Wastewatch: Architecture and Design of Vehicle Monitoring and MRF-Integrated Waste Collection for Cenro Alaminos City

Effective waste collection monitoring remains a significant challenge for the City Environment and Natural Resources Office (CENRO) of Alaminos City due to existing operational processes that rely on manual monitoring, the absence of real-time vehicle tracking capabilities, coordination delays in collection activities, and the need for a more structured complaint reporting mechanism. Consequently, these concerns present opportunities for improvement in delivering timely and organized waste management services. Although various technology-driven waste management solutions have been explored in different contexts worldwide, localized systems specifically designed for LGU-level operations in the Philippine context remain limited. To address this gap, the researchers propose WasteWatch, a web and mobile-based system designed to support vehicle monitoring and MRF-integrated waste collection management. The Agile Prototyping Model was utilized by the researchers to guide the system development process through continuous refinement based on user feedback. WasteWatch was structured using a Three-Tier Architecture composed of the presentation, application, and data tiers. Relevant information and system requirements were gathered through interviews, observation, document analysis, and purposive sampling of 85 respondents from CENRO personnel, garbage truck drivers, MRF representatives, landfill representatives, IT experts, and residents of Alaminos City. The proposed system integrates several critical functions: GPS-based vehicle monitoring, complaint reporting, MRF hauling coordination, digital landfill recording, and centralized administrative oversight. Its usability and acceptability will be assessed through stakeholder feedback to determine how well the system supports the needs of its intended users. Overall, WasteWatch aims to provide CENRO Alaminos City with a more organized, responsive, and technology-driven approach to waste management operations, replacing informal coordination methods with structured digital processes

Waste Management, Vehicle monitoring, Responsive, GPS-based

1. Alvarico, E. A. M., Arricivita, F. A. I., et al. (2024). Real-time tracking and monitoring system with geofence notification for garbage collection vehicles. 2024 6th International Conference on Electronics and Communication, Network and Computer Technology (ECNCT). [Google Scholar] [Crossref]

2. Camarillo, M. E. C., & Bellotindos, L. M. (2021). A study of policy implementation and community participation in the municipal solid waste management in the Philippines. Applied Environmental Research, 43(2), Article 2. https://doi.org/10.35762/AER.2021.43.2.3 [Google Scholar] [Crossref]

3. Cruz, C. C., Villafuerte, H. C. R., Avila, R. B., et al. (2024). Mobile application for monitoring trash collection schedules and promote efficient solid waste management. Cognizance Journal of Multidisciplinary Studies, 4(3), 22–31. https://doi.org/10.47760/cognizance.2024.v04i03.003 [Google Scholar] [Crossref]

4. Kannan, D., Khademolqorani, S., Janatyan, N., & Alavi, S. (2024). Smart waste management 4.0: The transition from a systematic review to an integrated framework. Waste Management, 174, 1–14. https://doi.org/10.1016/j.wasman.2023.08.041 [Google Scholar] [Crossref]

5. Langit, E. R., Parungao, C. A., Gregorio, E. T. A., Sabo-o, A. J. M., et al. (2024). Feasibility study of an integrated waste management technology system for a circular economy in the Philippines. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4742843 [Google Scholar] [Crossref]

6. Mapa-Madlos, J. S., Tapdasan, J., et al. (2022). Sensor-based garbage monitoring system and application development in Magallanes Agusan Del Norte. 2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM). [Google Scholar] [Crossref]

7. Newman, S. (2021). Building microservices: Designing fine-grained systems (2nd ed.). O'Reilly Media. [Google Scholar] [Crossref]

8. Obaid, A. (2024). Using prototypes in agile software development. International Journal of Computer Informatics, 12(1), 45–58. [Google Scholar] [Crossref]

9. Sosunova, I., & Porras, J. (2022). IoT-enabled smart waste management systems for smart cities: A systematic review. IEEE Access, 10, 104334–104355. https://doi.org/10.1109/ACCESS.2022.3188308 [Google Scholar] [Crossref]

10. United Nations Environment Programme. (2024). Global Waste Management Outlook 2024: Beyond an age of waste — Turning rubbish into a resource. United Nations Environment Programme. https://doi.org/10.59117/20.500.11822/44939 [Google Scholar] [Crossref]

11. International Organization for Standardization. (2023). Systems and software engineering — Systems and software quality Requirements and Evaluation (SQuaRE) — Quality model (ISO/IEC 25010:2023). International Organization for Standardization. [Google Scholar] [Crossref]

12. Dalimunthe, S., Putra, E., & Ridha, M. (2023). Restful API security using JSON Web Token (JWT) with HMAC-Sha512 algorithm in session management. IT Journal Research and Development, 8(1), 81–94. [Google Scholar] [Crossref]

13. Mpamugo, E., & Ansa, G. (2024). Enhancing network security in mobile applications with role-based access control. Journal of Information Systems and Informatics, 6(3). https://doi.org/10.51519/journalisi.v6i3.863 [Google Scholar] [Crossref]

14. Agup, R. M. (2024). Data Privacy Act: Awareness, compliance, and challenges of nurses of government hospitals in Northern Philippines. South Eastern European Journal of Public Health, 2215–2224. https://doi.org/10.70135/seejph.vi.2834 [Google Scholar] [Crossref]

• Smart Iot Device for Weather And Health
• Merlarchive: A Web-Based Academic Hub for UDM With AI-Powered Natural Language Processing
• Enhanced Social Network Security System: Integrating Biometric Authentication for Improved User Verification and Privacy Protection
• Smart Budget Allocation in Public Policy: A Data-Driven Approach for Equitable Resource Distribution
• Decision Support System for Faculty Selection, Promotion, and Reclassification Using Predictive Analytics