Milton Keynes council recently presented the MK:Smart vision to the TM Forum 3rd Smart City in Focus Forum in Yinchuan, China. At the event Milton Keynes Council (MKC), shared the details of how the City of Milton Keynes plans to get there and various initiatives relating to how they plan to improve mobility, including data, and artificial intelligence (AI).
Leading Milton Keynes's smart city initiative, MK:Smart, is the MK Data Hub. It was developed for its commercial potential and innovation. This city-scale data hub allows onboarding of data from multiple sources, including live data feeds, to support IoT innovation.
The data hub pulls in data about movement in the city, including pedestrian and vehicle flow, and bus occupancy levels, etc. This data is used in various ways - for example, in a route-planning app (MotionMap) for citizens.
Artificial Intelligence (AI)
Milton Keynes is now working with a partner called Vivacity Labs to introduce artificial intelligence (AI) sensors across the whole city for transportation purposes.
These video sensors detect what’s going on in the environment, perform analysis and send a data package back to a platform. They are deployed at key junctions to provide a real-time view of movement across the whole city.
This aims to help with issues such as more efficient use of available parking spaces. There are 23,000 non-multi-story car parking spaces in Milton Keynes. These sensors can scan the area for spaces (an individual sensor is not needed for each parking space) and can even detect the difference between cyclists, pedestrians and cars.
Geoff Snelson (Profile), Director of Strategy & Futures, Milton Keynes Council: “You get a very rich set of analytics. Ultimately there is potential to connect this technology with traffic signals to provide a real-time demand-responsive signalling system."
Milton Keynes has also been doing a lot of work around autonomy with its trials of a small fleet of 40 autonomous ‘autopods’.
From next year, the city will be running them as a small-scale public transport service to understand the economics and logistics of using this kind of technology.
The pods use a 3D digital template to understand their environment and sensors to detect movement. They can then ‘decide’ how to interact and avoid collisions. As they learn more, they will grow less risk averse and move more freely.
The city is also working with motor manufacturers on how systems might evolve from driverless systems to full autonomy and how they might interact and work collectively with other modes of transport to form a holistic service.
To support this, the city is using technology such as radar sensors, which communicate with the autopods and vehicles about traffic, movement and potential collisions.