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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM53005
Volume:
9 |
10 |
Oct 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Traditional navigation tools often fall short in addressing the growing complexities of urban commuting, such as traffic congestion, manual toll checks, and accidental speeding, leaving drivers reliant on multiple fragmented applications. This system resolves these persistent challenges by combining real-time route planning, live traffic analytics, toll booth notifications with automatic balance reminders, and speed limit alerts into one seamless mobile experience. Built using a structured Web Engineering methodology—including communication, planning, modeling, and deployment—the platform employs a Flutter-based front end with a back end powered by Node.js or Django REST. Integration with APIs such as Google Maps and FASTag ensures accurate and up-to-date information, while data storage is managed through Firebase or PostgreSQL. The system is validated through Black Box Testing to guarantee performance, reliability, and user satisfaction. By reducing delays at toll booths, preventing speed violations, and delivering optimized alternate routes, the solution not only improves individual driving experiences but also enhances broader traffic flow and road safety. It simplifies travel planning, lowers operational costs, and minimizes the need for multiple third-party tools. The app’s automated notifications and real-time data processing empower drivers with timely, actionable insights—promoting safer, more efficient, and environmentally conscious transportation habits. Ultimately, this all-in-one, intelligent mobility assistant showcases how integrated smart systems can reshape commuting, enhance digital mobility infrastructure, and set new standards for smart transport solutions.
KEYWORDS
Publication Date
10/13/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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