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- Manual attendance registers are susceptible to falsification and retrospective filling.
- No location verification.
- Supervisor verification requires physical co-presence which is not scalable across 100+ simultaneous camp locations.
- Attendance data is not linked to the DIGIPIN of the camp location, no spatial verification layer.
Field Devices and Infrastructure
TAB K11 (Lenovo Idea Tab / Tab K11 Gen 2)
- Product name: Lenovo Idea Tab / Lenovo Tab K11 Gen 2
- Model numbers: TB336FU / TB336ZU / TB336ZA
- Type: ZAFN
- Serial Number: HNY0M001
- Machine Type Model: ZAFN0370IN
- Warranty status: In Warranty, less than 10 months remaining
- Processor: 1x MediaTek Dimensity 6300 Processor (Dimensity 6300)
- Memory: 1x 8 GB LPDDR4X
- Operating System: shown on-screen as "Android 15 ou version ultérieure()", i.e. Android 15 or later (the source page itself mixes English and French here, that isn't a transcription error on my part, it's how the portal displayed it)
- Storage: 1x 128 GB UFS 2.2
- Wireless: 1x 802.11 a/b/g/n/ac; Bluetooth® 5.2; 5G LTE
- Ports: 1x Type C 2.0
- Camera: 1x 8MP FF (fixed focus) front; 13MP AF (autofocus) back
- Display: 11" 2.5K
- Included warranty: 1 year carry-in
Laptop L14
- Processor: 1x Intel® Core™ Ultra 7 255U Processor
- Memory: 1x 16 GB DDR5-5600
- Operating System: shown as "No Operating System()"
- Storage: 1x 512 GB SSD PCIe
- Wireless: 1x Intel® Wi-Fi 6E AX211 2x2 AX; Bluetooth® 5.3
- Ports: 1x Audio Jack; 1x USB 2.0 Gen 1 Type A; 2x USB Type A (USB 3.2 Gen 1); 2x TBT4 (Thunderbolt 4); 1x RJ45 (rear); 1x HDMI 2.1 TMDS
- Camera: 1x 5MP RGB+IR with dual microphone and privacy shutter
- Graphics: 1x Intel® Graphics
Principle
Attendance capture is triggered by user login- a pre-existing, mandatory workflow step. No new button, no separate attendance form, no additional action required from the users end. The system captures location silently and displays confirmation.
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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.
