Mobile-Based Smart Transport Route Optimization and Hazard Reporting System for San Juan

Abstract: The aim of this study is to develop a Mobile-Based Smart Transport Route Optimization and Hazard Reporting System that could improve navigation, minimize travel time, and increase road safety in San Juan City. The complex road system of the city and the ever-changing traffic rules, such as one-way and two-way rules based on time, pose great challenges to drivers, which often result in congestion and unintended traffic violations. This study solves these problems by giving a localized and adaptive navigation solution. The proposed system uses a combination of Dijkstra's Algorithm, Google Maps Application Programming Interface and real-time traffic information to produce the most efficient and accurate routes. It also has a hazard reporting feature that allows users to share updates on accidents, road closures, police presence, and other disruptions. Other features include English and Tagalog voice navigation, a built-in speedometer with overspeed warnings, two-factor authentication for secure access, a favorites feature for easy recall of commonly traveled routes. The system was developed following an iterative prototyping approach with user feedback and validated and filtered with data collected from local drivers and the San Juan City Traffic and Parking Management Office to maintain accuracy and usability. Its area of focus is private vehicles, motorcycles, and taxis that are operating within San Juan City. Findings indicate that the system offers better route guidance, minimizes traveling time, and improves the safety of commuters by combining algorithmic route optimization and community-based hazard reporting. This study illustrates the role of localized systems in ensuring safer and efficient mobility in urban settings. This study shows the need to design navigation tools based on the actual community needs and conditions. Through the case of San Juan City, the system demonstrates how technology can directly address daily traffic issues, can offer a safer traveling experience, and can also serve as an example that can be copied in other cities with complicated traffic schemes.

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Publication Details

Journal
International Journal of Latest Technology in Engineering Management & Applied Science
Published
2025-10-13
DOI
https://doi.org/10.51583/ijltemas.2025.1409000084
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Mobile-Based Smart Transport Route Optimization and Hazard Reporting System for San Juan

Alan Tan, Jester Mackenzie L. Guinto, Kvan Jazer A. Escalona, Cristian Jacob M. Eron et al.
International Journal of Latest Technology in Engineering Management & Applied Science
Traffic Prediction and Management Techniques
article

Mobile-Based Smart Transport Route Optimization and Hazard Reporting System for San Juan

Alan Tan, Jester Mackenzie L. Guinto, Kvan Jazer A. Escalona, Cristian Jacob M. Eron, Silas A. Flores, Ronald Fernandez
article en

Abstract

Abstract: The aim of this study is to develop a Mobile-Based Smart Transport Route Optimization and Hazard Reporting System that could improve navigation, minimize travel time, and increase road safety in San Juan City. The complex road system of the city and the ever-changing traffic rules, such as one-way and two-way rules based on time, pose great challenges to drivers, which often result in congestion and unintended traffic violations. This study solves these problems by giving a localized and adaptive navigation solution. The proposed system uses a combination of Dijkstra's Algorithm, Google Maps Application Programming Interface and real-time traffic information to produce the most efficient and accurate routes. It also has a hazard reporting feature that allows users to share updates on accidents, road closures, police presence, and other disruptions. Other features include English and Tagalog voice navigation, a built-in speedometer with overspeed warnings, two-factor authentication for secure access, a favorites feature for easy recall of commonly traveled routes. The system was developed following an iterative prototyping approach with user feedback and validated and filtered with data collected from local drivers and the San Juan City Traffic and Parking Management Office to maintain accuracy and usability. Its area of focus is private vehicles, motorcycles, and taxis that are operating within San Juan City. Findings indicate that the system offers better route guidance, minimizes traveling time, and improves the safety of commuters by combining algorithmic route optimization and community-based hazard reporting. This study illustrates the role of localized systems in ensuring safer and efficient mobility in urban settings. This study shows the need to design navigation tools based on the actual community needs and conditions. Through the case of San Juan City, the system demonstrates how technology can directly address daily traffic issues, can offer a safer traveling experience, and can also serve as an example that can be copied in other cities with complicated traffic schemes.

International Journal of Latest Technology in Engineering Management & Applied ScienceVol. 14(9)
University of the Philippines Manila (PH)
Openalex Percentile: Top 69%
Traffic Prediction and Management Techniques
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