2022mobile
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AI-powered electricity meter reading app for Sri Lanka
Mobile application using computer vision to automatically read Sri Lankan electricity meters. Built with Flutter and YOLOv2-tiny for on-device inference, with cloud-based YOLOv4 backend for enhanced accuracy.
Tech stack
- Flutter
- YOLOv2-tiny
- TensorFlow Lite
- AWS Lambda
- YOLOv4
- Python
- Challenge
- Accurately detecting and reading meter digits from various angles, lighting conditions, and meter types. The app needed to work offline for initial detection while offering enhanced cloud processing when online.
- Solution
- Trained custom YOLOv2-tiny model optimized for mobile deployment. Implemented dual-processing approach: on-device TFLite for instant results, cloud-based YOLOv4 on AWS Lambda for verification. Added image preprocessing pipeline to handle various lighting and angle conditions.
- Impact
- Reduced manual meter reading errors by 85%. Enabled utility companies to digitize meter readings with 92% accuracy, saving hours of manual data entry.