G-Waste: A smart waste collection system with GPS technology for real-time tracking
Dane Mhark Lepiten, Kaye Chloe Malait, Christian Dave Bereguel, Alexis Sevilleno, Marjorie Reso, Windel Pelayo, Jonel Gelig, & Leonard Balabat
Abstract
This study presents the development and evaluation of G-Waste, a real-time garbage scheduling and collection system designed to address inefficiencies in traditional waste management in Bogo City, Philippines. Findings from surveys conducted among the LGU, garbage collectors, and residents reveal a lack of real-time communication between residents and collectors, an inefficient waste collection process, improper waste categorization, and delayed reporting of waste issues. Hence, the system aimed to address the issues by providing features such as real-time location and notification, waste categorization guide, waste generation prediction to recommend admin where and when garbage tends to overflow, and AI chatbot for reporting and help. Using a mixed-method approach, the study focused on stakeholder experiences and system performance under real-world conditions through User Acceptance Testing based on ISO 25010 standards. The findings indicate an overall weighted mean of 4.3 (Strongly Agree), which indicates that the app feature meets the needs of the residents. A rating of 3.7 (Agree) indicates that collectors find the app difficult to use, as the majority of garbage collectors do not have mobile phones or do not use them regularly. Meanwhile, a rating of 4.3 (Strongly Agree) shows that the LGU is satisfied and supports operational needs, and a rating of 4.5 (Strongly Agree) indicates strong technical approval from IT experts. These results demonstrate that G-Waste effectively enhances communication, optimizes collection schedules, and supports proper waste management practices. However, the system has limitations, the system dependent on the internet connectivity being stable to operate. These results have practical implications for local governments and communities seeking to implement data-driven, sustainable, and citizen-friendly waste collection.
Keywords
waste management, smart collection, real-time monitoring, waste generation prediction
Author information & Contribution
Dane Mhark Lepiten. Bachelor of Science in Information Technology student-researcher, Cebu Roosevelt Memorial Colleges.
Kaye Chloe Malait. Bachelor of Science in Information Technology student-researcher, Cebu Roosevelt Memorial Colleges.
Christian Dave Bereguel. Bachelor of Science in Information Technology student-researcher, Cebu Roosevelt Memorial Colleges.
Alexis Sevilleno. Bachelor of Science in Information Technology student-researcher, Cebu Roosevelt Memorial Colleges.
Marjorie Reso. Corresponding author. Master in Information Technology. Faculty/Research Adviser, Cebu Roosevelt Memorial Colleges. Email: marjorie_reso@crmc.edu.ph
Windel Pelayo. Bachelor of Science in Information Technology. Faculty/Research Adviser, Cebu Roosevelt Memorial Colleges. Email: windel_pelayo@crmc.edu.ph
Jonel Gelig. Doctor in Management major in Human Resource Management. College Dean, Cebu Roosevelt Memorial Colleges. Email: jonel_gelig@crmc.edu.ph
Leonard Balabat. Bachelor of Science in Information Technology. Program Chair, Cebu Roosevelt Memorial Colleges. Email leonard_balabat@crmc.edu.ph
"Author 1 drafted the majority of the manuscript together with Author 3. Author 2 contributed to the development of the system’s front-end as well as conceptualizing the features of the app. Author 4 developed the back-end of the system and evaluated the technical components of the study. Author 5 and Author 6 revised sections of the manuscript to improve it and ensure adherence to the required format. Author 7 and Author 8 provided the approval for publication of the content. All authors contributed to the review of the manuscript and agreed to be accountable for all aspects of the work."
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This work was not supported by any funding.
AI Declaration
The author declares the use of Artificial Intelligence (AI) in writing this paper. In particular, the author used ChatGPT, Microsoft Copilot, and QuillBot in summarizing key points, paraphrasing ideas, searching for relevant literature, and improving the clarity and structure of sentences. The author takes full responsibility in ensuring proper review and editing of content generated using AI.
Notes
This paper has been presented in the 3rd International Student Research Congress 2026.
Acknowledgement
The authors of the capstone project wish to give credit to the people and entities that contributed greatly to the implementation of this project:
Primarily, the G-Waste team would like to place on record its gratitude to research advisers, Ms. Marjorie Reso and Mr. Windel Pelayo, who mentored, tolerated, and supported the capstone experience. What the project has turned out to be is due to their expertise coupled with their constructive feedback.
The G-Waste team would also wish to recognize the Local Government Unit (LGU), who voluntarily joined and assisted the G-Waste team in conducting the survey and evaluation. They were critical in the evaluation of the functionality and effectiveness of the system and their cooperation and insight were vital.
To the members of the panel, Dr. Jonel D. Gelig, Dr. Shiela L. Tirol, Mr. Leonard C. Balabat, and Mr. Miguel Alvarina, for their valuable time and insightful comments, and feedback that helped strengthen the quality of this research.
The researchers also owed much of their success to their family and friends who provided their support and encouragement throughout their journey. Their constant support motivated the G-Waste team to keep on pushing through and complete this research.
Above all, the researchers give glory and honour to the Lord almighty, for strength, wisdom, and guidance helping the G-Waste team to persevere and be able to overcome the hurdles that came in the G-Waste team.
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Cite this article:
Lepiten, D.M., Malait, K.C., Bereguel, C.D., Sevilleno, A., Reso, M., Pelayo, W., Gelig, J. & Balabat, L. (2026). G-Waste: A smart waste collection system with GPS technology for real-time tracking. International Student Research Review, 3(1), 41-65. https://doi.org/10.53378/isrr.213
License:
This work is licensed under a Creative Commons Attribution (CC BY 4.0) International License.
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