Artificial Intelligence Techniques in Smart Agriculture

This edited volume explores the integration of artificial intelligence to improve crop production. It addresses the critical need for intelligent crop management in light of the world's escalating population. Encompassing a spectrum of technologies, including computer vision, image processing, soft computing, machine learning, and deep learning, the book explores advancements in decision-making systems. It integrates data science methodologies, Internet of Things, wireless communications, and a range of sensors and actuators to provide precise, timely, and cost-effective solutions to agricultural challenges, ultimately enhancing both the quality and quantity of crop yields. The book empowers its audience to direct their efforts towards designing models and prototypes that benefit society and the environment, making it an indispensable resource for those eager to shape the future of intelligent agriculture.
It serves as a comprehensive guide for students, scholars, and academicians keen on delving into the transformative field of artificial intelligence in agriculture. Researchers, scientists, and field experts will find invaluable insights to guide their exploration and contribution to this domain.

List of contents

Chapter 1. Assessing the importance and need of Artificial Intelligence for Precision Agriculture.- Chapter 2. Challenges in Achieving Artificial Intelligence in Agriculture.- Chapter 3. Introduction to Artificial Intelligence techniques in Agricultural applications and their future aspects.- Chapter 4. Agricultural Artificial Intelligence: Obstacles and Opportunities.- Chapter 5. Smart Farming Management System: Pre and Post Production Interventions.- Chapter 6. Introduction to various intelligent devices and implementation platforms.- Chapter 7. Fruit Counting and Analysis Using Artificial Intelligence Approaches.- Chapter 8. Deep Learning-Based Plant Stress Diagnosis: An Optimized Generative Augmentation Model Approach.- Chapter 9. Transformative Impact of AI-Driven Computer Vision in Agriculture.- Chapter 10. An in-depth analysis of artificial intelligence-based crop pest management and water supply regulation.- Chapter 11. AI for Data-Driven Decision Making in Smart Agriculture: From Field to Farm Management.- Chapter 12. AI based Regulation of Water supply and Pest Management in Farming.- Chapter 13. Advancement and Challenges of Implementing Artificial Intelligence of Things in Precision Agriculture.- Chapter 14. Enabling Digital Platforms: Towards Smart Agriculture.- Chapter 15. IoT and Drone-Based Field Monitoring and Surveillance System.- Chapter 16. IoT based Real Time Farm Management System for Smart Agriculture.

About the author

Dr. Siddharth Singh Chouhan is currently working as an Assistant Professor in School of Computing Science and Engineering, VIT Bhopal University, Madhya Pradesh, India. He has completed Ph.D. in Computer Science and Engineering from Shri Mata Vaishno Devi University Katra, UT of Jammu and Kashmir, India. He is a Post Doctorate from the University of Malta, Europe. He has completed his B.Tech. and M.Tech. in Computer Science and Engineering from RGPV University, Bhopal, India. His research area includes Computer vision, Drone Technology, Deep Learning, and Precision Agriculture. He has authored several research papers published in journals of international repute and conferences.
Dr. Akash Saxena is currently working as (Director of Training and Placement) and Professor in School of Engineering & Technology, Central University of Haryana, India. He is an M.Tech. and Doctorate from Malaviya National Institute of Technology, Jaipur. Dr. Saxena is amongst the top 2% scientists of World in the field of Artificial Intelligence, this ranking is given by Stanford University and Elsevier jointly on the basis of quality publications and citation counts. His major research areas are soft computing, Computational and Artificial Intelligence with the specialization in Optimization theory. Dr. Saxena is Senior member of IEEE and Fellow of IETE.
Dr. Uday Pratap Singh is presently working as an Associate Professor in the Department of Mathematics, Central University of Jammu, India. He is also Associate Professor (EoL) in School of Mathematics, SMVDU Katra. He has obtained B.Sc. and M.Sc. (Mathematics and Statistics) Degree from Dr. R.M.L. Awadh University, Faizabad, (U.P.), India, M.Sc. (Mathematics and Computing) Degree from Indian Institute of Technology, Guwahati, India, and received Ph.D. in Computer Science from Barkatullah University, Bhopal. His area of interest includes Soft Computing, Nonlinear Systems, and Image Processing. He has authored several research papers published in 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. Sanjeev Jain is currently working as a Vice Chancellor of the Central University of Jammu. He received a Master’s degree in Computer Science and Engineering from IIT Delhi, New Delhi, India, in 1992, and a Ph.D. degree in Computer Science and Engineering. He also served various Institutions/University as a Director/ Vice Chancellor from the last 15 years and 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 image processing, Soft Computing, IoT and mobile ad-hoc network. He has authored several research papers in many reputed journals and conferences. He has undertaken several Research and Development projects sponsored by the Government and Private Agencies. He is a member of various societies like the Computer Society of India, IEEE.

Summary

This edited volume explores the integration of artificial intelligence to improve crop production. It addresses the critical need for intelligent crop management in light of the world's escalating population. Encompassing a spectrum of technologies, including computer vision, image processing, soft computing, machine learning, and deep learning, the book explores advancements in decision-making systems. It integrates data science methodologies, Internet of Things, wireless communications, and a range of sensors and actuators to provide precise, timely, and cost-effective solutions to agricultural challenges, ultimately enhancing both the quality and quantity of crop yields. The book empowers its audience to direct their efforts towards designing models and prototypes that benefit society and the environment, making it an indispensable resource for those eager to shape the future of intelligent agriculture.
It serves as a comprehensive guide for students, scholars, and academicians keen on delving into the transformative field of artificial intelligence in agriculture. Researchers, scientists, and field experts will find invaluable insights to guide their exploration and contribution to this domain.

Product details

• Assisted by: Siddharth Singh Chouhan (Editor), Sanjeev Jain (Editor), Uday Pratap Singh et al (Editor), Akash Saxena (Editor), Uday Pratap Singh (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Released: 01.10.2024
• EAN: 9789819758777
• ISBN: 978-981-9758-77-7
• No. of pages: 287
• Dimensions: 155 mm x 20 mm x 235 mm
• Weight: 578 g
• Illustrations: XXII, 287 p. 93 illus., 86 illus. in color.
• Subjects: Natural sciences, medicine, IT, technology > Biology > Agriculture, horticulture; forestry, fishing, food; Biotechnologie, Künstliche Intelligenz, Artificial Intelligence, Bildverarbeitung, agricultural biotechnology, Agriculture, Computer Imaging, Vision, Pattern Recognition and Graphics, Artificial Intelligence in Agriculture, Image Processing in agriculture, Internet of Things in agriculture, Soft Computing in agriculture, Deep Learning in agriculture