Data-Driven Farming: Harnessing the Power of AI and Machine Learning in Agriculture

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Syed Nisar Hussain Bukhari

Data-Driven Farming

Harnessing the Power of AI and Machine Learning in Agriculture

Syed Nisar Hussain Bukhari

$103

Paperback

Forthcoming
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English

Auerbach
13 June 2024

Agriculture & related industries; Automatic control engineering; Agricultural science; Artificial intelligence

In the dynamic realm of agriculture, artificial intelligence (AI) and machine learning (ML) emerge as catalysts for unprecedented transformation and growth. The emergence of big data, Internet of Things (IoT) sensors, and advanced analytics has opened up new possibilities for farmers to collect and analyze data in real-time, make informed decisions, and increase efficiency. AI and ML are key enablers of data-driven farming, allowing farmers to use algorithms and predictive models to gain insights into crop health, soil quality, weather patterns, and more. Agriculture is an industry that is deeply rooted in tradition, but the landscape is rapidly changing with the emergence of new technologies.

Data-Driven Farming: Harnessing the Power of AI and Machine Learning in Agriculture is a comprehensive guide that explores how the latest advances in technology can help farmers make better decisions and maximize yields. It offers a detailed overview of the intersection of data, AI, and ML in agriculture and offers real-world examples and case studies that demonstrate how these tools can help farmers improve efficiency, reduce waste, and increase profitability. Exploring how AI and ML can be used to achieve sustainable and profitable farming practices, the book provides an introduction to the basics of data-driven farming, including an overview of the key concepts, tools, and technologies. It also discusses the challenges and opportunities facing farmers in today’s data-driven landscape. Covering such topics as crop monitoring, weather forecasting, pest management, and soil health management, the book focuses on analyzing data, predicting outcomes, and optimizing decision-making in a range of agricultural contexts.

Edited by: Syed Nisar Hussain Bukhari
Imprint: Auerbach
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 560g
ISBN: 9781032778723
ISBN 10: 1032778725
Pages: 282
Publication Date: 13 June 2024
Audience: College/higher education , Primary
Format: Paperback
Publisher's Status: Forthcoming

Dr. Syed Nisar Hussain Bukhari holds a PhD in Computer Science from Chandigarh University India. His research interests include artificial intelligence and machine learning, deep learning, applying AI and ML in interdisplinary areas like Agriculture, Health care. His other work areas are bioinformatics, Immunoinformatics and computational biology and has taught courses on Artificial Intelligence and Machine Learning at UG and PG level. He has a proven experience of providing expert advice on the use of technology in different domain.