Vibhor Sharma, Ashutosh Kumar Choudhary, Deepak Srivastava, Suman Pant, Pramod Kumar and Mohit Payal
Abstract
The proposed intelligent information system for social tourism aligns closely with global environmental sustainability policies and the United Nations Sustainable Development Goals (SDGs), particularly SDG 11(Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action). By utilizing real-time user-generated data, geo-tagged information, and dynamic user ratings, the system supports evidence-based decision-making for sustainable tourism planning. The integration of the Maximum-Stack algorithm with haversine distance enables optimized route selection, reducing unnecessary travel, fuel consumption, and associated greenhouse gas emissions. Additionally, ontology-based modeling of tourist destinations and user interests facilitates balanced tourist distribution, helping policymakers mitigate over-tourism and protect ecologically sensitive sites. The continuous monitoring of user reviews further enables the identification and promotion of environmentally responsible destinations and practices. Thus, the proposed system serves as a policy-support tool for smart and sustainable tourism governance by enhancing resource efficiency, minimizing environmental impact, and fostering responsible tourist behavior in alignment with national and international Sustainability frameworks.