Integrating Generative AI and IoT for Sustainable Smart Tourism Destinations

Abstract

This paper aims to develop a groundbreaking approach to fostering inclusive smart tourism destinations by integrating generative artificial intelligence (Gen AI) with natural language processing (NLP) and the Internet of Things (IoT) into an intelligent platform that supports tourism decision making and travel planning in smart tourism destinations. The acquisition of this new technology was conducted using Agile methodology through requirements analysis, system architecture analysis and design, implementation, and user evaluation. The results revealed that the synergistic combination of these technologies was organized into three tiers. The system provides information, including place names, images, descriptive text, and an audio option for users to listen to the information, supporting tourists with disabilities. Employing advanced AI algorithms alongside NLP, developed systems capable of generating predictive analytics, personalized recommendations, and conducting real-time, multilingual communication with tourists. This system was implemented and evaluated in Suphan Buri and Ayutthaya, UNESCO World Heritage sites in Thailand, with 416 users participating. The results showed that system satisfaction was influenced by (1) the tourism experience, (2) tourism planning and during-trip factors (attention, interest, and usage), and (3) emotion. The relative Chi-square (χ2/df) of 1.154 indicated that the model was suitable. The Comparative Fit Index (CFI) was 0.990, the Goodness-of-Fit Index (GFI) was 0.965, and the model based on the research hypothesis was consistent with the empirical data. This paper contributions significant advancements in the field of smart tourism by demonstrating the integration of Gen AI, NLP, and the IoT and offering practical solutions and theoretical insights that enhance accessibility, personalization, and environmental sustainability in tourism.