AI-Driven Information Systems for Sustainable Tourism: A Review of IoT and Big Data Applications
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Background: Converging technologies of Big Data and Internet of Things (IoT) in sustainable tourism need systematic review of existing applications, efficacy, and implementation issues to enable evidence-based strategies for development. Methods: Systematic review in line with PRISMA guidelines of five principal databases across eight years searched peer-reviewed articles. Systematic screening was used to select studies with high inter-rater reliability, as confirmed during study selection. Results: Three main application fields appeared with different evidence profiles. Customer experience enhancement was well empirically supported by AI-enabled personalization systems utilizing neural networks, collaborative filtering techniques, and IoT-enabled infrastructure, including smart environmental controls, wearable device integration, and automated service delivery. Sustainability applications offered compelling proof through IoT sensor networks facilitating real-time environmental monitoring, predictive crowd control analytics, and intelligent resource optimization with substantial efficiency gains over traditional methods. Ethical concerns emerged in substantial implementation hurdles: though most research recognized privacy and data management issues, few suggested feasible agendas for ethical data stewardship. Geographical analysis offered extreme urban-bias with rural tourism environments represented far less. Explainable AI methods were not forthcoming even as transparency requirements increased. The key implementation obstacles were infrastructure expenses, technical interoperability issues, and lack of skilled personnel, mainly impacting resource-scarce settings. Conclusions: There is support for the effectiveness of IoT and Big Data technologies for enhancing customer experiences and environmental sustainability in tourism contexts. However, there are key deficiencies in ethical frameworks, rural tourism applications, and explainable AI implementations. Research agendas include the creation of scalable solutions in diverse geographical contexts, tourism-specific privacy frameworks, and participatory governance frameworks. These findings inform evidence-based approaches to responsible smart tourism development that reconcile technological innovation with ethical regard and fair application in varied tourism settings.
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