Realization of a WebGIS for Remote Control of Biometric Sensors for Facial Recognition of Permanent Staff in an Educational Environment: The Case of the Ministry of National Education in Conakry, Guinea
Initially focused on the earth sciences and mining resources, remote sensing is now finding increasing applications, notably in human resources management in public administration. This study proposes a WebGIS for real-time tracking using geolocated biometric sensors for facial recognition, with a view to optimizing the attendance management of MENA teachers in Conakry. The system is based on an integrated architecture combining open-source facial recognition sensors, a PostgreSQL/PostGIS database, a QGIS Server, and a Lizmap Web Client interface. Each sensor, installed in a school, automatically detects the teachers initially enrolled and records their clocking-in times. Data is stored locally and then transmitted to the central server via the MQTT protocol, with GSM/GPRS or LoRa relay in the event of failure. This infrastructure enables attendance to be mapped and controlled remotely, promoting transparency and administrative efficiency. Analysis of facial recognition clocking-in data, collected in nine MENA schools in Conakry for a total of 334 teachers, reveals an overall weekly attendance rate of 80.7%, i.e., 1,348 attendances out of 1,670 expected. Of these, 73.5% were on schedule, while 26.5% showed irregularities (late arrivals, early departures, or both). These discrepancies are mainly due to rush-hour traffic jams, aggravated by the fact that, for economic reasons, most teachers live in the suburbs. As for absences (19.3%), the main causes identified are: socio-political problems (70%), social events (22%), health reasons (7%), and 1% unjustified. A notable anomaly was observed on the 2nd day of collection with 68% absences, linked to a political demonstration by opposition parties. The integration of these data into a WebGIS system enables dynamic, geographical visualization of teacher presence, promoting better workforce management and decision-making within the Ministry.
Authors
- MB Saley
- Kakayo Hervé Kpegne
- Zomi Claude Lagobo
- N’Guessan Marie Mireille Kouame
Publication Details
- Journal
- Journal of Geographic Information System
- Published
- 2025-01-01
- DOI
- https://doi.org/10.4236/jgis.2025.174010
- Primary Topic
- Face and Expression Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.00