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Course Outline
Introduction to Edge AI in Agriculture
- Overview of AI applications in farming
- The benefits of Edge AI for real-time decision-making
- Key challenges and limitations in smart agriculture
AI-Powered Crop Monitoring
- Using computer vision for plant health analysis
- Identifying crop diseases with AI models
- Implementing drone-based crop inspections
Livestock Tracking and Behavior Analysis
- Edge AI for real-time livestock monitoring
- Behavioral analytics and anomaly detection
- Wearable sensors for precision livestock farming
Automated Irrigation and Environmental Sensing
- AI-driven irrigation control systems
- Soil moisture and climate monitoring with IoT
- Optimizing water usage with Edge AI
Deploying Edge AI Models for Smart Farming
- Choosing the right AI frameworks and hardware
- On-device processing vs. cloud-based solutions
- Ensuring scalability and efficiency in Edge AI systems
Future Trends and Challenges in Agri-AI
- Ethical considerations in AI-driven agriculture
- Emerging innovations in agritech and Edge AI
- Regulatory compliance and data security concerns
Summary and Next Steps
Requirements
- Basic understanding of AI and machine learning concepts
- Familiarity with IoT devices and sensor technologies
- General knowledge of agricultural practices and challenges
Audience
- Agritech professionals
- IoT specialists
- AI engineers
21 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €6840 online delivery, based on a group of 2 delegates, €2160 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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