Smart Tourism and Digital Transformation: Evaluating the Role of IoT and AI in Enhancing Tourist Experiences

Abstract

Abstract: Purpose: To examine the role of Internet of Things (IoT) infrastructures and Artificial Intelligence (AI) engines in the process of travelling to smart tourist destinations and in creating a framework of multidimensional measures of technical performance, user behavior, and satisfaction. This broader role now focuses on scalability to variable global destinations with emerging integrations of 5G to provide ultra-low latency services.

Materials and Methods: The explanatory sequential design utilizing mixed-methods was adopted at one of 2 pilot-sites, namely, the heritage open-air museum (Site A) and an urban cultural district (Site B). In phase one, 50 IoT sensor nodes (BLE beacons, environmental sensors, edge-processing crowd cameras) assembled at each location, and included two AI modules; a hybrid recommendation engine and transformer-based conversational agent. End-to-end latency, packet loss, sensor accuracy, energy consumption, recommendation and chat-bot latency, recommendation precision-recall, dwell time and satisfaction scores were quantitative data (N=400 visitors). Phase two involved semi structured interviews of 60 stakeholders (interviews with tourists and site managers). Triangulation of results was made by statistical analyses (t-tests, regression) and thematic coding, which is now supplemented by predictive modeling to make the analysis scalable in the future.

Findings: Site B had a much lower latency (120+-15 ms vs. 150+-20 ms), a lower packet loss (1.2+-0.3% vs. 2.5+-0.5%), more composite sensor accuracy (95.4% vs. 92.5%), and more uptime (99.1% vs. 97.8%) than Site A (all p<0.001, Cohen d[?]0.5). Site B had 40 and 20% faster recommendation throughput and chat-bot responsiveness, respectively) with higher visitor satisfaction (4.5+-0.4 vs. 4.2+-0.5) and higher recommendation F1 scores (0.85 vs. 0.82). The qualitative findings emphasized the importance of reliability of the infrastructures in the formation of positive user perceptions and efficiency in behavior, and new focus was placed on the AI-IoT synergy as predictive crowd management.

Inference: The implementation of IoT and well-optimized AI-based systems play a critical role in providing responsive and individual tourism services. The suggested evaluation framework provides practical advice to destination managers and technology providers on how to maximize smart tourism implementations, which are now also applied to the sustainability measures such as reduction of carbon footprint through streamlined visitor flows..