Report: Streamr’s Real-time Transport Data Hackathon
Last week, in a part of the UK fittingly referred to as the “Midlands Engine”, Streamr brought together some key regional players involved in transport. Devs and other sector experts from Birmingham City Council, Transport for West Midlands, Oxfordshire County Council, Birmingham in Real Time (part of Birmingham City University), the Big Data Corridor initiative and others joined Streamr core project members for a hackathon to figure out how to better access, visualise and trust transport related real-time data.
There were some ambitious aims. Would it be possible to provide greater coverage and confidence in data streams? Could we scope better ways of understanding the live events that take place on road networks? And by utilising those live insights, would it be possible to reduce congestion, journey times and emissions, improve safety and driver experience on both urban and rural roads?
These aims tied in with Birmingham’s network resilience strategy and putting data infrastructure in place to manage the forthcoming network of connected autonomous and electric vehicles.
There were, as always, challenges that had to be overcome when working with some of the datasets. Birmingham in Real Time (BiRT) demonstrated how to parse heavy DATEXII transport feeds to make it much easier for developers to work with. With that done, local authorities would, it was felt, be in a much better position to verify circumstances by being able to access multiple data sources for a single event.
During the full day event, participants achieved some great integrations and visualisations using the Streamr Editor. Birmingham City Council’s Andy Radford managed to stream real-time data from traffic lights. Coded via his iPhone using the BCC API, Andy managed to display Signal Phase and Timing (SPaT) data. In this instance, the Editor tool clearly reduced the need for parsing data.
The team from BiRT were able to get SCOOT data — speed and flow data produced by vehicle detectors embedded in the road surface — live streamed through the Streamr platform. Both SPaT and SCOOT are important datasets for urban traffic control measures.
Of course this first hack is just the start. Now that group members have a feel for working with Streamr’s toolstack, we’ll continue to explore which data can be made available through the Marketplace and how the Editor and data delivery Network can reduce the amount of time developers need when working with heavy files. And as more transport related data gets added to the Marketplace, we’ll explore fusing these together with open and other third party datasets to enhance value and attract more subscribers.
We also identified that better access to real-time data streams, including by leveraging data from cars already on the network, could lead to significant cost savings by lowering the need for physical roadside infrastructure. That’s an insight we can aim to make more realisable at scale through Streamr’s ongoing pilots and partner ecosystem development.
