Fusion of LoRa RFID and AI Base Smart Security Recognition Systems for Rural Areas

Authors

  • Imran Khurshid Department of Computing, National University of Modern Languages, Multan, 60000, Pakistan.
  • Dr. Tahir Abbas Department of Computer Science, TIMES University, Multan, 60000, Pakistan.
  • Attique-ur- Rehman Department of Computer Science, TIMES University, Multan, 60000, Pakistan.
  • Dr. Sadaqat Ali Rammy Department of Computer Science, TIMES University, Multan, 60000, Pakistan.
  • Muhammad Ashad Baloch Department of Computing, National University of Modern Languages, Multan, 60000, Pakistan.
  • Muhammad Department of Computer Engineering, Bahauddin Zakariya University, Multan, 60000, Pakistan

DOI:

https://doi.org/10.52700/scir.v7i2.189

Keywords:

Attendance Monitoring, RFID, LoRa Module, ESP32, Smart Card, RSSI, SNR.

Abstract

This paper has suggested and tested a low-cost standalone attendance monitoring system that has RFID and LoRa integration that can be applied to those regions that have poor connectivity with the internet or GSM, i.e., remote campuses or plantations. RFID is an option that allows highly secure off-line user authentication and LoRa Data can be relayed to a cloud database. Indoor and outdoor testing revealed reproducible indoor functioning at two levels and up to 133.17 meters outside with ordinary antennas. The findings showed that signal strength (RSSI) and clarity (SNR) were very dependent on the distance and the obstruction in the environment. The ESP32 microcontrollers and LCD modules integrate the system enhancing efficiency, user interaction, as well as cost-effectiveness. All in all, the system provides a convenient and flexible system of monitoring attendance in infrastructure limited setting.

Published

2025-08-12

How to Cite

Khurshid, I., Abbas, T., Rehman, A.- ur-., Rammy, S. A., Baloch, M. A., & Muhammad. (2025). Fusion of LoRa RFID and AI Base Smart Security Recognition Systems for Rural Areas. STATISTICS, COMPUTING AND INTERDISCIPLINARY RESEARCH, 7(2), 139-156. https://doi.org/10.52700/scir.v7i2.189