A Deep Learning-Powered Intelligent System for Crowd Management and Seamless Navigation for Cultural Heritage Exploration

In today's bustling world of tourism, navigating cultural heritage sites efficiently and effectively poses a significant challenge for new visitors. From the daunting task of organizing a coherent route to discovering must-visit points, parking availability, ticket prices, and suitable modes of transportation, tourists often find themselves wasting precious time and effort. Furthermore, the absence of a centralized platform for booking tickets and the lack of time slot allotment exacerbate issues of traffic congestion and inconvenience. Also, garbage disposal, and waste management at these sites a point of concern. This manuscript works on these challenges by utilizing the power of machine learning technologies. The authors in this manuscript propose an intelligent system for a systematic and crowd-free guide to navigating cultural heritage sites. The system optimizes routes based on user preferences, traffic conditions, and real-time feedback, ensuring an enhanced and personalized experience for every tourist. Moreover, the proposed system provides essential details such as parking availability, ticket prices, travel costs, and recommended modes of transportation to streamline the planning and minimize uncertainty. It also offers assistance in finding food, stay, and shopping options. The system also provide facility of automatic onsite waste segregation. The work is useful in providing real-time and personalized user experiences at heritage sites.