Kogii Lights The Way Ahead For Smart City Cyclists

Kogii lights the way ahead for smart city cyclists

Our Start-up of the Week, Kogii, is developing an innovative and feature-rich smart bike light to improve real-time safety for cyclists.

“Kogii is a smart light that uses integrated sensors to understand what makes a dangerous road dangerous for cyclists,” Kogii co-founder Karl Roe explained.

“There have been many innovations in the cycling industry that improve real-time visibility and safety, but there is very little real-world data that allows us to learn about what makes one road more dangerous than another.”

Kogii aims to change that, by collecting completely anonymous data about a cyclist’s surroundings as they cycle.

The market

“Initially, we’re going to target cyclists, particularly cyclists who are interested in technology,” said Roe. “Any cyclist that is looking to invest in a really good product is a potential customer.

“We plan to expand by conducting a large crowdfunding campaign to really boost the company, and we want to also target governments/councils who will be interested in the data we collect to improve road safety.”

Karl Roe is a PhD researcher at University College Dublin (UCD) with a master’s degree in computer science.

Andrea Pignanelli is a software engineer at a major tech company in Dublin and also has a master’s degree in computer science from UCD.

Callan Eldon is an electronic and mechanical engineer from Dublin Institute of Technology.

The venture was recently declared overall winner of the 2018 UCD Startup Stars Programme for student entrepreneurs and received a €3,000 cash prize.

This followed a four-week mentoring programme at NovaUCD. The aim of this mentoring programme is to assist the participating students in refining their start-up ideas through a series of structured workshops, including taught content from industry experts, interactive workshops and regular pitching sessions.

The technology

Kogii looks at how the cyclist is moving, along with their external environment. When the data from these two variables is combined, really interesting things about our roads can be learned.

“We want to look at the cyclist’s surroundings and see how their behaviour/movement changes depending on the environment,” said Roe.

“For example, if we see there are a lot of falls, dramatic swerves and sudden braking in a region where there are many close interactions with cars, we can deduce that area of road is dangerous. We aim to combine this data with locations of reported crashes and fatalities in the past to further verify our analysis and predictions.

“Ultimately, we want Kogii lights in every city where there are cyclists. The technology we have is fully scalable, and we hope one day to have a map where you can visualise all dangerous roads in every city. Even if one accident is prevented, or one life is saved, anywhere in the world, we’ve achieved our ultimate goal.”

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