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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
Testimonials (1)
That we can cover advance topic and work with real-life example