Optimizing Artificial Intelligence and Emerging Technologies for Sustainable Agriculture
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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…mehr

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Produktbeschreibung
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.
Autorenporträt
Roheet Bhatnagar, PhD is a professor in the Department of Computer Science and Engineering at Manipal University, Jaipur with over 22 years of academic and industry experience. He has published five books and over 100 research papers in reputed conferences and journals and given numerous talks, lectures, and keynote speeches at international conferences. His research interests include soft computing, data structure, remote sensing, and software engineering.   Chandan Kumar Panda, PhD is an assistant professor at Bihar Agricultural University, Sabour with over 8 years of academic and industry experience. He has published three books, 16 book chapters, and over 50 papers in international journals and conferences and completed a number of projects for the Indian Council of Agricultural Research. 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 Department of Artificial Intelligence at Kafrelsheikh University. He has published over 70 papers and conference presentations in top-tier journals and serves as a reviewer and editor for prestigious academic journals. He specializes in artificial intelligence, machine learning, pattern recognition, and classification.