کتاب تکنیک‌های هوش مصنوعی در کشاورزی هوشمند

Foreword
Preface
Acknowledgment
Contents
Editors and Contributors
About the Editors
Contributors
۱: Assessing the Importance and Need of Artificial Intelligence for Precision Agriculture
۱.۱ Introduction
۱.۱.۱ Disciplines Essential to Achieve AI
۱.۱.۲ Types of AI
۱.۱.۳ Components of AI
۱.۱.۴ Advantages of AI
۱.۱.۵ Disadvantages of AI
۱.۱.۶ Assessment and Need of AI in Agriculture
References
۲: Challenges in Achieving Artificial Intelligence in Agriculture
۲.۱ Introduction
۲.۲ Current Applications of AI in Agriculture
۲.۲.۱ Precision Agriculture
۲.۲.۲ Crop, Soil, and Livestock Monitoring
۲.۲.۳ Weather Forecasting and Climate Modeling
۲.۲.۴ Agriculture Robots and Autonomous Equipment
۲.۲.۵ Analyzing Agricultural Big Data
۲.۲.۶ Agricultural Predictive Analytics
۲.۲.۷ Logistics and Supply Chain Management
۲.۳ Challenges for Achieving AI in Agriculture
۲.۳.۱ Lack of Data Availability and Quality of Data
۲.۳.۲ Barriers to Accessing High Technology
۲.۳.۳ High Level of Input Cost
۲.۳.۴ Social Cultural Barriers
۲.۳.۵ Policy Barriers
۲.۴ Strategies to Overcome Achieving AI Challenges in Agriculture
۲.۴.۱ Strategies to Increase Data Availability and Quality of Data
۲.۴.۲ Strategies to Increase High Technology Accessibility
۲.۴.۳ Strategies to Reduce High Input Cost
۲.۴.۴ Strategies to Overcome Social Barriers
۲.۴.۵ Strategies to Overcome Policy Barriers
۲.۵ Future Directions
۲.۶ Conclusion
References
۳: Introduction to Artificial Intelligence Techniques in Agricultural Applications and Their Future Aspects
۳.۱ Introduction
۳.۲ Key Components and Techniques in AI
۳.۳ Major Applications of AI in Agriculture
۳.۳.۱ Precision Farming Management
۳.۳.۲ Soil and Irrigation Management
۳.۳.۲.۱ Soil Management
۳.۳.۲.۲ Irrigation Management
۳.۳.۳ Livestock Management
۳.۳.۳.۱ Animal Identification
۳.۳.۳.۲ Automated Weighing Systems
۳.۳.۳.۳ Automated Health Monitoring
۳.۳.۴ Aquaculture System
۳.۳.۴.۱ Automated Monitoring and Control
۳.۳.۴.۲ Precision Aquaculture
۳.۳.۵ Supply Chain Management
۳.۴ Future Aspects of AI in Agriculture
۳.۵ Opportunity of AI Technology in Agriculture
۳.۶ Challenges in Adoption of AI Technology in Agriculture
۳.۷ Conclusions
References
۴: Agricultural Artificial Intelligence: Obstacles and Opportunities
۴.۱ Introduction
۴.۲ Limitations of Implementing Artificial Intelligence Techniques in Agriculture Field: A Practical Approach
۴.۲.۱ Lack of Competent Labor
۴.۲.۱.۱ Solution
۴.۲.۲ The Affordability of AI Adoption in Agriculture
۴.۲.۲.۱ Factors Increasing AI’s Expensive Cost in Agriculture
۴.۲.۳ Financial Effects on Farming Businesses
۴.۲.۳.۱ Agricultural AI’s Expensive Costs: Strategies for Sustainable Adoption
۴.۲.۳.۲ Solution: Multiple Strategies Can Be Employed to Reduce Expenses and Encourage Broader Availability of AI Technologies
۴.۲.۴ Difficulty in Data Handling
