Revitalizing Mining Heritage Tourism: A Machine Learning Approach to Tourism Management

The convergence of Mining Heritage Tourism (MHT) and Artificial Intelligence (AI) presents a transformative paradigm, reshaping heritage preservation, visitor engagement, and sustainable growth. This paper investigates the dynamic synergy between these realms, probing how AI-driven technologies can augment the authenticity, accessibility, and educational significance of mining heritage sites. Focusing on the profound impact of AI on MHT, this study centers its examination on the Barr Conglomerate located in the culturally rich Pali District, India. Employing a mixed-methods approach involving survey data analysis and neural network modelling, the research work explores AI applications that enhance visitor experiences, interpret historical narratives, optimize resource allocation, and mitigate the adverse effects of over-tourism. The study meticulously navigates a vast landscape of AI technologies, spanning machine learning, natural language processing, and augmented reality, show-casing their potential to enrich encounters with mining heritage. While AI promises to revolutionize heritage management, the paper emphasizes the critical importance of ethical considerations and cultural sensitivities. Balancing innovation with preservation, the study advocates for an inclusive approach that honors diverse cultural values and encourages community engagement. Through this exploration, the paper delves into the practical implementation of AI, unveiling best practices lessons learned and illuminating challenges and opportunities. Ultimately, this research work envisions a future where AI empowers mining heritage to transcend temporal boundaries, cultivating immersive experiences resonating with authenticity, global understanding, and sustainable stewardship.

کلیدواژه ها:

Artificial intelligence ، Cultural Sensitivity ، Mining Heritage Tourism ، Sustainable Development ، Visitor Engagement