Name: Sustainable Farming Through Machine Learning (Artificial Intelligence for Sustainable Engineering and Management) (en Inglés)
SKU: 63320215
Price: 104.13 USD
Availability: InStock
Author: Satpathy Suneeta,Kumar Paikaray Bijay,Yang Ming

portada Sustainable Farming Through Machine Learning (Artificial Intelligence for Sustainable Engineering and Management) (en Inglés)

Sustainable Farming Through Machine Learning (Artificial Intelligence for Sustainable Engineering and Management) (en Inglés)

Formato

Libro Físico

Editorial

Crc Press

Autor

Satpathy Suneeta,Kumar Paikaray Bijay,Yang Ming

Idioma

Inglés

N° páginas

300

Encuadernación

Tapa Dura

ISBN13

9781032777498

N° edición

Sustainable Farming Through Machine Learning (Artificial Intelligence for Sustainable Engineering and Management) (en Inglés)

Satpathy Suneeta,Kumar Paikaray Bijay,Yang Ming (Autor) · Crc Press · Tapa Dura

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Reseña del libro "Sustainable Farming Through Machine Learning (Artificial Intelligence for Sustainable Engineering and Management) (en Inglés)"

This book explores the transformative potential of machine learning (ML) technologies in agriculture. It delves into specific applications, such as crop monitoring, disease detection, and livestock management, demonstrating how artificial intelligence/machine learning (AI/ML) can optimize resource management and improve overall productivity in farming practices.Sustainable Farming through Machine Learning: Enhancing Productivity and Efficiency provides an in-depth overview of AI and ML concepts relevant to the agricultural industry. It discusses the challenges faced by the agricultural sector and how AI/ML can address them. The authors highlight the use of AI/ML algorithms for plant disease and pest detection and examine the role of AI/ML in supply chain management and demand forecasting in agriculture. It includes an examination of the integration of AI/ML with agricultural robotics for automation and efficiency. The authors also cover applications in livestock management, including feed formulation and disease detection; they also explore the use of AI/ML for behavior analysis and welfare assessment in livestock. Finally, the authors also explore the ethical and social implications of using such technologies.This book can be used as a textbook for students in agricultural engineering, precision farming, and smart agriculture. It can also be a reference book for practicing professionals in machine learning, and deep learning working on sustainable agriculture applications.