IoT and AI in Agriculture (eBook)
XVII, 461 Seiten
Springer Nature Singapore (Verlag)
978-981-19-8113-5 (ISBN)
Tofael Ahamed is an Associate Professor, at the Faculty of Life and Environmental Sciences, the University of Tsukuba, which is one of the leading universities in Japan. Dr. Ahamed performs research in the field of precision agriculture technology, agricultural robotics, and decision support systems. He focuses on enabling smart applicationsusing the Internet of Things (IoT) and Artificial Intelligence (AI) in agriculture, where crop production varies spatially and temporally within the field boundaries depending on the soil and environmental conditions. Dr. Ahamed is also member of the American Society of Agricultural and Biological Engineers, Japanese Society of Agricultural Machinery, Food Engineers, Japanese Society of Agricultural Information, and Japan Section of Regional Science Association. He is also serving as one of the Associate Editors for Computer and Electronics in Agriculture, Agricultural Information Research, Editorial Member for Asia-Pacific Journal of Regional Science, Author and Editor of serval books and Guest Editor of special issues for Remote Sensing.
This book reviews recent innovations in the smart agriculture space that use the Internet of Things (IoT) and sensing to deliver Artificial Intelligence (AI) solutionsto agricultural productivity in the agricultural production hubs. In this regard, South and Southeast Asia are one of the major agricultural hubs of the world, facing challenges of climate change and feeding the fast-growing population. To address such challenges, a transboundary approach along with AI and BIG data for bioinformatics are required to increase yield and minimize pre- and post-harvest losses in intangible climates to drive the sustainable development goal (SDG) for feeding a major part of the 9 billion population by 2050 (Society 5.0 SDG 1 & 2). Therefore, this book focuses on the solution through smart IoT and AI-based agriculture including pest infestation and minimizing agricultural inputs for in-house and fields production such as light, water, fertilizer and pesticides to ensure food security aligns with environmental sustainability. It provides a sound understanding for creating new knowledge in line with comprehensive research and education orientation on how the deployment of tiny sensors, AI/Machine Learning (ML), controlled UAVs, and IoT setups for sensing, tracking, collection, processing, and storing information over cloud platforms for nurturing and driving the pace of smart agriculture in this current time. The book will appeal to several audiences and the contents are designed for researchers, graduates, and undergraduate students working in any area of machine learning, deep learning in agricultural engineering, smart agriculture, and environmental science disciplines. Utmost care has been taken to present a varied range of resource areas along with immense insights into the impact and scope of IoT, AI and ML in the growth of intelligent digital farming and smart agriculture which will give comprehensive information to the targeted readers.
Erscheint lt. Verlag | 10.4.2023 |
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Zusatzinfo | XVII, 461 p. 1 illus. |
Sprache | englisch |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Naturwissenschaften ► Biologie ► Ökologie / Naturschutz | |
Naturwissenschaften ► Geowissenschaften | |
Weitere Fachgebiete ► Land- / Forstwirtschaft / Fischerei | |
Schlagworte | Data Driven System • Deep learning • Digital Agriculture • machine learning • Smart Agriculture • Smart Farming |
ISBN-10 | 981-19-8113-2 / 9811981132 |
ISBN-13 | 978-981-19-8113-5 / 9789811981135 |
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