Nebula Labs is a small technology company specialising in mobile app development and bespoke software that has grown to a business of seven people since it was started by founders Dylan McKee and Nic Flynn straight out of university nearly four years ago.
The business, which is based in Carliol Square, Newcastle upon Tyne, has attracted some impressive clients and has worked for organisations including the NHS, AkzoNobel and North Tyneside Council.
To support the Cobalt Business Park in North Tyneside, , in developing its digital offering. Around 14,000 people work at Cobalt, which carries out an annual travel survey of workers , such as how many buses or cycle racks may be needed.
Nebula Labs was asked to help them automate this survey so that
We were looking at how we could make the travel data more dynamic than just once a year and get it to them faster and cheaper
By (NICD), Nebula Labs was able to develop an app that could track journeys and automatically work out whether a worker is travelling on foot or by bicycle, car, bus or Metro train.
If the app is adopted it could put an end to the need for an expensive physical survey. During the project they:
Although Nebula Labs has a great deal of expertise in digital technologies, to develop the survey app.
They initially approached the Arrow project at Newcastle University, which matches businesses seeking to innovate with academics and experts, and they were quickly matched with NICD. Arrow is part-funded by the European Regional Development Fund.
Initially, Nebula Labs was advised to gather more data and so they recruited 28 volunteers on the park who downloaded the app so that journeys could be monitored over a three-month period. Although the data was anonymous, the app followed individual journeys, recording information such as longitude, latitude and speed, and provided around 700 data points for the project.
The NICD team then worked with Nebula Labs to identify an off-the-shelf model that could be used to analyse the data and .
McKee explains: “The machine learning aspects of the model can increase its accuracy. As you feed more data through it, the machine can learn the patterns and look for more patterns. And .”
The model, for example, recognises that someone traveling 60mph is unlikely to be a cyclist or a pedestrian. But it also looks for more subtle patterns, for example people who are travelling faster but with stationary periods may be waiting on a platform.
By identifying such patterns in the data, Nebula Labs has been able to and this has been achieved by monitoring only a small number of journeys. The company intends to carry out more work to increase this success rate even further by allowing the model to analyse a larger number of journeys.
We were able to come up with a really good solution that pushed the boundary of the app side of things and brought in some really intelligent machine learning
McKee says: “The project went really well because and we are specialists in the technology that we work with. So, because we brought our skills from the app sector and they added their expertise in AI, data analysis and machine learning.”
The and they are considering how it might be used for other business parks and transport authorities.