Vision system developed to monitor car park occupancy

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Cambridge Consultants, a UK-based product design and development firm, and Analog Devices, an American semiconductor design and manufacturing company, have developed a low-cost camera that monitors car park occupancy and on-street parking bays, without expensive infrastructure.

The system combines the camera with a sophisticated algorithm running on a low-cost processing platform. It is able to calculate which parking spaces are occupied or empty – without the disruption or expense of digging up roads and car parks to install individual sensors and communications for each parking bay.

Dipak Raval, a commercial director at Cambridge Consultants, commented: ‘It’s an excellent example of how machine vision can provide a cost-effective way of monitoring occupancy over a wide area, since the camera is able to see multiple bays.’

There are various applications that this system enables. Drivers could be assigned a parking space as they enter a car park meaning they could go straight to their allotted spot. Or they could request a specific space in advance if they plan to shop at a particular shop – or a specific parking bay outside a building they need to visit in a busy town centre. If the data from the occupancy sensor is combined with number plate recognition, drivers could also be offered automated payment and help with locating their parked car.

‘Our deep expertise in algorithm development has enabled us to ensure the technology works in a variety of lighting conditions and can cope with different sizes of cars, trucks and motorcycles, without giving misleading results if pedestrians are standing in a parking space, for example, or shopping trolleys are left behind,' added Raval.

The new smart system is enabled by Analog Devices’ Blackfin Low Power Imaging Platform (BLIP), a low-cost, low-power embedded computer vision platform targeting a vast array of real-time sensing applications.

Further Information

http://www.cambridgeconsultants.com/

www.analog.com

 

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