What are the Challenges of Video Analytics in Transport Monitoring System?
With the increasing population and the number of vehicles, the challenges at roads are also increasing. They make it challenging to handle vehicular congestion and suspicious activity. The cases of accidents are also proliferating. It has become difficult for the road monitoring authority to keep track of everything.
Solutions
Government and road management authorities have started using Artificial Intelligence and video surveillance to reduce road incidents and make the road safer. The video surveillance systems not only track the moving objects but should interpret their patterns of behaviors. It determines the preconditions of mishappening and thus alerts the system to resist the mishappenings.
Predictive Analytical Process for Detecting Road Accidents.
AI-Based Detecting Road Accidents will Track and calculate the speed of every vehicle. Suppose vehicle speed moves very slow in a long time. In that case, it means an accident probably occurred. The camera can detect the accidents and indicate the accidents and the oversized vehicle on the road to people. Calculate box height and mark all large container trucks, trailers, and lorries in red and indicate the people about it.
Detect Road Accidents Dashboards
This Sample detects road accidents analytics dashboards, the organization will get the maximum average and maximum speed of the vehicle for different-different roads and the injury type for pedestrians and also see the speed vs. crashes for vehicle and road type.
This Sample detects road accidents analytics dashboards. The organization will get the number of vehicles and type of vehicle for every month and see the max count of vehicles for a particular vehicle.
According to the vehicle type, you can see the number of vehicles detected, a stationary vehicle's status vs. a moving vehicle, and the congestion of accidents for a particular speed.
End Customer Value
Here every tracking and vehicle detection will be in the system. The system is not getting the only single type of authorization; firstly, the system will determine the vehicle classification, parking status, oversized vehicle, and object detection. After that, the system will detect dangerous driving and Pedestrian/cyclist monitoring also.
Why XenonStack?
By clicking on the demo button, one can send a demo request; we gives the demo on the analytics in the transport monitoring system to detect vehicles on the roads by using a machine learning model. Organizations will get insights related to Detect road accidents. As for this for reference, the demo dashboards; from there, the results are generated from our machine learning model. Our ML model will provide you an accurate solution for computer vision.
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