Optimizing AI Applications for Sustainable Agriculture - Tapa dura

Acerca del autor

Roheet Bhatnagar, PhD is a Professor in the Department of Computer Science and Engineering at Manipal University, Jaipur, Rajasthan, India with over 22 years of experience. He has published more than 100 research papers in reputed conferences and journals and edited five books. His research focuses on soft computing, data structure, and software engineering.

Chandan Kumar Panda, PhD is an Assistant Professor at Bihar Agricultural University, Sabour, Bihar, India with over eight years of research and teaching experience. He has published three books, 16 book chapters, and more than 50 research papers in international journals and conferences. He is an acclaimed researcher in ICT in the agriculture sector. His research interests include agricultural extension, rural development, and information and communication technology in agriculture.

Mahmoud Yasin Shams, PhD is an Associate Professor of Machine Learning and Information Retrieval in the School of Artificial Intelligence, Kafrelsheikh University, Kafr el-Sheikh, Egypt. With over 70 papers and conference presentations published in top-tier journals he has made significant contributions to the field. He specializes in artificial intelligence, machine learning, pattern recognition, and classification.

De la contraportada

In an era marked by climate change, resource depletion, and population growth, innovation is not a luxury—it is a necessity. Integrating AI into agricultural practices offers a promising solution. From precision farming and crop monitoring to predictive analytics and decision support systems, artificial intelligence has the potential to revolutionize how we grow, manage, and distribute food. Optimizing Artificial Intelligence for Sustainable Agriculture is a comprehensive guide that delves into the transformative potential of artificial intelligence and emerging technologies in the field of agriculture. This volume offers an in-depth examination of various AI technologies, including machine learning, deep learning, natural language processing, and computer vision, as they apply to agricultural practices. It covers emerging technologies like the Internet of Things (IoT), drones, precision farming, and agrotechnology that are innovating the way farmers work. The primary focus is on how these technologies can enhance sustainability in agriculture by improving crop yields, reducing water consumption, minimizing chemical use, and promoting eco-friendly farming practices.