The rapid rise of e-bikes presents an opportunity to enhance urban mobility. However, unlike the automotive sector, the cycling industry lacks real-time, connected data insights. The Spinovate project, led by See.Sense, aims to address this gap by leveraging AI-powered sensor technology to create a fully connected cycling ecosystem. This initiative will generate valuable data on rider behaviour, safety, and infrastructure conditions to improve cycling experiences, drive commercial innovation, and support city planning.

Data gaps in urban cycling

Cities across Europe are striving to reduce congestion, lower emissions, and promote active travel. Yet, traditional cycling data sources—such as census data, fixed counters, and accident reports—offer incomplete insights. These methods often lack key metrics, such as near-miss incidents and road surface conditions. This provides outdated information, limiting their use for real-time decision-making, and cannot track individual rider behaviour beyond basic GPS tracking.

Without comprehensive, real-time data, cities struggle to design safe and efficient cycling infrastructure. Furthermore, fleet operators lack insights to optimise performance, and businesses miss opportunities to enhance sustainability reporting.

AI-driven data for smarter cities

Spinovate will employ See.Sense’s patented sensor technology, on-board processing and AI to turn e-bikes into connected vehicles. This allows capturing advanced telemetry on braking, swerving, speed, dwell time, route-choices, road surface conditions, and rider behaviour. See.Sense’s technology monitors the cyclist’s environment up to 800 times per second, giving city officials a complete picture of the cyclist experience in their urban area.  

The solution includes smart cycling sensors and data collection to capture real-world cycling patterns, safety risks and road quality insights. Expert partner in AI and design thinking, the University of Exeter will lead the development of AI-powered data dashboards. For city planners, the data dashboard will provide safety heatmaps, infrastructure assessments and predictive insights; for fleet operators, the capability to generate rider safety scores, maintenance alerts and fleet optimisation insights; and for employers it will support ESG reporting with data on CO2 savings and active travel trends.

Pilot implementation in Dublin

The Spinovate pilot will run in Dublin with project demo host Dún Laoghaire-Rathdown County Council and project partner Moby Bikes, who will deploy sensors on 60 e-bikes from both public and private fleets. The pilot will focus on three key cycling environments: public bike sharing, private business fleets, and courier and delivery services. By analysing data from these diverse cycling use cases, the project will generate insights that can be applied and replicated across European cities to improve safety, infrastructure, and micromobility services.

Data insights for a more sustainable future

In the short-term, the data dashboards launched for city planners, employers, and fleet operators will provide real-time insights into cycling safety, road conditions, rider behaviour and the identification of high-risk areas and infrastructure improvement needs. In the longer term, it is envisaged that the solution will be an integral part of urban smart mobility ecosystems, enhancing multi-modal transport planning and providing a European-wide standard for cycling data insights. This will enable the construction of safer and more efficient cycling infrastructure in a data-driven manner.

The Spinovate project is set to improve urban cycling by providing the real-time, connected data needed to enhance safety, improve infrastructure, and unlock new business models. By leveraging AI and sensor technology, this initiative aligns with the EU’s strategic vision for active mobility, while helping to foster a competitive and sustainable European cycling industry.

Read more about EIT Urban Mobility’s Innovation projects here.