ByeCorona aims to support Indonesian's mobility during and after the pandemic through health protocol enforcement on public spaces.
CCTVs on public areas will be equipped with Machine Learning model that detects health protocol violations. The supported health protocol currently are mask usage and social distancing. The ideal deployment scenario, cost-effectiveness wise, for the ML models would be on every CCTV embedded system using TFLite (edge-computing approach), second is deploying the model on a PC with CUDA GPU connected with the NVR/DVR, and the last (most costly) alternative is to deploy the model on cloud. The officers on-duty will then be notified for every health protocol violation, decide whether it is a false positive or not, and take necessary action towards it. Currently, the system only support verbal action as a preview. However, we are hoping that the action module is extendable to support more cool actions such as sending a drone or a robot dog!
Follow README.md on each components for guide on dependencies
Follow README.md on each components for guide on installing
Follow README.md on each components for guide on executing
Our team consists of members from Android App Development and Cloud Computing learning path at Bangkit 2021. We are missing of all Machine Learning members as they withdrawed and unreachable:
- Ajeng Savitrie (A2612428) - Android App Learning Path
- Ida Bagus Weda Baskara Adi Putra (A0141373) - Android App Learning Path
- Reyhan Naufal Hakim (C0020092) - Cloud Computing Learning Path
- Zakia Azzahro (C2582421) - Cloud Computing Learning Path
This project is licensed under the GNU GPL v3 License - see the LICENSE.md file for details