۴.۲.۴.۱ Lack of Access to Data
۴.۲.۵ Extreme Climatic Condition as a Challenge for Implementing AI in Agriculture
۴.۲.۶ Requirement of High Accuracy and Precision
۴.۲.۷ Security Risks
۴.۳ Conclusion
References
۵: Smart Farming Management System: Pre and Post-Production Interventions
۵.۱ Introduction
۵.۲ Problem with Modern Agriculture
۵.۲.۱ Why Smart Farm Management
۵.۲.۲ Agriculture Interventions
۵.۳ Irrigation Water Management
۵.۴ Farm Mechanization
۵.۴.۱ Precision Machinery
۵.۴.۲ Robotics
۵.۵ Postharvest Management
۵.۶ Recommendations, Limitation, and Suggestions for Future
References
۶: Introduction to Various Intelligent Devices and Implementation Platforms
۶.۱ The Dawn of the Intelligent Age
۶.۲ A Spectrum of Intelligence
۶.۲.۱ Implementation Platforms: Bridging the Gap
۶.۲.۱.۱ Road Ahead
۶.۳ Beyond the Text
۶.۳.۱ Raspberry Pi
۶.۳.۲ Arduino
۶.۳.۳ TensorFlow Lite
۶.۳.۴ OpenHAB
۶.۳.۵ Amazon Web Services (AWS) IoT Core
۶.۴ Case Studies: Intelligent Devices Reimagine Industries
۶.۴.۱ Healthcare
۶.۴.۲ Agriculture
۶.۴.۳ Manufacturing
۶.۵ Conclusion
References
۷: Fruit Counting and Analysis Using Artificial Intelligence Approaches
۷.۱ Introduction
۷.۱.۱ Challenges Associated with Traditional Manual Counting Methods
۷.۱.۲ Role of Artificial Intelligence in Addressing These Challenges
۷.۲ Need for Automation in Fruit Counting
۷.۲.۱ Importance of Efficient Fruit Counting for Yield Estimation
۷.۲.۲ Limitations of Manual Counting Methods
۷.۳ Computer Vision and Its Applications
۷.۳.۱ Object Detection Algorithms for Identifying and Locating Fruits in Images
۷.۳.۱.۱ One-Stage Object Detection Algorithms
۷.۳.۱.۲ Two-Stage Object Detection Algorithms
۷.۳.۱.۳ Artificial Neural Networks (ANNs)
۷.۳.۱.۴ Convolutional Neural Networks (CNNs)
۷.۳.۲ Image Segmentation Techniques for Precise Fruit Boundary Delineation
۷.۴ Machine Learning Models for Counting Accuracy
۷.۴.۱ Overview of Convolutional Neural Network and Support Vector Machines
۷.۵ Data Acquisition and Preprocessing
۷.۵.۱ Use of Labeled Datasets and the Challenges Associated with Data Collection
۷.۶ Case Studies and Success Stories
۷.۷ Limitations and Opportunities of AI in Agriculture
۷.۷.۱ Challenges and Future Directions in Fruit Counting Using AI
۷.۷.۲ Exploration of Some Emerging Technologies
۷.۸ Conclusion
References
۸: Deep Learning-Based Plant Stress Diagnosis: An Optimized Generative Augmentation Model Approach
۸.۱ Introduction
۸.۲ Literature Review
۸.۳ Proposed Model for Plant Stress Identification
۸.۳.۱ Training and Testing with MBGD Optimization
۸.۴ Result and Discussion
۸.۴.۱ Dataset Distribution and Augmentation
۸.۴.۲ DCNN Performance Analysis
۸.۴.۳ Comparative Analysis of Disease Identification
۸.۴.۴ Comparative Assessment with Previous Methods
۸.۵ Conclusion
References
۹: Transformative Impact of AI-Driven Computer Vision in Agriculture
۹.۱ Sampling of Agricultural Soil Using UAV
