Skip to main content

University data experts team up with local company to improve road safety

Data analytics experts at Queen’s University Belfast have teamed up with local company See.Sense to create an intelligent bike light, which they say could help to improve road safety.
June 20, 2017 Read time: 2 mins

Data analytics experts at Queen’s University Belfast have teamed up with local company See.Sense to create an intelligent bike light, which they say could help to improve road safety.

See.Sense created the world’s first intelligent and connected bike light, which uses advanced sensor technology to monitor and react to its environment, helping to make the cyclist visible when they most need to be. Now, The university’s researchers are working with the company and are using a new type of data analytics to develop the light further.

Special sensors, which are built in to the bike light, collect information on the road surface in real time and analyse the cyclist’s activity. Through an app, the data is then processed using sophisticated analytics methods and mathematics.

They claim the latest updates mean that accurate sensor data collected by the light could be used to plan better infrastructure and create smart cities. By applying advanced analytics and data visualisation, the team could use this anonymised and aggregated data to work with a city to design better infrastructure and policies.

It also means the light can detect if a cyclist has had an accident or near miss, or hotspots where they should take extra care, as well as alerting local authorities if a road needs repairing.

The bike lights are currently on sale and closed data trials are currently underway in several cities around the world.

Related Content

  • Airborne traffic monitoring - the future?
    March 1, 2013
    A new frontier in the quest to monitor road traffic is opening up… but using airborne drones to reduce the jams comes with some thorny issues. Chris Tindall reports. Imagine if you could rely on a system that provided all the data you needed to regulate traffic flow, route vehicles and respond swiftly to emergencies for a fraction of the cost of piloting a helicopter. That system exists, but as engineers and traffic managers start to explore the potential of unmanned aerial vehicles (UAVs) – more commonly k
  • Viaduct deck renewal creates detour dilemma for MassDOT
    May 26, 2016
    As the deck renewal of the I-91 viaduct in Springfield gets underway, David Crawford looks at the preparation and planning to ease the resulting traffic congestion. Accommodating the deck renewal of a 4km-long/four-lanes in each direction viaduct in the heart of Springfield (Massachusetts’ third largest city), has involved the state’s Department of Transportation (MassDOT) in a massive exercise in transport research and ITS-based area-wide preplanning and traffic management. Supporting a workzone of well ab
  • Deriving data to tackle tribal road crashes
    June 14, 2017
    David Crawford looks at a new initiative to deal with high crash and fatality rates on America’s tribal roads. According to the US Centres for Disease Control and Prevention, on average two members of the country’s indigenous communities - American Indians or Alaskan Natives (AI/AN) - die every day in motor vehicle crashes. This represents a far higher percentage than that of the country’s general population. Historically, the US states with the worst records are Wyoming, South Dakota, Montana, North Dakot
  • Gearing up for IntelliDrive cooperative traffic management
    February 1, 2012
    Beginning in the first quarter of 2010 it became evident that the IntelliDrivesm programme direction had been reestablished, by the USDOT's ITS Joint Program Office (JPO), after being adrift for a few years. The programme was now moving toward a deployment future and with a much broader stakeholder involvement than it had exhibited previously. By today not only is it evident that the programme was reestablished with a renewed emphasis on deployment, it is also apparent that it is moving along at a faster pa