WiFi Received Signal Strength (RSS) Based Automated Attendance System for Educational Institutions
| dc.contributor.author | Khan, Sidratul Muntaha | en |
| dc.contributor.author | Maliha, Mehreen Tabassum | en |
| dc.contributor.author | Haque, Md Shahedul | en |
| dc.contributor.author | Rahman, Ashikur | en |
| dc.date.accessioned | 2025-02-06T18:35:45Z | en |
| dc.date.available | 2025-02-06T18:35:45Z | en |
| dc.date.issued | 2024-12-19 | en |
| dc.date.updated | 2025-02-01T09:07:06Z | en |
| dc.description.abstract | Smartphones are becoming part of people’s day-to-day activities now-a-days. Globally, almost 90% of cellular phones are smartphones. “Personnel tracking” is a viable usage of smartphones. Automated attendance system, an application of personnel tracking, is efficient and essential for enhancing productivity and streamlining operations in modern workplaces and educational institutions. While traditional methods of attendance tracking are prone to inaccuracies and inefficiencies, smartphone-based systems offer a smoother approach. In this paper, we present a smartphone-based attendance system that leverages Wi-Fi signal strength for indoor localization. Instead of requiring precise positioning, we propose a system with zone-based localization approach. We divide the whole area into distinct smaller zones and determine the users’ location within these zones. Through real-world deployment, we demonstrate that our novel approach reduces the complexity of exact positioning while still achieving high accuracy in identifying a user’s presence within specific areas, which are often enclosed by boundaries. Comparative evaluations with implementing an algorithm show the superiority of our proposed method in terms of accuracy and practicality, making it suitable for deployment in large-scale organizational settings. | en |
| dc.description.version | Published version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | https://doi.org/10.1145/3704522.3704523 | en |
| dc.identifier.uri | https://hdl.handle.net/10919/124516 | en |
| dc.language.iso | en | en |
| dc.publisher | ACM | en |
| dc.rights | Creative Commons Attribution 4.0 International | en |
| dc.rights.holder | The author(s) | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
| dc.title | WiFi Received Signal Strength (RSS) Based Automated Attendance System for Educational Institutions | en |
| dc.type | Article - Refereed | en |
| dc.type.dcmitype | Text | en |