۹.۲ Computer Vision-Based Prototype of Picking System for Fruit
۹.۳ Canopy Height Estimation
۹.۴ Computer Vision-Based Fruit Grading System for Quality Evaluation
۹.۵ A Generalized Computer Vision Approach to Mapping Crop Fields in Heterogeneous Agricultural Landscapes
۹.۶ Potato Crop Stress Prediction of Aerial Images Using Naïve Bayes Classifier
۹.۷ Vision-Based Navigation for Autonomous Vehicles in Agricultural Fields: A Novel Texture Tracking Approach
۹.۸ Water Necessity Assessment Using Computer Vision and Drone Technology
۹.۹ Different Vegetation Indices Measurement Using Computer Vision
۹.۱۰ Plant Disease Detection and Classification
۹.۱۱ limitations and Opportunities of AI
۹.۱۲ Conclusion
References
۱۰: An In-Depth Analysis of Artificial Intelligence-Based Crop Pest Management and Water Supply Regulation
۱۰.۱ Introduction
۱۰.۲ Impact of AI on Indian Agriculture
۱۰.۳ AI in Irrigation Systems
۱۰.۴ Reviving the Irrigation System Through AI Model
۱۰.۴.۱ Machine Learning Algorithms
۱۰.۴.۲ Supervised Irrigation Model
۱۰.۴.۲.۱ Linear Regression
۱۰.۴.۲.۲ Support Vector Machine (SVM)
۱۰.۴.۳ Unsupervised Irrigation Model
۱۰.۴.۳.۱ K Means Clustering
۱۰.۴.۴ Artificial Neural Network (ANN)
۱۰.۴.۴.۱ Deep Learning
۱۰.۴.۵ Convolutional Neural Network (CNN)
۱۰.۴.۶ Recurrent Neural Network (RNN)
۱۰.۴.۷ Long Short-Term Memory (LSTM)
۱۰.۴.۸ Reinforcement Learning (RL)
۱۰.۵ For Future: Optimize Agriculture with Smart Irrigation
۱۰.۶ Case Studies
۱۰.۶.۱ Irrigation with NASA and AI (Application: EVAPO)
۱۰.۶.۱.۱ Core Value
۱۰.۶.۲ AI-Powered Crop Monitoring and Irrigation (Application: Nano Ganesh)
۱۰.۶.۲.۱ Core Value
۱۰.۷ AI in Pest Management
۱۰.۸ Startups Using AI and Machine Learning in Agriculture
۱۰.۸.۱ Taranis
۱۰.۸.۲ Trap View
۱۰.۸.۳ EcoRobotix
۱۰.۸.۴ Kishan Know
۱۰.۸.۵ Greeneye Technology
۱۰.۹ Pest Detection and Monitoring Systems
۱۰.۱۰ Decision Support System
۱۰.۱۱ Precision Pest Management
۱۰.۱۲ GIS and GPS Modules
۱۰.۱۳ Merits of AI
۱۰.۱۳.۱ Reduced Use of Pesticides
۱۰.۱۳.۲ Increased Efficiency
۱۰.۱۳.۳ Lower Costs of Pest Control
۱۰.۱۴ Limitations of AI
۱۰.۱۴.۱ Response Time and Accuracy
۱۰.۱۴.۲ Large Data Requirement
۱۰.۱۴.۳ Methodology
۱۰.۱۴.۴ High Data Cost
۱۰.۱۴.۵ Flexibility
۱۰.۱۵ Challenges While Using AI
۱۰.۱۶ Conclusion and Future Perspectives
References
۱۱: AI for Data-Driven Decision-Making in Smart Agriculture: From Field to Farm Management
۱۱.۱ Introduction
۱۱.۲ Overview of Smart Agriculture
۱۱.۲.۱ Definition and Scope
۱۱.۲.۱.۱ Definition
۱۱.۲.۱.۲ Scope
۱۱.۲.۲ Components of Smart Agriculture
۱۱.۲.۲.۱ Sensing and Monitoring
۱۱.۲.۲.۲ Data Collection
۱۱.۲.۲.۳ Communication Technologies
۱۱.۲.۲.۴ Decision Support Systems (DSS)
۱۱.۳ Role of Data in Smart Agriculture
۱۱.۳.۱ Importance of Data-Driven Decision-Making
۱۱.۳.۲ Types of Data in Agriculture
۱۱.۳.۲.۱ Environmental Data
۱۱.۳.۲.۲ Crop Data
۱۱.۳.۲.۳ Livestock Data
