International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

This study presents the development of an AI-assisted digital guide designed to support cultural and religious tourism through the integration of interactive mapping and text-to-speech technologies. The project focuses on the cultural heritage of the city of Svishtov, Bulgaria, where several historically significant temples and monasteries are organized into a structured digital cultural route. Historical and descriptive information about each site was collected from local historiography and field observations and subsequently transformed into a digital format suitable for web presentation. An interactive map created in Google Maps allows users to visualize the spatial distribution of the sites and navigate the cultural route. In addition, an AI-generated audio guide based on text-to-speech technologies provides accessible audio narration for each location, enhancing the interpretive experience for visitors. The platform integrates visual content, geographic navigation, and automated voice narration within a single digital environment. The proposed approach demonstrates how artificial intelligence tools and interactive mapping technologies can support the interpretation of cultural heritage, improve the accessibility of historical information, and create engaging digital experiences for visitors. The study highlights the potential of combining digital humanities approaches with modern AI technologies for the promotion of local cultural heritage and the development of innovative tourism applications.

This study presents a data-driven exploration of the demographic evolution of Veliko Tarnovo from 1878 to 2024. By compiling population data from official census records and statistical yearbooks, the project builds a unified dataset covering nearly 150 years of urban development. The analysis focuses on population dynamics by gender and total population growth, identifying key periods of expansion and decline. The visualizations were developed using Power BI, providing an interactive and intuitive dashboard that enables users to explore trends, compare periods, and observe long-term demographic shifts. The study highlights a sharp population increase during the socialist era (1950s–1980s), followed by a significant decline in the post-1990 period, interpreted in the context of socioeconomic transformations and migration processes. The research offers both historical insight and a modern methodological approach, demonstrating how business intelligence tools can be effectively applied in urban demographic analysis and digital heritage projects.