My hands-on projects in 3D printing and ESP32-based alert systems reflect a broader interest in affordable, decentralized computing. I am currently exploring how low-power microcontrollers can be used for real-time environmental monitoring in smart homes. Future research may focus on optimizing Telegram-based alert latency or integrating delta printers with AI-based failure detection.
Research Areas:
- Computer Vision
- Real-Time Detection
- Synthetic Dataset Generation
- AI-Based Trajectory Prediction
This research focuses on detecting and predicting dangerous tennis ball impacts toward the camera using efficient lightweight deep learning models.
The system aims to achieve real-time performance while maintaining high detection accuracy and low computational cost.