Dual-Purpose IoT Systems in Smart Tourism: A Systematic Review of Frameworks for Crowd Management and Destination Sustainability

Integration of the Internet of Things (IoT) in Smart Tourism Destinations (STDs) has transformed physical travel environments into data-driven ecosystems, yet systematic evidence regarding architectural trade-offs, empirical performance bounds, and technical user adoption models remains fragmented. Following the PRISMA 2020 protocol and the SPICE question formulation framework, this systematic literature review synthesizes 56 core studies (38 empirical and 18 conceptual) identified from Scopus and secondary repositories through 2026. The architectural synthesis reveals a structural dominance of Centralized Cloud Computing (67.9%, n = 38), whose high latency (>1500ms) limits real-time responsiveness. Conversely, Decentralized Edge (17.9%, n = 10) and Hybrid Cloud-Edge (14.3%, n = 8) architectures achieve sub-500 millisecond response times, ensuring bandwidth optimization and offline operational resilience. Quantitative synthesis of empirical studies establishes consistent operational impact boundary ranges: operational efficiency gains (+20% to +45\%), energy and facility maintenance cost savings (-15% to -35%), and visitor satisfaction increases (+10% to +30%). To explain user adoption dynamics, this study proposes an Extended Technology Acceptance Model (Extended TAM) positioning network latency, system reliability, and data privacy protections as critical technical antecedents to trust, perceived usefulness, and revisit intention. Strategic recommendations advocate for Destination Management Organizations (DMOs) to adopt multi-tiered hybrid computing topologies and privacy-by-design frameworks to balance real-time crowd mitigation with long-term governance.