۱۱.۳.۳ Challenges in Handling Agricultural Data
۱۱.۳.۳.۱ Data Security and Privacy
۱۱.۳.۳.۲ Data Integration
۱۱.۳.۳.۳ Connectivity Issues
۱۱.۴ AI in Agriculture
۱۱.۴.۱ Introduction to AI
۱۱.۴.۲ AI Techniques in Agriculture
۱۱.۴.۲.۱ Machine Learning
۱۱.۴.۲.۲ Deep Learning
۱۱.۴.۲.۳ Computer Vision
۱۱.۴.۳ Applications of AI in Smart Agriculture
۱۱.۴.۳.۱ Crop Monitoring
۱۱.۴.۳.۲ Pest and Disease Detection
۱۱.۴.۳.۳ Yield Prediction
۱۱.۵ Data-Driven Decision Making
۱۱.۵.۱ Concept and Principles
۱۱.۵.۲ Integration of AI in Decision-Making
۱۱.۵.۳ Benefits and Challenges
۱۱.۵.۳.۱ Benefits
۱۱.۵.۳.۲ Challenges
۱۱.۶ From Field to Farm Management
۱۱.۶.۱ Precision Agriculture
۱۱.۶.۲ Intelligent Farm Equipment
۱۱.۶.۳ Automation in Farm Management
۱۱.۷ Data Integration and Management
۱۱.۷.۱ Data Integration Platforms
۱۱.۷.۲ Challenges in Data Management
۱۱.۷.۳ Security and Privacy Concerns
۱۱.۸ Future Trends in AI for Smart Agriculture
۱۱.۸.۱ Emerging Technologies
۱۱.۸.۱.۱ Internet of Things (IoT) Integration
۱۱.۸.۱.۲ Robotics and Automation
۱۱.۸.۱.۳ Edge Computing
۱۱.۸.۲ Potential Innovations
۱۱.۸.۲.۱ Predictive Analytics for Crop Management
۱۱.۸.۲.۲ Precision Agriculture at Scale
۱۱.۸.۲.۳ Blockchain for Supply Chain Transparency
۱۱.۸.۳ Sustainability and Ethical Considerations
۱۱.۸.۳.۱ Resource Optimization and Environmental Impact
۱۱.۸.۳.۲ Ethical Use of Data
۱۱.۸.۳.۳ Addressing Socioeconomic Impact
۱۱.۹ Conclusion
References
۱۲: AI-Based Regulation of Water Supply and Pest Management in Farming
۱۲.۱ Introduction
۱۲.۱.۱ The Rise of AI and Its Application in Agriculture Water Management
۱۲.۱.۲ Predictive Analytics for Weather and Water Availability
۱۲.۱.۲.۱ Machine Learning Algorithms
۱۲.۱.۲.۲ Real-time Monitoring Systems
۱۲.۱.۳ AI to Detect Irrigation Malfunctions or Leaks
۱۲.۱.۴ Sensor-based AI Solutions to Optimize Irrigation Scheduling
۱۲.۱.۵ Smart Irrigation Systems and Water Conservation
۱۲.۱.۵.۱ AI-Powered Drip Irrigation
۱۲.۱.۵.۲ Soil Moisture Sensors
۱۲.۱.۶ AI in Different Types of Irrigation Systems
۱۲.۱.۶.۱ Sprinkler Irrigation
۱۲.۱.۶.۲ Centre Pivot Irrigation
۱۲.۱.۷ Key Areas for Policy Action
۱۲.۱.۸ Advancing: Effective Partnerships Between Government and Private Sector
۱۲.۲ Significance of Artificial Intelligence in Pest Management
۱۲.۲.۱ Pest Detection, Identification, and Classification
۱۲.۲.۲ Pest Monitoring
۱۲.۲.۳ Pest Prediction and Decision-Making by Employing AI
۱۲.۲.۴ Pesticide Application Using AI
۱۲.۳ AI in Agriculture: Opportunities
۱۲.۴ AI in Agriculture: Challenges
۱۲.۵ Conclusions
References
۱۳: Advancement and Challenges of Implementing Artificial Intelligence of Things in Precision Agriculture
۱۳.۱ Introduction
۱۳.۲ Traditional Agriculture to Smart Agriculture
۱۳.۲.۱ Artificial Intelligence of Things (AIoT)
۱۳.۳ Technological Integration in Smart Agriculture
۱۳.۴ Application of Smart Agriculture
۱۳.۴.۱ Soil Management
