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July 03, 2020 4 min read

We’d like to extend a huge THANK YOU to all 800 participants of the See.Sense Smart Cycling project. With your help we crowdsourced ride insights across three european cities, mapping day-to-day cycling conditions and experiences like never before. We have compiled this webpage to share with you some of the findings from the project. 

Our Project: See.Sense Smart Cycling

In early 2019, following a highly competitive application process consisting of more than 130 applications from across Europe, See.Sense won a place on the European IoT Large-Scale Pilot project ‘SynchroniCity’.  During the project See.Sense partnered with BT to carry out three projects in Dublin, Manchester and Antwerp.

These projects set out to deliver new insights into the use of city transport infrastructure that can be used to encourage modal shift towards cycling. Using crowdsourced sensor data collected by the patented See.Sense IoT-enabled bike lights and accompanying app, aggregated insights were shared with the cities, enabling never-before-seen insights into the experience and safety of cyclists in each city. 

Across three cities we received 2,400 applications to join the project which saw 800 cyclists sharing their insights into cycling behaviour. Over the course of three months of data collection they generated almost 9 million data points collecting information such as location, speed, road surface quality as well as highlighting hotspot areas for cyclists swerving and heavy braking. Through the See.Sense app, participants were also able to provide qualitative feedback via in-app surveys as well as providing profile information, enabling a greater level of insight into the similarities and differences between different groups of cyclists.

What ride insights did we collect?

Route Popularity

As well as the data highlighting route popularity as shown in the graphics above, the unique See.Sense data enabled cities to see a number of different variables, giving a greater level of insight into the experiences of cyclists in their city.

Average Speeds And Dwell Times

The ride insights shared with See.Sense enabled us to rapidly map average speeds of cyclists throughout each city. These insights highlighted issues such as potential bottlenecks in the cycling network, showed alternative routes with fewer stops and also measured the impact of different types of cycling infrastructure on average speeds. They also allowed us to map dwell times at junctions - allowing the cities to identify areas where cyclists are having to wait a long time during their journeys.  

Road Surface Roughness

Here we can see the impact that road surface quality is having on the speed of cyclists in Manchester, with rougher roads (higher bars) resulting in relatively slower speeds (colour: red). Over the three months of the project, the quality of the road surfaces within each city has been measured, highlighting problem areas and creating the potential to inform maintenance schedules.

Post-Ride Surveys

Project participants were also able to share qualitative feedback via in-app surveys. Here a participant has highlighted their experience of using a network of underpasses to navigate a busy junction in Manchester.


Here we are seeing the difference in cycling experience between different streets in Manchester. The cyclists travelling on Wilmslow Road (green) are swerving more than those travelling on Moseley (top pink) or Fallowfield Loop (bottom pink).

Heavy Braking

As well as measure lateral swerving movements, See.Sense data is also able to map areas of heavy braking in the city. Here we can see that there are relatively fewer occurrences of cyclists braking heavily when travelling on the segregated infrastructure along the Grand Canal in Dublin.

Profile Data


The profile data provided by project participants has allowed us to map differences between different groups of cyclists in the city, based on gender, age and type of bicycle used. For instance, here we can see the difference in relative average speeds between e-bike users and ‘regular’ cyclists in Antwerp.

Temporal Analysis

The ride insights collected has enabled cities to identify prominent patterns in how their streets are used, filterable by time of day and days of the week. Here we can see the differences in the routes used throughout the day in Antwerp from (left to right) AM Peak (0600-0900), InterPeak (0900-1500) and PM Peak (1500-1800).

Coverage received

Events & Conferences

We have presented (or are due to present) our work on the SynchroniCity project at the following events:

  • AGI NI Conference (07 June 2019)
  • VeloCity Global, Dublin (25-28th June 2019)
  • ITS Europe Congress, Eindhoven (3-6 June 2019)
  • Cycle County Active County, Essex (5th-6th September 2019)

Press Articles

Next Steps

While the SynchroniCity project officially finishes on 6th September, we would encourage all participants (who get to keep their See.Sense ACE light!) to continue sharing their ride insights with See.Sense. We are currently engaged with each city to identify next steps and aim to undertake further projects with each. As such, having a continuous collection of ride insights over a longer period of time will enable further, more detailed analysis to take place.

We will be presenting the final results of the project to each city over the course of September and October and will send a final email to participants with project results after these have taken place. 

Once again we are incredibly grateful to the participants of our projects, thank you for being part of the SynchroniCity See.Sense Smart Cycling Project!

What is SynchroniCity?

SynchroniCity is a European Large Scale IoT Pilot project. The project is driven by a simple question: What would it take for a great data-driven solution in City “A” to readily work in City “B”? Starting in February, 18 cities and 40 companies will join the movement to redefine the social and economic potential of new services using the Internet of Things (IoT) and Artificial Intelligence (AI) in Europe and beyond by giving a real answer to that question.

Find out more about how See.Sense is working with Ride Insights to make cycling safer here