The proposed solution is a mobile network data-based mobility analytics platform that aggregates anonymized signaling data from extensive mobile network infrastructure to map movement patterns in real time. The system leverages data from base stations and hundreds of thousands of mobile devices, processing this information through sophisticated anonymization and aggregation algorithms that are fully compliant with GDPR requirements and ISO/IEC 27559:2022 standards for privacy-enhancing data de-identification. The platform delivers actionable insights through intuitive visualizations and comprehensive reports covering mobility flows, temporal trends, and visitor origin analysis. Users can access these insights through a convenient self-service portal or export data in CSV format for integration with existing
planning tools.
By leveraging both real-time and historical mobility data, the solution enables cities to monitor tourist flows dynamically across the city, identify peak visitation times and crowded areas, and gain deeper understanding of visitor origins and typical stay durations. This data foundation supports more effective crowd management strategies, optimized public transport routes, and evidence-based urban planning decisions, all while maintaining strict respect for individual privacy. The platform also helps municipal authorities maintain an appropriate balance between promoting tourism and preserving
residents’ quality of life by providing data-driven insights that can inform decisions about infrastructure investments, public safety measures, and resource allocation throughout the city.
