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The application of edge computing in traffic to unmanned driving and law enforcement capture

1. Edge computing in traffic in driverless applications


When a car is driving on the road, various sensors will generate a huge amount of data, and if all these data need to be uploaded to the cloud for processing before returning to the vehicle, it will create serious safety hazards, and the edge AI computer with independent edge computing and cloud computing power shows its value.


For example, if a high-speed self-driving car suddenly has an obstacle in front of it and needs to slow down or stop immediately, if it still needs to upload data to the "cloud", wait for the cloud to calculate and then give the braking command to the car, and then the car responds, then an accident may have already happened.


Although network latency has improved dramatically with the gradual spread of 5G, relying entirely on the network and the cloud is still not a good option. If the car happens to be in an area where the network signal is down or disturbed, it would be terrible if the edge computing in traffic was completely disconnected and the car could not make decisions on its own.


This is why it is important to use edge AI computers to give cars the ability to think accordingly, so that they can react "subconsciously" without the need for cloud computing.


In addition, intelligent mobility is moving from single scenario driverlessness to convergent scenarios for services of edge computing in transportation, and V2X (vehicle wireless communication interconnection) scenarios can make intelligent driving safer, more efficient and more convenient.


More road smart devices are added to provide data for cars such as speed limits, bad weather warnings, merge alerts, intersection signal timing scheduling, etc. to achieve the goal of vehicle-road collaboration.


2. The application of edge computing in traffic in law enforcement capture


Through AI algorithms of intelligent transportation, integrated algorithms of human-vehicle non-recognition, track tracking, license plate recognition, face and feature recognition, etc., real-time monitoring of traffic violations on the road is carried out with the help of monitoring equipment.


The system intelligently determines the type of illegal behaviour, such as going against the traffic, pressing the line, running red lights, parking violations, etc., and automatically records the complete process of the illegal behaviour.


With edge AI computers, traffic monitoring capabilities and auditing efficiency are effectively improved, thus saving manpower costs.


There is no doubt that global enterprises are firmly adopting a more flexible, cost-effective and cloud-connected infrastructure as a key solution to simplify the digital transformation journey. concepts such as SD-WAN, SASE Platform, ZTNA and Multi-cloud are becoming the hottest topics in the industry. Enquiries are welcome.


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