This week I focus on charging app development and CV development, and did some testing related to the subsystem.
Charging App Development
- Completed the development of the iOS and macOS apps, enabling users to monitor their phone’s charging status in real-time.
- Successfully integrated Google Cloud Firebase storage, providing a centralized system where users can view and manage the charging statuses of all their devices from the macOS app.
- Added features to enhance the user experience, such as real-time updates and seamless synchronization across devices.
Computer Vision System - Finalized the object detection module, achieving approximately 90% accuracy in detecting phones on the table.
- Implemented a two-frame difference technique to identify significant changes between video frames, signaling the potential placement of a phone, and also avoid using yolo model at all frame to save performance.
- Incorporated a YOLO model to confirm the detection, identify the phone, and calculate its center coordinates for precise localization.
- Enhanced the detection pipeline to minimize processing time while maintaining high accuracy.
The project is on track, with key software systems functional and aligned with the project timeline. Significant progress has been made on both the app and vision subsystems, ensuring they are ready for integration.
Next Week’s Plan:
- Enhance Charging Pad Stability:
- Focus on improving the stability and reliability of the charging pad system to ensure consistent wireless charging performance.
- Optimize Phone Detection:
- Fine-tune the YOLO model to reduce false positives and further improve accuracy.
- Test the system with various phone models and orientations to enhance robustness.
- Integrate Vision and Gantry Systems:
- Begin integrating the computer vision system with the gantry system, enabling the seamless transfer of phone location data to control the movement of the charging pad.
Test the communication between the vision system and Raspberry Pi to ensure smooth coordination.
Testing
Software Testing (iOS and macOS Apps) (Already did):
Ensure real-time updates of charging status for multiple phones through Firebase. Therefore, for this test, we need to test multiple different devices (iPhone 12 Pro, iPhone 13 Pro, iPhone 14) charging simultaneously, and we need to measure the time taken for status changes to reflect on the apps and repeat for 10 times. The test result shows an average update delay <500 million seconds, meeting real-time requirements, and it verified seamless synchronization across iOS and macOS platforms.
Data Consistency Testing (Already did)
Verified data consistency between Firebase and app interfaces by making real-time changes to device charging status and observing updates on both IOS and MacOS platform. The test was conducted 15 times, and the data are all consistent and updated in a very short time period. (< 500 milliseconds)
Object Detection Accuracy Testing (Already did)
Evaluated the accuracy of the YOLO model with a dataset of 3 phone placements in various conditions such as different lighting, orientations, and phone models. The test was conducted 20 times, and in 18 of the times all phone locations are correctly identified, achieving an overall detection accuracy of 90 percent with occasional false positives for phone-like objects.