Artificial Intelligence in Animal Science, Volume 1
Description
This book explores how AI technologies are transforming animal agriculture. This edited volume integrates research, practical applications, and interdisciplinary perspectives, showcasing AI's role in feed optimization, disease prediction, livestock monitoring, and animal welfare. It captures the digital shift in global farming, offering insights into building intelligent systems for sustainable animal production.
The book's foundation lies in the urgent need to merge animal science with AI-driven engineering to address food security, environmental sustainability, and rural development. By bridging computer science, biology, and agricultural engineering, it lays a robust framework for leveraging AI in modern animal husbandry. This background is critical to understanding how traditional farming methods are evolving into data-centric, efficient, and ethical systems that benefit farmers, animals, and consumers alike.
Spanning ten comprehensive chapters, the book covers the fundamentals of animal science and AI methodologies, practical applications in health management, reproduction, and smart farming technologies. It addresses ethical considerations, data management, and real-world challenges, while projecting future trends such as robotics and climate-smart practices. Each chapter provides both theoretical depth and case studies, making it a holistic resource for advancing intelligent animal farming.
This volume targets researchers, agritech innovators, veterinarians, and policymakers invested in the future of animal agriculture. It is essential for those seeking to harness AI to improve productivity, welfare, and sustainability in livestock systems, fostering interdisciplinary collaboration and innovation across sectors.
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Persons
Dr. R.L. Yadava is a Professor in Electronics and Communication Engineering at Galgotias College of Engineering and Technology (GCET), Greater Noida. He holds a Ph.D. from IIT-BHU and M.Tech, M.Sc., and B.Sc. degrees. He began his career at VIT University, Vellore, as Head of Microwave Division and R&D Coordinator and served as visiting faculty at Kigali Institute of Science and Technology, Rwanda. At GCET, he has been M.Tech Coordinator, HOD, and Head of Exams. His research spans microwave communication, IoT, AI, and their applications in biomedical and biosensing systems. He focuses on Specific Absorption Rate (SAR) and cancer imaging, with 150+ publications and guidance to five Ph.D. scholars. He is associate editor/reviewer for reputed journals and a member of IEEE, EAI, ISTE, and SEMCE(I). He received AKTU's Best Teacher Award in 2024 for excellence in teaching, research, and leadership.
Ajeet Kumar Bharttee is an Assistant Professor at Sanskaram University with over 18 years in academia and industry. He served at Galgotias College (2011-2025) and other institutions and worked as a J2EE software developer for two years. Currently pursuing a Ph.D. in Computer Science at NIT Uttarakhand, he holds an M.Tech. (CDAC-Noida, 2007) and B.E. (M.M.M. Engineering College, 2001). His teaching interests include Soft Computing, Deep Learning, Algorithms, Computer Architecture, and Parallel Computing. He focuses on AI applications in animal science, aiming to enhance animal health and behavior research. He also handles administrative duties that support AI integration in this field.
Dr. Uttam Sarkar, former Head and Assistant Professor, Department of Animal Genetics & Breeding, WBUAFS, has over 13 years of teaching and 6 years of field experience. He earned his Ph.D. from ICAR-NDRI, focusing on molecular and quantitative genetics, biostatistics, and livestock improvement-especially in small ruminants, cattle, buffalo, and poultry. He has authored 39 research articles, two review papers, and led DBT and ICAR-funded projects. Dr. Sarkar also held field roles in hospital management and livestock development and holds a Diploma in Computer Language. He is actively involved in professional bodies like the Indian Society of Animal Genetics and Breeding and the Indian Veterinary Association, bridging research, teaching, and rural outreach.
Dr. Alok K. Wankar, MVSc, Ph.D. (Veterinary Physiology, ICAR-IVRI), is an Assistant Professor at the College of Veterinary & Animal Sciences, MAFSU, Parbhani. His expertise includes heat stress physiology, endocrinology, and climate-resilient livestock production. His Ph.D. focused on thermal stress and gas emissions in buffaloes, and his MVSc work explored neem leaf powder's effects on broiler immunity. With academic roles since 2012, Dr. Wankar is a recognized PG guide and holds a patent on microbial-mediated immune enhancement. Awards include the Outstanding Faculty Mentor (2024-25) and National Research Excellence Award (2023-24). He is affiliated with ISROSET, SAPI, APA, and other bodies, contributing to climate-focused veterinary science.
Dr. Rajasekhar Tellabati, Ph.D. in Dairy Engineering (ICAR-NDRI), is an Assistant Professor at the College of Dairy Technology, Sri Venkateswara Veterinary University, Andhra Pradesh, since 2012. He brings over 12 years of both industry and academic experience in dairy, food, bakery, and tobacco sectors. His research includes 13 scientific papers, 22 popular articles, and a book chapter. Honors include Best Paper Award (Indian Dairy Association), Hari Ohm Ashram Award (Sardar Patel University), and the NutriScholars Award (2020) for a high-protein shake premix. He has developed innovations like the Smart Milk-Can and dairy processing tools. Dr. Tellabati is a life member of ISTE, IDEA, ISAE, AFST(I), and IDA, contributing actively to dairy technology and education.
Content
Chapter 1. AI in Animal Science- An Introduction.- Chapter 2. Fundamentals of Animal Science for AI Applications.- Chapter 3. Core Methodologies in Artificial Intelligence and Machine Learning.- Chapter 4. AI Approaches in Animal Monitoring and Health Management.- Chapter 5. AI Approaches for Livestock Reproduction and Animal Breeding.- Chapter 6. Sensor Networks and IoT in Smart Animal Farming.- Chapter 7. Data Management in AI-Enabled Animal Science.- Chapter 8. Ethics, Privacy, and Legal Frameworks in Human-Animal Interactions.- Chapter 9. Overcoming Challenges with AI Approaches in Animal Science.- Chapter 10. Prospective Developments and Technological Trends in Animal Science.