Predictive Analytics for Heritage Site Visitor Patterns

Abstract

This study explores the relationship between predictive analytics and heritage site management, using a survey conducted across four Indian heritage cities involving 893 participants. The research uses advanced predictive modelling techniques and IoT technologies to understand visitor interactions at heritage sites. The study emphasises cultural sensitivity and the impact of diverse cultural backgrounds on visitor behaviours. It provides a comprehensive understanding of heritage site engagement, promoting long-term sustainability and informed strategic planning, conservation efforts, and community engagement initiatives. The research also explores climate change's impact on visitor patterns, integrating climate-related variables into predictive models to facilitate adaptive heritage site management. This study not only advances the theoretical understanding of predictive analytics in heritage site contexts but also offers practical, ethical, and culturally informed strategies for sustainable heritage management and safeguarding cultural heritage for future generations.