The roadside parking management system is a parking and operation management system based on Internet of Things, cloud computing services and intelligent sensor technology. Roadside equipment such as curb machine, parking Meter and video pile is an important part of the system. By installing Benewake LiDAR, real-time detection of vehicles can be realized, and through the change of distance measurement value, the vehicle can be monitored if it has entered or left the parking space, triggering the camera to take pictures of the license plate, and then timing and cost settlement. Through LiDAR measurement, the power consumption of the whole system can be greatly reduced, the frequency of camera wake-up can be reduced and optimized, and the computing resources of background algorithm processing can be reduced. With the cooperation of LiDAR and camera and algorithm of the whole system, the detection accuracy rate can be as high as 99%, which can greatly improve the fee deduction rate and reduce the operation and maintenance cost.


The system monitors occupancy status for all parking spaces, and enables remote data query, e-mapped parking space monitoring, parameter configuration, and rate adjustment. Through data interfaces, it provides fundamental data to large-scale driving/parking promotion systems, optimizes operation inside parking lots, thus reduces operating costs. 


Solution Advantages

1.In ultra-low power consumption mode, the standby power consumption is 1.5mW, and the average power consumption is only 1.72mW. It can work for 3.3 years on a 10,000mAh battery, without the need for AC power or frequent battery replacement, greatly reducing the overall power consumption of roadside equipment and maintenance costs.

2.The detection range can reach up to 3m, and the range is stable. The small FoV can also effectively avoid the interference of complex objects around the vehicle.

3.Customized parking algorithms enable accurate vehicle detection even in mild.

Headquarters:3rd Floor, Haiguo Jiaye Sci-Tech Park, Haidian District, Beijing, China
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