Artificial Intelligence and Smart Agriculture Applications
  1. 335 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

About this book

An essential resource work for understanding how to design and develop smart applications for present and future problems of the field of agriculture. — Dr. Deepak Gupta, Maharaja Agrasen Institute of Technology, Delhi, India

As a result of the advances in Artificial Intelligence (AI), many aspects of daily life have been transformed by smart digital technology. Advanced intelligent algorithms can provide powerful solutions to real-world problems. Smart applications have become commonplace. All areas of life are being changed by smart tools developed to deal with complex issues challenging both humanity and the earth.

Artificial Intelligence and Smart Agriculture Applications presents the latest smart agriculture applications developed across the globe. It covers a broad array of solutions using data science and AI to attack problems facing agriculture worldwide.

Features:

  • Application of drones and sensors in advanced farming
  • A cloud-computing model for implementing smart agriculture
  • Conversational AI for farmer's advisory communications
  • Intelligent fuzzy logic to predict global warming's effect on agriculture
  • Machine learning algorithms for mapping soil macronutrient elements variability
  • A smart IoT framework for soil fertility enhancement
  • AI applications in pest management
  • A model using Python for predicting rainfall

The book examines not only present solutions but also potential future outcomes. It looks at the role of AI-based algorithms and the almost infinite combinations of variables for agricultural applications. Researchers, public and private sector representatives, agriculture scientists, and students can use this book to develop sustainable and solutions for smart agriculture. This book's findings are especially important as the planet is facing unprecedented environmental challenges from over-farming and climate change due to global warming.

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Yes, you can access Artificial Intelligence and Smart Agriculture Applications by Utku Kose, V.B. Surya Prasath, M.Rubaiyat Hossain Mondal, Prajoy Podder, Subrato Bharati, Utku Kose,V.B. Surya Prasath,M.Rubaiyat Hossain Mondal,Prajoy Podder,Subrato Bharati in PDF and/or ePUB format, as well as other popular books in Computer Science & Information Technology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Half-Title Page
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Foreword
  7. Preface
  8. Acknowledgments
  9. Editors
  10. Contributors
  11. 1 Application of Drones and Sensors in Advanced Farming: The Future Smart Farming Technology
  12. 2 Development and Research of a Greenhouse Monitoring System
  13. 3 A Cloud-Computing Model for Implementing Smart Agriculture
  14. 4 Application of Conversational Artificial Intelligence for Farmer’s Advisory and Communication
  15. 5 The Use of an Intelligent Fuzzy Logic Controller to Predict the Global Warming Effect on Agriculture: Case of Chickpea (Cicer arietinum L.)
  16. 6 Using Machine Learning Algorithms to Mapping of the Soil Macronutrient Elements Variability with Digital Environmental Data in an Alluvial Plain
  17. 7 A Smart IoT Framework for Soil Fertility Enhancement Assisted via Deep Neural Networks
  18. 8 Plant Disease Detection with the Help of Advanced Imaging Sensors
  19. 9 Artificial Intelligence-Aided Phenomics in High-Throughput Stress Phenotyping of Plants
  20. 10 Plant Disease Detection Using Hybrid Deep Learning Architecture in Smart Agriculture Applications
  21. 11 Classification of Coffee Leaf Diseases through Image Processing Techniques
  22. 12 The Use of Artificial Intelligence to Model Oil Extraction Yields from Seeds and Nuts
  23. 13 Applications of Artificial Intelligence in Pest Management
  24. 14 Applying Clustering Technique for Rainfall Received by Different Districts of Maharashtra State
  25. 15 Predicting Rainfall for Aurangabad Division of Maharashtra by Applying Auto-Regressive Moving Average Model (ARIMA) Using Python Programming
  26. Index