This week, I made progress in multiple areas of the project. I evaluated the performance of the ResNet18, ResNet50, and MobileNetV2 image classification models. After running tests, I found that ResNet18 and MobileNetV2 outperformed ResNet50, so I will further evaluate these models on our dataset to determine the best choice for deployment. Additionally, I successfully set up the Raspberry Pi NOIR camera for live streaming through the web application. I worked with Yuna to integrate the camera feed with the web application using HTTP, ensuring that key camera parameters (exposure, etc.) are adjustable to maintain visibility in both day and night conditions for 24/7 monitoring. Another achievement was integrating the machine learning model with the web application using MQTT. I built a system where the Raspberry Pi captures images, runs the ML model for health classification, and sends real-time results to the web application. This ensures that users can monitor plant health dynamically without manual intervention. I also set up the plant identification API, which captures an image of the plant and sends it to the API for identification. One of my main priorities was privacy, so I made sure that captured images are processed in memory and never saved to disk at any point.
This week, the focus was primarily on integration and ensuring smooth communication between different components, such as the camera, ML model, web application, and sensor system.
I am on schedule with the project timeline.
Next Week’s Deliverables:
- Start collecting sensor and image data of our plants in the greenhouse.
- Set up the greenhouse environment for the interim demo.
- Develop and test multi-classification ML models to classify plant health into more detailed categories instead of just “healthy” and “unhealthy.”
- Implement a late fusion network to combine sensor and image data for a more accurate health classification system.
- Enhance privacy measures for live streaming by adding options to turn it off and ensuring only authorized users can access it.