Description: An innovative surveillance system designed to enhance crop protection and monitoring through advanced image capture technology, deep neural networks, and real-time data analysis. The system identifies invasive animals, detects crop diseases, and monitors soil moisture levels, providing timely alerts to farmers and supporting sustainable farming practices.
Key Features:
- Invasive animal detection and deterrence
- Crop disease identification
- Soil moisture level monitoring
- Real-time alerts
- Drone integration for enhanced surveillance
- Support for sustainable agriculture
Future Development Goals:
- Broader disease detection capabilities
- Integration with weather forecasting
- Advanced data analytics
- Improved user interfaces and mobile app support
This project represents a significant step forward in agricultural technology, aiming to empower farmers with the tools they need to protect their crops and promote sustainable farming practices.
Link for the computer vision(animal detection) is provided (SLIOT-Challenge)