Computational Intelligence and Image Processing in Agriculture: Applications and Innovations

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 Agriculture 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.

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.