Application of Machine Learning in Agriculture

Erscheinungsjahr 2022
ISBN: 978-0-323-90550-3
Verlag: Elsevier Science & Technology

Buch, Englisch, 330 Seiten, Format (B × H): 193 mm x 236 mm, Gewicht: 732 g

Application of Machine Learning in Smart Agriculture is the first book to present a multidisciplinary look at how technology can not only improve agricultural output, but the economic efficiency of that output as well. Through a global lens, the book approaches the subject from a technical perspective, providing important knowledge and insights for effective and efficient implementation and utilization of machine learning.

As artificial intelligence techniques are being used to increase yield through optimal planting, fertilizing, irrigation, and harvesting, these are only part of the complex picture which must also take into account the economic investment and its optimized return. The performance of machine learning models improves over time as the various mathematical and statistical models are proven. Presented in three parts, Application of Machine Learning in Smart Agriculture looks at the fundamentals of smart agriculture; the economics of the technology in the agricultural marketplace; and a diverse representation of the tools and techniques currently available, and in development.

This book is an important resource for advanced level students and professionals working with artificial intelligence, internet of things, technology and agricultural economics.

Autoren/Hrsg.

Khan, Mohammad Ayoub (Associate

Khan, Mohammad Ayoub

Khan, Rijwan

Ansari, Mohammad Aslam (Scientist

Ansari, Mohammad Aslam

Fachgebiete

• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Primärer Sektor Agrarökonomie, Ernährungswirtschaft
• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften Agrartechnik, Landmaschinen

Inhaltsverzeichnis

Part 1: Fundamentals of Smart Agriculture
1. Machine learning based Agriculture
2. Monitoring agriculture essentials
3. Livestock management in agriculture

Part 2: Market, Technology and products
4. Agriculture Economics
5. Digital Marketing and its impact
6. Technology and products

Part 3: Tools and Techniques
7. Modeling Techniques used in Smart Agriculture
8. Diseases detection
9. Food Security
10. Medicines Care Management
11. Detection and diagnosis of plant diseases
12. Machine Learning Technique for agriculture image recognition

Über Autor(innen)

Khan, Rijwan
Rijwan Khan is Professor and Head of Department of Computer Science at the ABES Institute of Technology in Uttar Pradesh, India.

Khan, Mohammad Ayoub
Mohammad Ayoub Khan is Associate Professor at the University of Bisha in Bisha, Saudi Arabia.

Ansari, Mohammad Aslam
Scientist Professor, Department of Agriculture Communication, College of Agriculture, G B Pant University of Agriculture and Technology, Pantnagar (Uttarakhand). Post-doctoral studies at University of Leicester (UK). Received Senior Research Fellowship during doctoral studies and UNDP/ICAR scholarship during post-graduation at Pantnagar University. He is chairman of the editorial board of Indian Journal of Science Communication and has nearly 25 years' experience in different capacities in corporate, governmental, NGO and Academic institutions. He has worked in that time has included focuse on the use of technologies in agricultural settings, including the use of mobile phones, e-learning, and internet use. His research interests include ICT applications in agriculture and rural development, Development Communication, Training, Health Communication and Science Communication.