Neural Labs
Neural Orchestrator is a solution for traffic analysis, independent of the camera model and brand. Through Deep Learning techniques, it analyzes the scene by recognizing objects, individualizes and classifies them and then tracks each of them.
The system can evaluate the real-time behavior of objects by detecting traffic events and violations, being able to analyze up to four lanes per camera. It can also process multiple Onvif cameras and leverages the processing power of GPU (Graphics Processing Unit) for object detection using Deep Learning.
Ideal for applications where it is necessary to analyze a scene, perform counts, perform sanctions, DAI, or video analytics on vehicles or people with Onvif cameras, detecting motorcycles, cars, trucks, buses, people, bicycles and even electric skateboards.
Using a rules engine, Orchestrator can recognize situations such as people counts, vehicles (even by category), improper crossing of people, traffic jam detection, vehicles in reverse, among many other programmables. It can also detect brand, color, speed, type of vehicle, among others.
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