The Role of Biometric and IoT-Based Attendance Systems in Streamlining HR Administrative Functions, Enhancing Workforce Accountability, and Reducing Labor Inefficiencies
The integration of biometric and Internet of Things (IoT)-based attendance systems is revolutionizing human resource (HR) management by enhancing operational efficiency, promoting workforce accountability, and minimizing labor-related inefficiencies. This paper explores the pivotal role of these technologies in transforming traditional attendance tracking methods, which are often plagued by inaccuracies, time theft, and administrative burdens. Biometric systems, leveraging unique physiological identifiers such as fingerprints and facial recognition, offer a secure and tamper-proof mechanism for employee identification and time logging. When combined with IoT infrastructure such as cloud connectivity and smart devices attendance data becomes more accessible, real-time, and reliable, enabling HR departments to make informed decisions swiftly. These integrated systems not only simplify routine administrative tasks such as payroll processing and leave management but also foster a transparent work culture where accountability is reinforced through accurate attendance records. Furthermore, they enable organizations to monitor workforce distribution, identify trends in absenteeism or tardiness, and allocate human resources more efficiently. By addressing issues such as “buddy punching,” manual data entry errors, and excessive HR workload, biometric and IoT-based attendance systems present a forward-looking solution for organizations striving to optimize labor productivity. Ultimately, the adoption of these smart technologies is a strategic move toward data-driven HR practices and sustainable workforce management.
Authors
- Onuh Matthew Ijiga
- Diana Ussher-Eke
- Onum Friday Okoh
Publication Details
- Journal
- International Journal For Multidisciplinary Research
- Published
- 2025-07-26
- DOI
- https://doi.org/10.36948/ijfmr.2025.v07i04.52237
- Primary Topic
- Impact of AI and Big Data on Business and Society
- Type
- article
- Field-Weighted Citation Impact
- 0.00