Agriculture & Allied Sciences

AAP Research Notes on Optimization and Decision Making Theories

Precision Agriculture for Sustainability
Use of Smart Sensors, Actuators, and Decision Support Systems

Editors: Narendra Khatri, PhD, Postdoc
Ajay Kumar Vyas, PhD
Celestine Iwendi, PhD
Prasenjit Chatterjee,PhD

Precision Agriculture for Sustainability

Published. Available now.
Pub Date: February 2024
Hardback Price: see ordering info
Hard ISBN: 9781774913734
E-Book ISBN: 9781003435228
Pages: 506pp w/index
Binding Type: Hardback / eBook
Series: AAP Research Notes on Optimization and Decision Making Theories
Notes: 15 color, 209 b/w illustrations

This book provides a comprehensive exploration of the aspects of the current state-of-the-art digital technological intervention for precision agriculture for sustainable agricultural development. It delves into how modern technologies—i.e., global positioning systems (GPS), unmanned aerial vehicles (drones), image processing methods, artificial intelligence, machine learning, and deep learning—are being used in agriculture to make it more farmer-friendly and more economically profitable.

The volume discusses the use of smart sensors, actuators, and decision support systems for precision agriculture that provide intelligent data about crop health and for monitoring for yield prediction, soil quality, and nutrition requirement prediction, etc., using machine learning, deep learning, and artificial intelligence through a globally connected system via the Internet of Things (IoT).

The book begins with a section on AI in agriculture that looks at using satellite data for vegetation studies, AI-based solutions to increase farmer income, satellite images for yield prediction using machine learning algorithms, and more. The second section presents robotic-based innovations in agriculture, including agricultural field robots, along with cobots (computer-controlled robotic devices designed to people) used in and outside farms and greenhouses, methods for continual robotic monitoring of crops, robot-based weed identification and control systems, and more.

The section on intelligent computing in agriculture looks at soft computing methodologies and frameworks for yield forecasting for crop production, machine learning techniques to classify and identify plant diseases, machine learning algorithms to analyze all factors affecting crop yield and the climatic effect on produce, deep convolutional neural networks (DCNNs) for recognizing nutrient deficiencies, etc. The last section explores IoT in agriculture and provides an overview of the research that has gone into making smart precision agriculture a reality, IoT applications for smart garden plantation condition monitoring, smart agriculture that makes use of cloud computing and IoT, and much more.

The book covers artificial intelligence in agriculture, robotic-based innovations in agriculture, intelligent computing in agriculture, and the Internet of Things in agriculture, providing a rich resource on this exciting and developing area.

CONTENTS:
Preface

PART I: AI IN AGRICULTURE

1. Review of Various Technologies Involved in Precision Farming Automation
Rajeev Karothia and Manju K. Chattopadhyay

2. State-of-the-Art Technologies for Crop Health Monitoring in Modern Precision Agriculture
E. Fantin Irudaya Raj, M. Appadurai, D. Thiyaharajan, and T. Lurthu Pushparaj

3. Comprehensive Study of Artificial Intelligence Techniques for Early-Stage Disease Identification System in Plants
Senthil Kumar Ramu, Leninpugalhanthi Ponnuswamy, Dhanyaa Nataraj, and Kaviyanjali Venkatachalam

4. Understanding the Relationship between Normalized Difference Vegetation Index and Meteorological Attribute Using Clustering Algorithm
Hemanta Medhi, Pramod Soni, Vikas Kumar Vidyarthi, and Shikha Chourasiya

5. Agricultural Productivity Improvement: Role of AI and Yield Prediction Using Machine Learning
Chhaya Narvekar and Madhuri Rao

PART II: ROBOTIC-BASED INNOVATIONS IN AGRICULTURE

6. Comprehensive Review of Agricultural Robotics: A Post-Covid Perspective of Advanced Robotics with Smart Farming
Nikunj S. Yagnik

7. Autonomous Aerial Robot Application for Crop Survey and Mapping
Ajay Sudhir Bale, Varsha S. N., Anish Sagar Naidu, Vinay N., and Subhashish Tiwari

8. Structural Design and Analysis of 6-DOF Cylindrical Robotic Manipulators for Automated Agriculture
Jordan Kurian Kuruvilla, Atirav Seth, Jyotishka Duttagupta, Shashwat Sharma, and Ankur Jaiswal

9. Robot-Based Weed Identification and Control System
Rashmi Bangale and Mohit Kumar

10. Design and Development of a Quadruped Robot for Precision Agriculture Applications
Sivayazi Kappagantula

11. Design and Fabrication of a Solar-Powered Bluetooth-Controlled Multi-Purpose Agro Machine
Nikhil S. Nandi, K. B. Mallikarjuna, Ashok Kumar R., Arunkumar K. H., Ajay Sudhir Bale, and Vinay N.

PART III: INTELLIGENT COMPUTING IN AGRICULTURE

12. Machine Learning and Deep Learning Methods for Yield Forecasting
Akanksha Gahoi and Vishal Gupta

13. Supervised Machine Learning for Crop Health Monitoring System
Divya Dadarya, Aditya Sinha, Anupam Agrawal, Tarun Jain, Rishi Gupta, and Rajveer Singh Shekhawat

14. Analyzing the Effect of Climate Change on Crop Yield Over Time Using Machine Learning Techniques
Heta Patel, Harish Sharma, and Varuni Sharma

15. Deep Learning Techniques for Crop Nutrient Deficiency Detection: A Comprehensive Survey
K. U. Kala, M. Nandhini, M. N. Kishore Chakkravarthi, M. Thangadarshini, and S. Madhusudhana Verma

16. Plant Disease Detection Techniques: A Survey
Dishant Sharma, Nitika Kapoor, and Divyanshi Sood

PART IV: IoT IN AGRICULTURE

17. Internet of Things Enabled Precision Agriculture for Sustainable Rural Development
Sumanta Das, Arindam Ghosh, and Sarit Pal

18. Internet of Things: A Growing Trend in India’s Agriculture and Linking Farmers to Modern Technology
Prithviraj Singh Solanki and Ganpat Joshi

19. IoT-Based Condition Monitoring System for Plantation
Arif Iqbal, Surya Prakash Singh, and Yudhishthir Pandey

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
Nitin Rathore and Anand Rajavat

21. Smart Sensors for Soil Health Monitoring
K. Shirley Kiran

22. An IoT-Aided Smart Agritech System for Crop Yield Optimization
Ujjaval Patel, Rohit Patel, and Priyank Kadecha

23. FATEH: A Novel Framework for Internet of Things based Smart Agriculture Monitoring System
Prabhdeep Singh, Kiran Deep Singh, Rajbir Kaur, Diljot Singh, and Vikas Tripathi

Index


About the Authors / Editors:
Editors: Narendra Khatri, PhD, Postdoc
Assistant Professor, Department of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India

Narendra Khatri, PhD, Postdoc, is Assistant Professor in the Department of Mechatronics at the 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 a member of 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 for 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
Assistant Professor, Department of Information and Communication Technology, Adani Institute of Infrastructure Engineering, Ahmedabad, India

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
Associate Professor (Senior Lecturer), School of Creative Technologies, University of Bolton, Bolton, UK

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
Dean (Research and Consultancy), MCKV Institute of Engineering, West Bengal, India

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).




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