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An AI-enabled, zero-touch attendance system that auto-captures GPS coordinates, derives DIGIPIN, records device metadata, and generates a tamper-resistant attendance event on user login without requiring any manual entry. An anomaly detection layer flags suspicious patterns in real time.
Key Requirements
- In current Field worker opens the STOP TB application , the attendance module should be separate where all the camp staff can give their check in and not login into the applicationand enters login credentials.
- On user login to the application, the system shall automatically capture: GPS latitude, GPS longitude, GPS accuracy (metres), DIGIPIN, device ID (IMEI/Android ID), timestamp, network status (Offline) etc. It should work on no network areas like rural forest areas, tribal areas etc. Also capture check out time stamp.
- It should work on android tablets without sim.
- The system compares the captured GPS coordinates against the configured camp geo-fence (defined by Admin as: centre point DIGIPIN + radius in metres). The camp site is variable and is bound to change everyday but camp personnel are same.
- The AI anomaly detection engine shall flag:
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- Eliminates proxy attendance and location fabrication- program data integrity restored.
- DIGIPIN-based geo-verification provides legally defensible location records for salary disbursement and donor reporting.
- Real-time anomaly flags enable supervisors to respond within the same working day- not weeks later during audit.
- Attendance pattern analytics identify chronically absent workers, high-performing sites, and geographic coverage gaps.
- Zero additional workflow friction: attendance capture is embedded in the login step that already exists.
