World’s smartest car park is self-taught and costs next to nothing

Deep learning is finally moving out of research and into real-life, physical projects, with breakthrough innovation specialists Cambridge Consultants unveiling the world’s smartest car park. The system, aptly named Goldeneye, has taught itself to recognise cars and how those cars appear in spaces. It can do this without expensive physical infrastructure and in a range of lighting and weather conditions, day and night, even proving itself during recent severe snow in the UK.

Goldeneye uses a machine vision and deep learning solution developed entirely at Cambridge Consultants, along with the existing security camera and networking infrastructure on-site, to continuously monitor the availability of parking bays. Goldeneye uses 12 cameras to monitor 430 parking spaces and with digital signs at the entrance to the site, the system alerts a 500-strong workforce and visitors to where they can quickly find a parking space.

Traditional parking monitoring solutions use sensors for each individual parking space, which can be expensive to maintain and often the business case to justify a large investment in bay sensors does not exist. Automatic Number Plate Recognition (ANPR) systems are very effective; however they do not offer the parking facility owner any greater information than entry and exit from the car park and stay time.

Goldeneye offers a more cost-effective way to scale parking monitoring via the cloud, making it possible to choose your parking location, reserve and pay for a parking spot online while also allowing the user to continually monitor their car. Retailers could harvest valuable information on footfall from vehicles, dwell time at retail locations, car brand and more.

In addition, because Goldeneye is based on machine vision it can readily be extended to include new use cases, including occupancy monitoring per vehicle, vehicle identification, and identification of pedestrian flows.

Taking the system out of the car park, it could enhance wider smart city applications. Deep learning and machine vision could be harnessed to monitor traffic or to manage crowds on train platforms, for retail analytics, to monitor crowd safety and a range of other applications.

“We’re now at a point where deep learning can move out of the research fields, into the real world, and we’re excited to be pioneering this world first for cities of the future,” said Thomas Carmody, Head of Transport and Infrastructure at Cambridge Consultants. “What’s truly remarkable about Goldeneye is the fact that the system taught itself to identify and operate a car park. It does this without the need for any additional computing equipment. This is a further example of Cambridge Consultants disrupting markets with breakthrough technologies and there’s much more to come”.  

Goldeneye is the latest deep learning innovation from Cambridge Consultants. The company is working at the frontier of this vital, transformative technology, developing bespoke systems that leverage deep learning techniques to achieve unprecedented performance in a wide range of applications.