solar-Powered Bluetooth-Controlled Multi-Purpose Agro Machine PART III: INTELLIGENT COMPUTING IN AGRICULTURE 12. Machine Learning and Deep Learning Methods for Yield Forecasting 13. Supervised Machine Learning for Crop Health Monitoring System 14. Analyzing the Effect of Climate Change on Crop Yield Over Time Using Machine Learning Techniques 15. Deep Learning Techniques for Crop Nutrient Deficiency Detection: A Comprehensive Survey 16. Plant Disease Detection Techniques: A Survey PART IV: IoT IN AGRICULTURE 17. Internet of Things Enabled Precision Agriculture for Sustainable Rural Development 18. Internet of Things: A Growing Trend in India’s Agriculture and Linking Farmers to Modern Technology 19. IoT-Based Condition Monitoring System for Plantation 20. Smart Farming Based on IoT Edge Computing: Applying Machine Learning Models for Disease and Irrigation Water Requirement Prediction in Potato Crop Using Containerized Microservices 21. Smart Sensors for Soil Health Monitoring 22. An IoT-Aided Smart Agritech System for Crop Yield Optimization 23. FATEH: A Novel Framework for Internet of Things based Smart Agriculture Monitoring System

O autorze

Narendra Khatri, PhD, Postdoc, is Assistant Professor at Department of Mechatronics, Manipal Institute of Technology, Manipal, India. He worked as a Postdoctoral Research Associate (Agri-drones) at the World Bank and the Indian Council of Agricultural Research, a New Delhi-sponsored project under NAHEP-CAAST-DFSRDA, Centre of Excellence for Digital Farming Solution for Enhancing Productivity Using Robots, Drones, and AGVs at VNMKV, Parbhani, India. He was awarded a research fellowship on a project titled "Smart Embedded Control System for Energy Independent Waste Water Treatment Plant" Dr. Khatri is Member IEEE, LM-ISTE, and Faculty Advisor IEEE Robotics and Automation Society Student Branch Manipal. He has published various International Journal articles and conference papers. He is a peer reviewer of IEEE Systems,Elsevier’s Water Research, Environmental Pollution and Bioavailability, Journal of Water Process Engineering, MDPI’s Sustainability, Agriculture, etc. Dr. Khatri was awarded a best paper presentation award at RATE-2013 and NSEC-2014.

Ajay Kumar Vyas, PhD, is Assistant Professor, Department of Information and Communication Technology, Adani Institute of Infrastructure Engineering, Ahmedabad, India. He is a senior member of IEEE, a life member of ISTE, senior member of IACSIT (Singapore) and the Internet Society (USA), senior member of the Institute of Research Engineers and Doctors, USA. He has published books and research articles with internationally renowned publishers and journals. He is a certified peer reviewer with the Elsevier Researcher Academy and the Publons Academy. He is a reviewer and editorial board member of several peer-review journals of IEEE, Springer, OSA, IET, Inderscience, Chinese Journal of Electrical Engineering, and IGI Global USA. He has completed skill development courses at Harvard Business School, USA. He earned his PhD from Maharana Pratap University of Agriculture and Technology, Udaipur, India.

Celestine Iwendi, PhD, is a visiting Professor with Coal City University, Enugu, Nigeria, and Associate Professor (Senior Lecturer) with the School of Creative Technologies, University of Bolton, United Kingdom. He is also a Fellow of the Higher Education Academy, United Kingdom, and a Fellow of the Institute of Management Consultants. Other assignments include Adjunct Professor at Delta State Polytechnic, Nigeria. He is a distinguished speaker at ACM and a senior member of IEEE and the Swedish Engineers, as well as a member of ACM, IEEE Computational Intelligence Society, Nigeria Society of Engineers, and Smart Cities Community. He is currently serving as the newsletter editor and a board member of IEEE, Sweden section. He was awarded a grant for principal excellence fund at the University of Aberdeen 2011.

Prasenjit Chatterjee, PhD, is currently a Professor of Mechanical Engineering and Dean (Research and Consultancy) at MCKV Institute of Engineering, West Bengal, India. He has over 4100 citations and 120 research papers in various international journals and peer-reviewed conferences. He has authored and edited more than 25 books on intelligent decision-making, fuzzy computing, supply chain management, optimization techniques, risk management, and sustainability modelling. He has received numerous awards, including best track paper awards, outstanding reviewer awards, best paper awards, outstanding researcher awards, and university gold medals. Dr. Chatterjee is the Editor-in-Chief of the Journal of Decision Analytics and Intelligent Computing. He has also been a guest editor of several special issues in different SCIE/Scopus/ESCI (Clarivate Analytics) indexed journals. He is also the Lead Series Editor of Smart and Intelligent Computing in Engineering (Chapman and Hall/CRC Press); Founder and Lead Series Editor of Concise Introductions to AI and Data Science (Scrivener – Wiley); AAP Research Notes on Optimization and Decision Making Theories; Frontiers of Mechanical and Industrial Engineering (Apple Academic Press, co-published with CRC Press, Taylor and Francis Group) and River Publishers Series in Industrial Manufacturing and Systems Engineering. Dr. Chatterjee is one of the developers of two multiple-criteria decision-making methods called Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI).