Revolutionizing Agricultural Quality Control with AI, Image Processing, and Computational Intelligence Techniques
As the global demand for high-quality, sustainable agricultural products increases, advanced technology becomes critical in meeting these challenges. Computational Intelligence and Image Processing in Quality Evaluation of Agricultural Products explores how innovative technologies are transforming agricultural quality evaluation. Combining foundational concepts with practical applications, this comprehensive text delves into innovative techniques to improve accuracy, efficiency, and sustainability in quality control.
Addressing key challenges faced by researchers, practitioners, and industry professionals, contributions from leading experts in AI, agriculture, and computational intelligence provide a deep understanding of technologies such as deep learning, computer vision, and AI-driven robotics. Real-world examples, step-by-step tutorials, and code snippets make the concepts accessible and actionable, while coverage of emerging trends and future directions highlights the evolving landscape of agricultural technology. Offering interdisciplinary insights and practical tools to modernize evaluation techniques, reduce waste, enhance food safety, and meet the growing demands of sustainable farming practices, this book:
- Addresses challenges and solutions for real-time monitoring systems in agriculture
- Highlights cutting-edge applications such as AI-driven robotics and LiDAR in farming
- Emphasizes sustainability and environmental impact through technological innovation
- Offers detailed coverage of image analysis algorithms for quality control
- Discusses ethical and environmental implications of technology in agriculture
This book is ideal for advanced undergraduate and graduate courses in agricultural engineering, computer science, and AI applications. It is also an essential reference for professionals including agricultural scientists, AI practitioners, and quality control experts.
Preface vii
Acknowledgments ix
1 Grain Quality Assessment: Image-based Techniques for Grain Analysis,
Detecting Contaminants and Impurities and Real-world Applications 1
2 AI-driven Robotics in Agriculture 15
3 Computer Vision in Agriculture: Object Detection, Recognition, and Image
Segmentation Techniques and Advanced Image Analysis 31
4 Artificial Intelligence and Machine Learning in Agriculture: Novel
Techniques, Implementation Strategies, and Application 55
5 A Novel Approach Toward Computational Image Processing and Strategies for
Precision Agriculture 73
6 Adoption of Advanced Technologies in Soilless Modern Agriculture 97
7 Computer Vision in Agriculture 113
8 Quality Evaluation of Fruits and Vegetables 125
9 Ensuring Quality in Fruits and Vegetables: Strategies and Tools 143
10 Mapping and Validation of Fusion-based Classification of Land Use and
Land Cover Using Remote Sensing Satellite Images 155
11 Computer Vision Applications for Sustainable Agriculture 165
12 Autonomous Drones and AI Applications in Agriculture for Monitoring and
Pest Control 183
13 Using AI Robotics for Soil Analysis and Fertility Management in
Agriculture 199
14 Computational Intelligence and IoT in Transforming Agricultural
Environmental Control 213
15 Real-time Monitoring and Quality Evaluation System of Fruits and
Vegetables Using Image Processing 227
16 Computational Intelligence and Image Processing in Quality Evaluation of
Agricultural Products 245
Index 259
Jay Kumar Pandey is an Assistant Professor at Shri Ramswaroop Memorial University, India, and specializes in AI, machine learning, image processing, biomedical engineering, and renewable energy. Holding a Ph.D. and M.Tech. in Power Control, and an MBA in Finance & Marketing, he focuses on real-time imaging, surveillance, emotion recognition, driving AI solutions for healthcare, agriculture, disaster prediction, renewable energy, and advanced surveillance systems.
Mritunjay Rai is an Assistant Professor at Shri Ramswaroop Memorial University, India. He specializes in digital image processing, machine learning, and thermal imaging. His research, including a Ph.D. from IIT (ISM) Dhanbad, focuses on real-time thermal imaging, surveillance, and emotion recognition. With numerous publications and editorial contributions, he advances AI-driven solutions for healthcare, disaster prediction, and next-generation surveillance systems.
Tanmay Sarkar is currently working as a Lecturer in the Department of Food Processing Technology, Government of West Bengal. He is the top 2% global most cited researcher, by Stanford University, USA and Elsevier (2024). His research areas include AI, and food bioactive.
