Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67481
Volume:
10 |
9 |
Sep 2026
Pages:
1-7
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.

Department of Computer Science Engineering
East West Institute of Technology, Bengaluru, India

Department of Computer Science Engineering
East West Institute of Technology, Bengaluru, India

Department of Computer Science Engineering
East West Institute of Technology, Bengaluru, India

Department of Computer Science Engineering
East West Institute of Technology, Bengaluru, India

Department of Computer Science Engineering
East West Institute of Technology, Bengaluru, India
Modern travelers navigate a fragmented ecosystem of disconnected tools for booking, navigation, accommodation, and emergency support — increasing cognitive load and safety risks. To address this, we develop SMART-ROUTE, a unified mobile application consolidating the entire travel workflow in one interface. Users input a source, destination, trip duration, budget, group size, and travel category (Solo, Couple, Friends, or Family). The platform generates a structured day-wise itinerary with hotel suggestions, transport options, flight data, local attractions, AI-generated guidance, and sustainability insights. An embedded map renders the route, delegating navigation to Google Maps. One-tap emergency shortcuts connect travelers to hospitals, police, fuel stations, and mechanics, while a context-aware AI assistant supports the journey throughout. Authenticated users can persistently store and retrieve trips via MongoDB Atlas. The client is built on React Native with Expo; the server uses Node.js and Express.js with JWT authentication and Mongoose for data management. The platform advances SDG 11 by promoting sustainable and responsible tourism. This work presents a functional prototype; performance benchmarking and large-scale user studies remain as future work.
KEYWORDS
This paper presents SMART-ROUTE, a unified mobile travel-planning platform designed to address the fragmentation that characterizes conventional trip preparation workflows. By consolidating itinerary generation, hotel and transport recommendations, flight information, attraction discovery, route visualization, emergency support, and an AI travel assistant within a single React Native application, the system delivers a cohesive end-to-end planning experience that existing tools — evaluated individually — do not provide. The backend, built on Node.js and Express.js with JWT authentication and MongoDB Atlas persistence, supports multi-trip storage scoped to authenticated users. Functional evaluation across varied input combinations confirms that all implemented features operate correctly at prototype scale. The work explicitly distinguishes implemented functionality from proposed functionality and does not report performance benchmarks or user-adoption figures, as these were not within the scope of the current prototype. The integration gap identified in the literature — the absence of a deployable system combining intelligent itinerary generation with navigation, emergency access, and an AI assistant — is addressed here at prototype level. Future work will prioritize quantitative performance evaluation, large-scale user studies, real-time weather integration, live pricing APIs, and progressive expansion toward a production-ready deployment. SMART-ROUTE's alignment with SDG 11 through sustainability-oriented recommendations and consolidated travel planning represents an early step toward more responsible and informed tourism behaviour.
[1] A. Karras, C. Karras, D. Tsolis, S. Sioutas, and I. Giannakos, "Adaptive tourism recommendation models using deep learning and collaborative filtering," IEEE Access, vol. 12, pp. 45321–45338, 2024. [2] P. Wang, Y. Zhang, and H. Liu, "AI tour-guide services: Outlook and direction from a lifelong machine learning perspective," Journal of Hospitality and Tourism Technology, vol. 12, no. 3, pp. 512–528, 2021. [3] S. Manoharan, R. Prabhu, and K. Krishnamurthy, "Voyage Virtuoso: How artificial intelligence transforms tourism," in Advances in Smart Tourism Systems, Springer, Singapore, 2024, pp. 183–210. [4] E. Aribas and E. Daglarli, "Personalized travel recommendation integrating generative AI with personality-based models," Expert Systems with Applications, vol. 238, pp. 121–134, 2024. [5] G. Srikanthan, R. Meenakshi, and P. Anandan, "An AI-driven smart tourism platform for personalized, safe, and sustainable travel planning," International Journal of Advanced Computer Science and Applications, vol. 16, no. 2, pp. 78–91, 2025.
Publication Date
9/26/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
1
Total views since publication
PDF Downloads
5
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...