May 19, 2024

Automotive Industry – Innovation – Technology

Innovative design for smart systems from Cambridge Consultants and Analog Devices

Machine vision has brought an entirely new aspect to parking. It’s the most cost-effective method to monitor the occupancy of car parks and on-street parking spots without the expense of infrastructure. The revolutionary smart system was developed by the product development and design firm Cambridge Consultants and semiconductor design and manufacturing firm Analog Devices.

The system is a low-cost camera with an advanced algorithm based on a low-cost processing platform. It is able to determine the percentage of parking spaces that are used or vacant – with no inconvenience or cost of tearing up parking spaces and roads to set up individual sensors and communication for each parking space.

“Our unique smart system uses machine vision to establish whether each space is free or occupied – with no need for expensive infrastructure,” said Dipak Raval, who is a director of commercial services for Cambridge Consultants. “It’s an excellent illustration of how machine vision can offer a cost-effective method to monitor occupancy across large areas because the camera can see several bays.

“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.”

Finding a parking spot could take as long as 20 minutes, surveys of parking often report. The average driver spends thousands of hours throughout their entire life searching to find a space. Along with the financial costs of this time, it can also contribute to the pollution and congestion in the streets.

A nudge of machine vision could place the driver back in the driver’s seat. Drivers may be assigned parking spaces when they enter a parking lot, such as a parking garage, allowing them to go to the spot they have been allocated immediately. You can also ask for a particular space ahead of time if they intend to purchase something from a specific shop, or even a specific parking space outside of an establishment they must visit in a bustling town center. If the information from the occupancy sensors is paired with the number plate recognition, motorists could also receive an automated payment system and assistance in finding their vehicle.

The latest smart system is powered with Analog Devices’ award-winning Blackfin(r) Low Power Imaging Platform (BLIP), a Low-cost, embedded, low-power computer vision system that is designed to target an array of applications that use real-time sensing.

“The BLIP platform allows Analog Devices 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,” said Michael Murray, general manager of industrial IoT and sensing at Analog Devices.

“We’re delighted to be working in partnership with Cambridge Consultants on this project. The world-class expertise of the company in the field of complex algorithm development has helped us algorithmically implement BLIP to be used in an application which would provide an original solution that would eliminate the major cause of stress for drivers all over the world.”

The final acceptance of autonomous vehicles will be a collective and political one; as such, the people involved are required to communicate their decision-making process and the reasoning for the decisions. The assurance that is employed by other industries will be difficult to procure.

The complex driving environment will require the development of new sensors and communications channels, along with more sophisticated methods to interpret and capture the data.

  • The decision-making processes should take into account:
  • A fair division of responsibility between manufacturers, operators, and other stakeholders is based on precise technical requirements rather than abstract objectives.
  • The capability to modify and correct the decision-making process over time.
  • Human-machine interaction requires user-centric designs to be adopted.

Autonomous systems can be complex, and architectural techniques will be required to reduce costs and make security possible.

No matter what assurance goals are established in the future, the complexity of vehicles and their surroundings can make testing difficult. So:

  • Test strategies that are able to support huge and well-defined tests are required.
  • The evidence gathered from a broad array of assurance methods (not just dynamic testing) will have to be utilized.


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