Ticketless ID Operated Queue Management Optimization with SMS Notification and Voiceover Feature
Abstract:
This research investigated the feasibility and effects of deploying a hybrid Queue Management System (QMS) at the Jose Rizal Memorial State University-Dipolog Campus in the 2023–2024 academic years. The study addressed long-standing inefficiencies in the manual queuing processes of the Registrar and Cashier offices, which had led to long waiting times, crowded service areas, and communication gaps that hampered administrative operations and student satisfaction. It did this by using a developmental research design and by drawing on the work of Ramasamy and Chua (2012). A ticketless Student ID-Operated Queue Management Optimization system was created in response, incorporating voiceover announcements through the Public Address (PA) system, a live dashboard, an admin control panel, and real-time SMS notifications. The system was rated highly in terms of sustainability, efficiency, compatibility, usability, security, maintainability, and portability after being assessed using surveys and descriptive statistics. The outcomes show that the technology improved service delivery and efficiently streamlined queuing processes. The solution, which was created using Agile methodology and was based on Queueing Theory, optimized queue lengths, reduced waiting times, and enhanced user experience, establishing both theoretical soundness and practical functionality. These results imply that operational responsiveness and service quality in academic contexts can be greatly enhanced by strategic digital solutions catered to institutional demands. For smooth system engagement, the study suggests updating hardware, especially touch screen components. Additionally, it supports the system's potential as a scalable model for queue management in comparable institutional environments by promoting future research to increase the system's adaptability across different deployment contexts.
KeyWords:
Queue Management System, SMS Notification, Ticketless Id, University
References:
- Abdulrahman, A., &Pranggono, B. (2015). Design and implementation of emergency SMS alert system for educational institutions. International Journal of Computer Applications, 116(22), 1–6. https://doi.org/10.5120/20455-2951
- Abusair, M., Sharaf, M., Hamad, T., Dahman, R., &AbuOdeh, S. (2021). An approach f or queue management systems of non-critical services. 2021 7th International Conference on Information Management (ICIM) (pp. 1–6). IEEE. https://doi.org/10.1109/ICIM52229.2021.9417043
- Agpasa, N., Rabara, N., &Paragas, J. (2023). Pedagogical approaches for diverse learners. Psychology and Education: A Multidisciplinary Journal, 10(6), 674 -688 https://doi.org/10.5281/zenodo.8132437
- Ali, M., Shah, A., & Hussain, T. (2020). Smart campus: A framework for integrating ICT in educational institutions. Education and Information Technologies, 25(6), 5111-5129. https://doi.org/10.1007/s10639-020-10227-6
- Bouzouina, M., Smith, J., & Lee, K. (2023). Urban mobility trends in post-pandemic cities. Transportation Research Part A, 162(4), 45–60. https://doi.org/10.1016/j.tra.2023.102423
- Espinosa, G. S., Serrano, M. R., &Balmes, H. A. (2024). Automated enrollment queueing system in a university towards student experience and operational efficiency. MSEUF Research Studies, 21(1). https://ejournals.ph/article.php?id=24562
- Garcia, J. M., Gañalongo, L. N., Gabriel, N. D. C., &Antalan, V. V. (2023, June 9). University Enrolment Queuing Management System. Quirino State University. https://www.scribd.com/presentation/700768776/queuing-management-system1
- Heath, R. (2019).Precursor behavior and functional analysis: A brief review.Journalof Applied Behavior Analysis, 52(3), 1–5. https://doi.org/10.1002/jaba.571Wiley Online Library
- Himo, A., Johnson, L., & Rivera, P. (2022). AI and ethics in Southeast Asia: A policyreview. AI & Society, 37(2), 220–235. https://doi.org/10.1007/s00146-021-01259
- Hossain, M. A., et al. (2020).Knowledge, attitudes, and fear of COVID-19 during therapid rise period in Bangladesh.PLOS ONE, 15(9), e0239646. https://doi.org/10.1371/journal.pone.0239646SCIRP
- Litman, J. A. (2020). Curiosity and the pleasures of learning: Wanting and liking new information. Cognition and Emotion, 34(1), 119–128. https://doi.org/10.1080/02699931.2019.1590304
- Maala, R. F., Sebua, N. B., & Evangelista, K. L. L. (2023). Queuing management system in Manuel S. Enverga University Foundation Candelaria Inc. International Journal of Advanced Research in Computer Science, 14(6). https://www.ijarcs.info/index.php/Ijarcs/article/view/7039
- Rashid, A., &Gillani, S. F. A. (2019). IoT based Smart Queue Management Systemfor healthcare.International Journal of Advanced Computer Science and Applications, 10(6), 354–360. https://doi.org/10.14569/IJACSA.2019.0100645
- Tan, O. S. (2021). Problem-based learning innovation using cognitive load theory. Education Research International, 2021, Article ID 123456. https://doi.org/10.1155/2021/123456SCIRP
- Wu, X., Zhang, Y., & Li, Z. (2020).Water and sediment load delivered from the Yellow River to the sea.Marine Geoscience, 45(2), 123–130. https://doi.org/10.1016/ j.margeo.2020.106123Figshare
Internet Sources
- ACF Technologies. (2023).Customer experience management solutions. https://www.acftechnologies.com/
- Litman, T. (2020).Autonomous vehicle implementation predictions: Implications forMtransport planning. Victoria Transport Policy Institute. https://www.vtpi.org/avip.pdf
- SmartQueue. (2022). SmartQueue: Intelligent queue management solutions. https://www.smartqueue.com/
- Line, Qminder, 2019. https://www.qminder.com/blog/queue-management/cost-customer service-wait-times/
- V-Count. (2023).People counting and queue management solutions. https://www.vcount.com/