۱۳.۴.۲ Water Management
۱۳.۴.۳ Weed Management
۱۳.۴.۴ Diseases and Pest Management
۱۳.۴.۵ Crop Yield Prediction
۱۳.۴.۶ Harvesting
۱۳.۴.۷ Weather Forecast
۱۳.۴.۸ Supply Chain Management
۱۳.۵ Challenges in Smart Agriculture
۱۳.۵.۱ Data Level Challenges
۱۳.۵.۲ Network Layer Challenges
۱۳.۵.۳ Storage and Processing Challenges
۱۳.۵.۴ Data Analysis Challenges
۱۳.۵.۵ Decision-Making and Recommendation Challenges
۱۳.۵.۶ General Issues Challenges
۱۳.۶ Cybersecurity Challenges in the Smart Farming Ecosystem
۱۳.۶.۱ Data Attacks
۱۳.۶.۲ Networking and Equipment Attacks
۱۳.۶.۳ Supply Chain Attacks
۱۳.۷ Conclusions
References
۱۴: Enabling Digital Platforms: Toward Smart Agriculture
۱۴.۱ Introduction
۱۴.۲ Internet of Things in Agriculture
۱۴.۳ Application of Digitized Platforms in Genetics and Plant Breeding
۱۴.۳.۱ Genomic Sequencing in Rice Cultivation
۱۴.۳.۲ Isolation, Cloning, and Functional Validation of Pi54 Gene for Resistance to Rice Blast (Adopted from ICAR Gene Bank, 2022)
۱۴.۳.۳ Application of Internet of Things (IoT) in Next-Generation Sequencing (NGS) in Genetics and Plant Breeding
۱۴.۳.۳.۱ Advantages of Next-Generation Sequencing in Agriculture
۱۴.۳.۴ Application of Digitized Platforms in Soil Health Management
۱۴.۳.۴.۱ Sentinel-2 Satellite Data for Spatiotemporal Mapping of Deep Pools for Monitoring the Riverine Connectivity (Adopted from Zhang et al. 2021)
۱۴.۳.۵ Application of Digitized Platforms in Animal Husbandry
۱۴.۳.۵.۱ Disease Informatics (Table 14.1; Fig. 14.7)
۱۴.۴ Conclusion
References
۱۵: IoT and Drone-Based Field Monitoring and Surveillance System
۱۵.۱ Introduction
۱۵.۲ A Brief Idea About Drones Used in Agriculture
۱۵.۲.۱ Sensors Used in Drones
۱۵.۲.۲ Method of Processing Data Acquired by Sensors
۱۵.۳ Components of Sensor Platform Based on IoT
۱۵.۴ “Modus Operandi”: Method of Data Acquisition and Transmission
۱۵.۵ Instances of Field Monitoring and Surveillance Based on IoT and Drones
۱۵.۵.۱ Crop Health Monitoring
۱۵.۵.۲ Crop Growth Monitoring and Yield Estimation
۱۵.۵.۳ Water Stress Monitoring
۱۵.۵.۴ Weed Mapping
۱۵.۵.۵ Nutrient Status
۱۵.۶ Conclusion
۱۵.۷ Future Prospect
References
۱۶: IoT-Based Real-Time Farm Management System for Smart Agriculture
۱۶.۱ Introduction
۱۶.۲ Major Sensors Used in IoT for Smart Agriculture
۱۶.۲.۱ Soil Moisture Sensor
۱۶.۲.۲ Soil Nutrient Sensor
۱۶.۲.۳ Actuators
۱۶.۲.۴ Encoders
۱۶.۲.۵ RGB, Multispectral, and Hyperspectral Camera
۱۶.۲.۶ Thermal Camera
۱۶.۲.۷ Leaf Area Index (LAI) Sensors
۱۶.۲.۸ Weather Station
۱۶.۳ IoT-Based Technologies
۱۶.۴ Data Communication, Storage, and Mining
۱۶.۴.۱ Data Communication
۱۶.۴.۲ Cloud Storage
۱۶.۴.۳ Data Mining for IoT
۱۶.۵ Application of AI in Agricultural IoT
۱۶.۵.۱ Crop and Yield Management
۱۶.۵.۲ Disease/Pest Management
۱۶.۵.۳ Autonomous Tractor and Field Robots
۱۶.۵.۴ Soil Analysis
۱۶.۵.۵ Irrigation Management
۱۶.۵.۶ Frost Management
۱۶.۶ Conclusion
References