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 Duration 21 hours

Course Outline

Introduction to Edge AI in Agriculture

  • Summary of AI applications in farming
  • The advantages of Edge AI for instant decision-making
  • Primary challenges and restrictions in smart agriculture

AI-Driven Crop Surveillance

  • Applying computer vision for plant health assessment
  • Detecting crop diseases using AI models
  • Executing drone-based crop evaluations

Livestock Tracking and Behavior Assessment

  • Edge AI for real-time animal monitoring
  • Behavioral analysis and anomaly identification
  • Wearable sensors for precise livestock management

Automated Irrigation and Environmental Detection

  • AI-controlled irrigation management systems
  • Soil humidity and climate tracking via IoT
  • Optimizing water consumption with Edge AI

Implementing Edge AI Models for Smart Farming

  • Selecting appropriate AI frameworks and hardware
  • On-device processing versus cloud-based solutions
  • Guaranteeing scalability and efficiency in Edge AI systems

Future Developments and Obstacles in Agri-AI

  • Ethical aspects of AI-driven agriculture
  • New innovations in agritech and Edge AI
  • Regulatory adherence and data privacy issues

Recap and Future Directions

Requirements

  • Fundamental grasp of AI and machine learning principles
  • Knowledge of IoT devices and sensor technologies
  • General awareness of agricultural methods and associated challenges

Target Audience

  • Agritech professionals
  • IoT specialists
  • AI engineers

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