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Train Station

Ignite: Rethinking Urban Mobility with Data

the challenge

Urban mobility planning often relies on outdated, fragmented data. City transit officials—like Alina in Tallinn—must make multi-million euro decisions, such as where to build new tram lines, without clear insights into how people actually move around the city. Gathering and analyzing this data is time-consuming and costly, leaving decision-makers overwhelmed and underserved.

the
IDEA

Ignite is a data platform that helps governments and private companies visualize urban mobility patterns more clearly. By integrating multiple data sources—telecom signals, real-time public transport, shared mobility usage, and demographics—the platform delivers actionable insights to support better planning. Users can explore mobility flows, analyze commute behaviors, and see optimized transit proposals tailored to their needs.

the
Process

This project was developed during a two-week EIT Digital Summer School in Tallinn. We began by identifying the key user: a city mobility planner in need of timely and reliable insights. Through ideation workshops, data exploration, and user scenario development, we shaped a concept that prioritized usability, automation, and visual clarity.

Solution & Strategy

As part of the summer school project, our team developed a full Business Model Canvas for Ignite. This framework outlines our key partners, value proposition, revenue model, and customer relationships, helping validate the business potential of the platform.
Value proposition
Ignite provides cities and businesses with:
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  • A centralized platform to view live mobility patterns
  • Instant insights without needing data science teams
  • Tools to simulate, filter, and visualize routes and behaviors
  • Downloadable reports for faster decision-making
Data Sources Used
Our prototype was designed to integrate:
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  • Telecom Data – Anonymized user location (via cell towers)
  • Public Transport Feeds – Real-time tram, bus, trolley tracking
  • Shared Mobility – Usage from scooter, bike, and car share services
  • Demographics – Age, income, occupation, education levels
  • Commuter Patterns – Mode share and time-of-day flows
Market Potential
Target users include:
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  • Local Governments – Optimize transit infrastructure and reduce congestion
  • Retailers – Analyze foot traffic and select store locations
  • Real Estate Developers – Study demand and growth potential in emerging districts
  • Marketing & Advertising Firms – Plan campaigns using commuter flow dataWith 204+ European cities and thousands of potential B2B partners, the market is broad and scalable

prototype

The interactive dashboard allows users to:
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  • Filter commuting data by time, age group, occupation, and gender
  • View modal splits (bike, tram, car, etc.) and usage trends
  • Simulate route scenarios
  • Export reports and visualizations for stakeholder use
Design focused on clarity, usability, and decision support, especially for non-technical users.
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