Tourist experiences: a systematic literature review of computer vision technologies in smart destination visits

Abstract

Purpose: This study investigates the applications of computer vision (CV) technology in the tourism sector to predict visitors' facial and emotion detection, augmented reality (AR) visitor engagements, destination crowd management and sustainable tourism practices. Design/methodology/approach: This study employed a systematic literature review, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses methodology and bibliometric study on research articles related to the tourism sector. In total, 407 articles from the year, 2013 to 2024, all indexed in Scopus, were screened. However, only 150 relevant ones on CV in Tourism were selected based on the following criteria: academic journal publication, English language, empirical evidence provision and publication up to 2024. Findings: The findings reveal a burgeoning interest in utilizing CV in tourism, highlighting its potential for crowd management and personalized experience. However, ethical concerns surrounding facial recognition and integration challenges need addressing. AR enhances engagement, but ethical and accessibility issues persist. Image processing aids sustainability efforts but requires precision and integration for effectiveness. Originality/value: The study’s originality lies in its thorough examination of CV’s role in tourism, covering facial recognition, crowd insights, AR and image processing for sustainability. It addresses ethical concerns and proposes advancements for a more responsible and sustainable tourist experience, offering novel insights for industry development.