Internet of Things and Machine Learning in Agriculture
Description
Agriculture is one of the most fundamental human activities. As the farming capacity has expanded, the usage of resources such as land, fertilizer, and water has grown exponentially, and environmental pressures from modern farming techniques have stressed natural landscapes. Still, by some estimates, worldwide food production needs to increase to keep up with global food demand. Machine Learning and the Internet of Things can play a promising role in the Agricultural industry, and help to increase food production while respecting the environment. This book explains how these technologies can be applied, offering many case studies developed in the research world.
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Persons
Jyotir Moy Chatterjee , LBEF, Nepal; Abhishek Kumar , CUIET, India; P. S. Rathore , ACERC, India; Vishal Jain , Sharda University, India
Content
- Intro
- Preface
- Acknowledgments
- Contents
- List of contributors
- Part I: Machine learning and Internet of things in agriculture
- 1 Smart farming: using IoT and machine learning techniques
- 2 Food security and farming through IoT and machine learning
- 3 An innovative combination for new agritechnological era
- 4 Recent advancements and challenges of artificial intelligence and IoT in agriculture
- 5 Technological impacts and challenges of advanced technologies in agriculture
- Part II: Applications of Internet of things in agriculture
- 6 IoT-based platform for smart farming - Kaa
- 7 Internet of things platform for smart farming
- 8 Internet of things platform for smart farming
- 9 Internet of things platform for smart farming
- Part III: Applications of machine learning in agriculture
- 10 Kisan-e-Mitra: a tool for soil quality analyzer and recommender system
- 11 Artificial intelligence for plant disease detection: past, present, and future
- 12 Wheat rust disease identification using deep learning
- 13 Image-based hibiscus plant disease detection using deep learning
- 14 Rainfall prediction by applying machine learning technique
- 15 Plant leaf disease classification based on feature selection and deep neural network
- 16 Using deep learning for image-based plant disease detection
- 17 Using deep learning for image-based plant disease detection
- 18 Using deep learning for image-based plant disease detection
- Index
