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

  • Bluetooth and Wi-Fi offer new options for travel time measurements
    November 20, 2013
    New trials show Bluetooth and Wi-Fi signals can be reliably used for measuring travel times and at a lower cost than an ANPR system, but which is the better proposition depends on many factors. Measuring travel times has traditionally relied automatic number plate (or licence plate) recognition (ANPR/ALPR) cameras capturing the progress of vehicles travelling along a pre-defined route. Such systems also have the benefit of being able to count passing traffic and have become a vital tool in dealing with c
  • When weather warnings get hyperlocal
    August 24, 2016
    David Crawford looks at new technologies to cope with the age-old problem of driving in bad weather. On the 10-year average, between 2005 and 2014 bad weather contributed to more than 1.5 million vehicle crashes in the US each year, resulting in more than 800,000 injuries and 7,400 deaths. These were the findings of analysis by Booz Allen Hamilton of NHTSA data which concluded that the loss of life, hospital treatment and damage to assets costs an annual average of $42bn.
  • Better liveability through more micromobility
    November 1, 2022
    Shared and micromobility offer new options, weaning urbanites off their cars, stitching existing mass transit combinations together. Andrew Stone looks at a report on transforming our cities
  • Machine vision - cameras for intelligent traffic management
    January 25, 2012
    For some, machine vision is the coming technology. For others, it’s already here. Although it remains a relative newcomer to the ITS sector, its effects look set to be profound and far-reaching. Encapsulating in just a few short words the distinguishing features of complex technologies and their operating concepts can sometimes be difficult. Often, it is the most subtle of nuances which are both the most important and yet also the most easily lost. Happily, in the case of machine vision this isn’t the case: