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Application of Machine Learning in Agriculture - Research Book

Application of Machine Learning in Agriculture - Research Book

Good Research Book in Application of Machine Learning in Agriculture

Author(s) Name:  Mohammad Khan, Rijwan Khan, Mohammad Ansari

About the Book:

   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.

Table of Contents

  • Chapter 1. Machine learning-based agriculture
  • Chapter 2. Monitoring agricultural essentials
  • Chapter 3. Machine learning-based remote monitoring and predictive analytics system for monitoring and livestock monitoring
  • Chapter 4. Agricultural economics
  • Chapter 5. Current and prospective impacts of digital marketing on the small agricultural stakeholders in the developing countries
  • Chapter 6. Intelligent farming system through weather forecast support and crop production
  • Chapter 7. Deep learning-based prediction for stand age and land utilization of rubber plantation
  • Chapter 8. Modeling techniques used in smart agriculture
  • Chapter 9. Plant diseases detection using artificial intelligence
  • Chapter 10. A deep learning-based approach for mushroom diseases classification
  • Chapter 11. Smart fence to protect farmland from stray animals
  • Chapter 12. Enhancing crop productivity through autoencoder-based disease detection and context-aware remedy recommendation system
  • Chapter 13. UrbanAgro: Utilizing advanced deep learning to support Sri Lankan urban farmers to detect and control common diseases in tomato plants
  • Chapter 14. Machine learning techniques for agricultural image recognition

    • ISBN:  9780323905503

    Publisher:  Elsevier

    Year of Publication:  2022

    Book Link:  Home Page Url