Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

ExhibitXplorer: Enabling Personalized Content Delivery in Museums using Contextual Geofencing and Artificial Intelligence

Version 1 : Received: 28 August 2023 / Approved: 29 August 2023 / Online: 29 August 2023 (09:58:41 CEST)

A peer-reviewed article of this Preprint also exists.

Ivanov, R. ExhibitXplorer: Enabling Personalized Content Delivery in Museums Using Contextual Geofencing and Artificial Intelligence. ISPRS Int. J. Geo-Inf. 2023, 12, 434. Ivanov, R. ExhibitXplorer: Enabling Personalized Content Delivery in Museums Using Contextual Geofencing and Artificial Intelligence. ISPRS Int. J. Geo-Inf. 2023, 12, 434.

Abstract

In recent years, there has been an increasing demand for personalized experiences in various domains, including the cultural and educational sectors. Museums, as custodians of art, history, and scientific knowledge, are seeking innovative ways to engage their visitors and provide tailored content that enhances their understanding and appreciation of the exhibits. This article presents ExhibitXplorer, a distributed architecture service that leverages geofencing, artificial intelligence, and microservices to enable personalized content delivery in museums. By combining implicit and explicit segmentation of museum visitors and utilizing the GPT API for content generation, ExhibitXplorer offers a dynamic experience to different visitor segments, including researchers, students, casual visitors, and children. The system utilizes push notifications triggered by visitor location changes, allowing seamless delivery of personalized information both indoors and outdoors. Tests were conducted to evaluate the user experience of visitors to an outdoor ethnographic museum. The results showed that 55% of the test participants were satisfied and 45% very satisfied with the way personalized content was delivered.

Keywords

Personalized content delivery; Smart Museums; Contextual Geofencing; Artificial Intelligence; Visitors Satisfaction

Subject

Computer Science and Mathematics, Computer Science

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