Devaprabha, Devika Yesodharan and Wang, Jia ORCID: https://orcid.org/0000-0003-4379-9724 (2026) An AI-powered location-based recommendation system for personalized urban mobility. In: 2026 33rd International Conference on Geoinformatics (Geoinformatics). Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey. ISBN 979-8319522993 ISSN 2161-0258 (Print), 2161-024X (Online) (doi:10.1109/Geoinformatics72247.2026.11665031)

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Abstract

The increasing availability of heterogeneous spatial and contextual data sources presents both an opportunity and a challenge for location-based decision support systems. This paper presents an AI-powered recommendation system designed to facilitate personalized urban mobility while enhancing users' sense of place. The proposed system integrates multiple open data sources through a unified fusion pipeline that aligns various data to support location-based recommendations. Data sources include UK police crime statistics, Ticketmaster event listings, OpenStreetMap points of interest (POIs), online news articles, and routing data. The proposed system comprises four components: a dynamic scoring module for safety and popularity assessment, a conversational AI interface supporting natural language location queries, a personalized recommendation engine informed by user interaction behaviors, and a journey planner that provides users with ranked routes based on safety. The results confirm real-time responsiveness across all four components and contextually meaningful outputs across diverse query types. The key contributions of this work are: (i) a scalable, timely spatial data fusion pipeline for multi-source urban data; and (ii) an AI-augmented decision support framework that promotes more informed and safer urban mobility.

Item Type:	Conference Proceedings
Title of Proceedings:	2026 33rd International Conference on Geoinformatics (Geoinformatics)
Additional Information:	2026 33rd International Conference on Geoinformatics (Geoinformatics) DOI: 10.1109/Geoinformatics72247.2026. Singapore 19th - 22th July 2026.
Uncontrolled Keywords:	safety, modeling, timing, planning, labeling, application programming interfaces, artificial intelligence, recording, current displays, location, natural language processing, Machine Learning, conversational AI, safety, popularity, routing
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	05 Oct 2026 09:55
URI:	https://gala.gre.ac.uk/id/eprint/54611

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