Machine vision is bringing a new dimension to parking – a cost-effective way of monitoring car park occupancy and on-street parking bays, without expensive infrastructure, product development engineering and technology consulting service provider Cambridge Consultants commercial director Dipak Raval explains.
Raval notes that the innovative system has been created by Cambridge Consultants and semiconductor design and manufacturing company Analog Devices.
The system combines a low-cost camera with a sophisticated algorithm running on a low-cost processing platform and 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, he highlights.
“Our unique system uses machine vision to establish whether each space is free or occupied – with no need for expensive infrastructure, it is an good 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.” says Raval.
He points out that, its deep expertise in algorithm development has enabled the company 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.
The search for parking space can often take up to 20 minutes, parking surveys regularly report – with the average motorist said to waste thousands of hours over their lifetime driving around trying to find a vacant spot, Raval says. All this results in wasted time and adds to pollution and congestion on the roads.
Raval claims that, machine vision, however, could put the motorist back in the driving seat. Drivers could be assigned a parking space as they enter a car park, for example. They then go straight to their allotted spot. Specific bays can be requested in advance if motorists plan to shop at a particular store, or a specific parking bay outside a building they need to visit. 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.
The new smart system is enabled by Analog Devices’ award-winning Blackfin Low Power Imaging Platform (BLIP) – a low-cost, low-power embedded computer vision platform targeting a vast array of real-time sensing applications.
Analogue Devices GM Michael Murray reports that, the BLIP platform allows the company to make significant contributions in emerging Internet of Things (IoT) spaces, such as smart buildings and cities, where this is a radical shift from passive to real-time intelligent sensing nodes.
“We are excited to collaborate with Cambridge Consultants on this project. “The company’s expertise in complex algorithm development allowed us to algorithmically enable BLIP for an application space that would create a unique solution to relieve a major source of frustration for drivers everywhere,” he concludes.