SMART TOUR: AN AI-DRIVEN MULTILINGUAL CONTEXT-AWARE TOURIST GUIDE PROGRESSIVE WEB APPLICATION

IBEKWE, KOSIOCHUKWU HASEL (2026) SMART TOUR: AN AI-DRIVEN MULTILINGUAL CONTEXT-AWARE TOURIST GUIDE PROGRESSIVE WEB APPLICATION. Other thesis, Godfrey Okoye University, Enugu Nigeria.

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Abstract

The tourism sector plays a critical role in economic development, yet tourists in developing regions such as Enugu State, Nigeria continue to face significant challenges in accessing personalised, context-aware digital tourism information. This study presents Smart Tour — an AI-driven, multilingual, context-aware tourist guide Progressive Web Application developed to address this gap. The system was built on a full-stack JavaScript architecture comprising React as the frontend PWA, Node.js with Express as the RESTful API backend, and Supabase-managed PostgreSQL as the relational database. A hybrid AI recommendation engine was implemented, combining knowledge-based pre-filtering, content-based cosine similarity ranking, and collaborative filtering enhancement. The system supports seven languages via i18next with automatic browser language detection, renders an interactive GPS-linked map using React-Leaflet and OpenStreetMap, and is deployed as an installable PWA with offline capability through a Workbox service worker. Developed using Agile Scrum methodology across eight two-week sprints, all twenty functional test cases passed. Non-functional testing confirmed an initial load time of 2.1 seconds, a recommendation API response time of 1.3 seconds, and a Lighthouse PWA score of 92 out of 100, demonstrating that a handcrafted hybrid scoring model is a viable and interpretable alternative to machine learning approaches for tourism recommendation in resource-constrained emerging market contexts. Keywords: Smart Tourism, Progressive Web Application, Artificial Intelligence, Recommendation System, GPS, Multilingual Support, Agile Scrum, Enugu State, Nigeria.

Item Type: Thesis (Other)
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Computing And Information Technology (FACIT)
Depositing User: Cynthia Ugwuoti
Date Deposited: 24 Jul 2026 14:10
Last Modified: 24 Jul 2026 14:10
URI: http://eprints.gouni.edu.ng/id/eprint/6000

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