
IoT and Advanced Intelligence Computation for Smart Agriculture
- English
- ePUB (mobile friendly)
- Available on iOS & Android
IoT and Advanced Intelligence Computation for Smart Agriculture
About this book
Smart agriculture is an approach to maintaining nature without compromising the basic needs of future generations while at the same time improving the efficiency of farming. The main achievements of smart agriculture in terms of sustainable agriculture are crop rotation, controlling nutrient deficiencies in crops, pest and disease control, recycling, and water harvesting, leading to a safer environment overall. Living organisms depend on the nature of biodiversity and are exposed to pollution due to waste emissions, use of fertilizers and pesticides, degraded dead plants, and so on. The emission of greenhouse gases affects plants, animals, humans, and the environment; hence, this necessitates a better environment for living organisms.
The purpose of this book is to provide a comprehensive overview of the latest advancements, challenges, and potential applications of artificial intelligence (AI) technology and the Internet of Things (IoT) in the future of intelligent agriculture. The book is primarily focused on equipping younger researchers, graduates, and professionals in the industry with the necessary knowledge to understand the advantages of AI technology, machine learning, and data analytics methods in improving current agricultural practices.
Key features include the following:
- The book showcases the latest advancements in AI and smart agriculture technologies
- The text emphasizes sustainable practices supported by AI, highlighting how technology can enhance productivity while minimizing environmental impact
- Readers will learn how to harness big data and analytics to drive informed decision-making and optimize their agricultural yields
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Information
Table of contents
- Cover
- Half Title
- Title
- Copyright
- Contents
- Editors
- Contributors
- Chapter 1 Smart Farming: An IoT-Enhanced and Interpretable Optimal Crop Selection Technique Based on Soil and Environmental Data
- Chapter 2 Enhanced Date Palm Seed Classification Using Genetic Algorithms and XGBoost
- Chapter 3 IoT-Based Precision Agriculture with Integrated Security for Smart Farming
- Chapter 4 Dynamic Texture Classification Using ConvLSTM and Video Optical Flow Analysis: A Case Study
- Chapter 5 Digital Guardians: Revolutionizing Pest Management with AI and IoT for a Greener Future
- Chapter 6 Artificial Intelligence: Technological Revolution for Moroccan Agriculture
- Chapter 7 Utilizing IoT and AI for Soil Health Monitoring and Enhancement in Sustainable Agriculture
- Chapter 8 Leveraging IoT for Wildlife Deterrence: Smart Solutions for Crop Protection in Modern Farming
- Chapter 9 Advancing Water Quality Assessment through Artificial Intelligence Techniques
- Chapter 10 Aspects of IoT-Based Applications Intended for Transforming the World on a Large Scale
- Chapter 11 Smart Agro-Tech: Using IoT-Powered Intelligence and Sustainable AI Solutions to Revolutionize Crop Management
- Chapter 12 Introduction to Smart Agriculture Using IoT
- Chapter 13 Deep Feature Extraction: Comparing VGG16, ResNet50, and InceptionV3 for Image Matching
- Chapter 14 The Future of Farming: AI, ML, and IoT for Improved Crop Yields
- Index