Overview
- Covers key technologies and techniques such as IoT, AI, and ML in the development of smart agriculture
- Provides information for different types of hardware, platforms, and machine learning techniques used in smart farming
- Presents examples and exercises in each chapter
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About this book
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.
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Table of contents (23 chapters)
Editors and Affiliations
About the editor
Bibliographic Information
Book Title: IoT and AI in Agriculture
Book Subtitle: Self- sufficiency in Food Production to Achieve Society 5.0 and SDG's Globally
Editors: Tofael Ahamed
DOI: https://doi.org/10.1007/978-981-19-8113-5
Publisher: Springer Singapore
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023
Hardcover ISBN: 978-981-19-8112-8Published: 11 April 2023
Softcover ISBN: 978-981-19-8115-9Published: 12 April 2024
eBook ISBN: 978-981-19-8113-5Published: 10 April 2023
Edition Number: 1
Number of Pages: XVII, 461
Number of Illustrations: 1 b/w illustrations
Topics: Agriculture, Machine Learning, Sustainable Development