AI-Enabled Optimization of University of Cebu Computer Laboratories: A Sit-in Reservation and Monitoring System for Enhanced Resource Management

In an era where technological advancements are reshaping various sectors, including education, Artificial Intelligence (AI) offers significant potential to enhance resource management in academic institutions. This study focuses on optimizing the computer laboratory sit-in reservation and monitoring process at the University of Cebu - Main Campus, College of Computer Studies. The current manual system presents inefficiencies, such as difficulty in scheduling, suboptimal utilization of resources, and lack of real-time monitoring. To address these challenges, this research proposes the development of an AI-enabled Sit-in Reservation and Monitoring System designed to streamline reservation processes, optimize resource allocation, and provide real-time visibility into laboratory usage. The system aims to achieve four key objectives: creating a user-friendly reservation interface, developing an AI-based algorithm to optimize computer resource allocation, implementing a real-time monitoring dashboard, and evaluating the system’s effectiveness based on user feedback and performance metrics. This AI-driven solution is expected to enhance the student experience by improving accessibility and reducing wait times, while also enabling better resource management through data-driven decision-making. By maximizing the utilization of available resources, the system offers cost savings and operational efficiency improvements for the college. The study's scope is limited to the College of Computer Studies’ computer laboratory and focuses on optimizing the sit-in reservation and monitoring processes.

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Publication Details

Journal
Journal of Computer Science and Technology Studies
Published
2024-12-18
DOI
https://doi.org/10.32996/jcsts.2024.6.5.16
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

AI-Enabled Optimization of University of Cebu Computer Laboratories: A Sit-in Reservation and Monitoring System for Enhanced Resource Management

Neil Basabe, Leo C. Bermudez, Jeff Salimbangon, Jennifer Amores
Journal of Computer Science and Technology Studies
Big Data and Business Intelligence
article

AI-Enabled Optimization of University of Cebu Computer Laboratories: A Sit-in Reservation and Monitoring System for Enhanced Resource Management

Neil Basabe, Leo C. Bermudez, Jeff Salimbangon, Jennifer Amores
article en

Abstract

In an era where technological advancements are reshaping various sectors, including education, Artificial Intelligence (AI) offers significant potential to enhance resource management in academic institutions. This study focuses on optimizing the computer laboratory sit-in reservation and monitoring process at the University of Cebu - Main Campus, College of Computer Studies. The current manual system presents inefficiencies, such as difficulty in scheduling, suboptimal utilization of resources, and lack of real-time monitoring. To address these challenges, this research proposes the development of an AI-enabled Sit-in Reservation and Monitoring System designed to streamline reservation processes, optimize resource allocation, and provide real-time visibility into laboratory usage. The system aims to achieve four key objectives: creating a user-friendly reservation interface, developing an AI-based algorithm to optimize computer resource allocation, implementing a real-time monitoring dashboard, and evaluating the system’s effectiveness based on user feedback and performance metrics. This AI-driven solution is expected to enhance the student experience by improving accessibility and reducing wait times, while also enabling better resource management through data-driven decision-making. By maximizing the utilization of available resources, the system offers cost savings and operational efficiency improvements for the college. The study's scope is limited to the College of Computer Studies’ computer laboratory and focuses on optimizing the sit-in reservation and monitoring processes.

Journal of Computer Science and Technology StudiesVol. 6(5)
University of the Philippines Cebu (PH), University of Cebu (PH)
Openalex Percentile: Top 64%
Big Data and Business Intelligence
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