1st Edition

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

    506 Pages 24 Color & 249 B/W Illustrations
    by Apple Academic Press

    506 Pages 24 Color & 249 B/W Illustrations
    by Apple Academic Press

    This new book 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 to make agriculture more farmer-friendly and more economically profitable. The volume focuses on the use of smart sensors, actuators, and decision support systems to provide intelligent data about crop health and for monitoring for yield prediction, soil quality, nutrition requirement prediction, etc. The authors discuss robotic-based innovations in agriculture, soft computing methodologies for crop forecasting, machine learning techniques to classify and identify plant diseases, deep convolutional neural networks for recognizing nutrient deficiencies, and more.


    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


    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.


    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


    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


    Narendra Khatri, PhD, is Assistant Professor of Mechatronics at the Manipal Institute of Technology, India. He previously worked on a project for the Centre of Excellence for Digital Farming Solution for Enhancing Productivity Using Robots, Drones, and AGVs. He has published international journal articles and conference papers and is a peer reviewer for several journals.

    Ajay Kumar Vyas, PhD,  is Associate Professor of Information and Communication Technology at the Adani Institute of Infrastructure Engineering, India. He has published books and research articles and is a certified peer reviewer and an editorial board member of several journals.

    Celestine Iwendi, PhD,  is a visiting Professor with Coal City University, Nigeria, and Associate Professor with the School of Creative Technologies at the University of Bolton, UK. He is also a Fellow of the Higher Education Academy and the Institute of Management Consultants. He is a board member of IEEE, Sweden section.

    Prasenjit Chatterjee, PhD, a Professor of Mechanical Engineering and Dean (Research and Consultancy) at MCKV Institute of Engineering, India. A prolific author and editor, he has published many well-cited research papers and more than 35 books. Dr. Chatterjee is Editorin- Chief of the Journal of Decision Analytics and Intelligent Computing and an editor for several book series.