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The latest blog comes from Thames Valley Berkshire Live Lab's Sam Shean.

With the Live Lab coming to a close in the next few months and a lot of success under its belt, I wanted to use the blog to highlight our trials and share some of the lessons learnt.  

The £4.8m Live Lab, led by Reading Borough Council, was a large and complex project bringing together the six Berkshire unitary authorities with five commercial partners, Stantec, O2, Yunex Traffic, Smarter Grid Solutions, Shoothill and the University of Reading, to deliver a range of interconnected projects across potholes, congestion, air quality, energy and health. 

Our Live Lab explored several ways to reduce carbon emissions on our highway network, keeping data collection and sharing, and data analytics at the heart of our project. We recognised that in order to achieve our carbon reduction targets in transportation, we needed to take a proactive and holistic approach. For example, the need to reduce the use of cars was supported by our Innovation Valley rewards app which promotes active travel while the need to provide necessary EV charging infrastructure has been addressed through a Berkshire-wide study of EV growth. 

We also identified the need to better manage the impact of charging on the electricity grid. This can be achieved by optimising charging times when carbon intensity is at the lowest and balancing the demand for charging with other energy demands such as building energy use. To address this, we implemented building energy management systems across a number of buildings.

To address emissions along our roads, we trialled using network prediction systems to improve the use of datasets (ranging from signal loops to phone data) to optimise traffic lights thereby smoothing traffic flow and reducing environmental impacts. NOx was the focus of our trials in these areas, however, the lessons learnt apply to carbon reduction too. 

Even elements that are not so obviously related to carbon reduction have a role to play. For example, we trialled the use of automated pothole identification systems by mounting cameras coupled with image recognition and machine learning onto refuse vehicles. Better maintained highway surfaces improve vehicle efficiency and are more cycle-friendly, while fewer physical inspections reduces driving for highway inspectors. 

So, what have we learnt? Innovation is only a small part of delivering a successful project such as this. Whilst we can develop new technology in a silo, success in delivering complex cross-sector projects involves the collaboration of a wide range of different people within the authorities and private sector organisations. Because of this, extensive work is needed on stakeholder engagement to contact all parties relevant to the delivery, discuss the need for innovation, highlight the importance of the work (at a time when most already have busy schedules) and keep them engaged and supportive throughout the project. For our Live Lab, although we had good engagement across key stakeholders and the authorities, we found that there were still gaps that only came to light at the end of the project. 

As an authority, we collect a lot of data, but it is important not to underestimate the time and effort required to make that data useful, reliable and accessible for a given project. We have many legacy systems which are complex to extract data from, services where we don’t necessarily own the data, and datasets which are less complete or reliable than we initially expected. On the other side, private sector datasets can be large and reliably delivered, but we have to have the right services for the right applications - a large dataset does not necessarily have the granularity for all applications but can have a significant value when applied correctly. Ensuring that the groundwork is done in data ownership, quality and reliability is critical to enable us to make the best use of innovation. 

Over the next few months we are looking forward to publishing our findings and taking forward some of the key outcomes of the project.