Data-Driven Urban Mobility Insights – URBANMOVE by Algebra Bernays University and Croatian Telecom
In a forward-thinking collaboration between Algebra Bernays University Zagreb and Croatian Telecom, part of the Deutsche Telekom Group, a new data system has been developed to analyse urban mobility patterns using anonymised mobile device records. The initiative, known as URBANMOVE, applies mathematical and spatial analysis to large volumes of aggregated telecom data to generate meaningful insights into how people move across cities.
Traditional methods like surveys and manual traffic counts often fall short in capturing the complexity of urban mobility. In response, URBANMOVE was designed to provide accurate, timely, and comprehensive insights into movement patterns across Zagreb. The goal was to support smarter urban planning, optimise transport systems, and enhance quality of life by aligning infrastructure with real mobility needs.
The system aggregates and analyses anonymised mobile records to deliver evidence-based tools for municipalities and planners. It also demonstrates the value of big data analytics in improving public services while safeguarding privacy.
This initiative contributes to the thematic areas of:
- Research and innovation
- Regional impact
Implementation and Impact
The project followed a structured process divided into several key steps:
- Key zones in Zagreb—business districts, residential areas, transport hubs, cultural and recreational sites—were selected to ensure diverse mobility scenarios.
- Aggregated records were analysed to understand spatial and temporal interdependencies.
- Time slices were chosen to test repeatability and seasonal dynamics.
- The team worked with Deutsche Telekom experts, city authorities, and external consultants to validate the prototype and plan for commercialisation.
The result was a validated prototype capable of processing large datasets and generating actionable insights. Supporting documents, such as market analysis and commercialisation plans, were produced, and the project qualified for grant funding under innovation and R&D frameworks.
Transferability
The methodology is highly adaptable and transferable to other urban environments. It can be replicated in cities with different layouts, densities, or transport systems, and extended to areas like tourism, emergency planning, and environmental monitoring.
Key lessons include:
- Early stakeholder engagement ensures alignment with practical needs.
- Scalability and flexibility must be built into the system.
- Data privacy and governance are essential.
- Insights should be communicated through user-friendly tools.
- Pilot replications in diverse settings can validate broader applicability.
Learn More
For further details, see the German Patent Office entry for the utility model: Mobilitätsverfolgungssystem auf der Grundlage mathematischer Analyse und mobiler Daten.
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