According to statistics, about 1.25 million lives are lost in road traffic accidents every year in the world, which means that about 3,500 people die in traffic accidents every day in the world. Among all the traffic accidents, the ones caused by blind spots and driver behavior account for the highest proportion. With such background, SORAX, as a leading company in intelligent automotive electronics industry, has made deep integration of advanced automotive electronics technology with a new generation of artificial intelligence (AI) technology. With accumulated technical experience in image processing, pattern recognition, and deep learning, the company has developed new smart products equipped with face recognition, behavior analysis and status warning function, providing high-quality intelligent vehicle monitoring products and solutions which contribute to the safe driving and accidents reduction.

The face recognition technology is to collect dynamic facial images of the driver; then convert the biological features of the driver such as face type, eye spacing, single or double eyelid into data features and perform intelligent analysis. The technology identifies the driver by comparing the data to the registered identity image features. If an unregistered identity is recognized, the system will trigger an alert and activate the recording function, which will effectively prevent the vehicle from being stolen and be used for subsequent investigation and evidence collection.

Fatigue driving monitoring technology accurately locates multiple feature points of the drivers face through multi-layer neural network technology, and combines clustering and neural network algorithms to assess the state of the human eyes. It can detect if the driver is fatigue , regardless it’s in the day or night, and whether the driver wears glasses or sunglasses. Once the driver is detected to be fatigue driving, the system will immediately trigger a warning to wake up the driver and start recording at the same time to avoid serious accidents

Distracted driving monitoring technology, based on video image analysis technology, can accurately assess whether the driver has distracted driving behavior by positioning the drivers head posture and its deflection angle, etc.. An alarm would be promptly triggered to avoid accidents .

The cell phone use monitoring technology can accurately identify whether the driver is answering or making a phone call. Once it detects that the driver has spent more than 2-4 seconds on the phone when driving, it will promptly trigger an alarm to avoid accidents.

Smoking monitoring technology can accurately identify the drivers smoking behavior. When the driver is detected to smoke during driving, an alarm will be raised to the driver to prevent accidents.

The driverless monitoring technology can accurately detect whether there is a driver. Once it detects the change of drivers when the car is moving or the driver is leaving the driving seat, it will promptly alert the driver to mind his driving behavior.

The forward collision warning technology can intelligently and accurately analyze the distance and relative speed between the vehicle and the preceding vehicle, estimate the potential risk of rear-end collision, and send warnings to the driver to avoid accidents.

The preceding car starting reminder technology can intelligently detect the distance from the vehicle in front. Once the vehicle is detected to stay still while the vehicle ahead waiting for red lights or in a traffic jam has started, an alert will be sent to the driver .

The lane departure warning technology can precisely collect the lane information by processing and analyzing the video of driving. When the driver is detected to shift the lane without turning on the signal light, an alarm will be triggered immediately to prevent the possible traffic accidents caused by lane departure.

Through the AI algorithm, the speed sign recognition technology can accurately recognize the road speed limit and analyze whether the vehicle is over speed in real time. When it is detected that the vehicle exceeds the limited speed, an alarm will be triggered immediately to prevent traffic violations or accidents.

Pedestrian detection technology, which is a deep learning technology based on big data, can intelligently detect whether there are targets such as pedestrians and cyclists in front of the vehicle, meanwhile it could accurately analyze information such as the speed and distance between the vehicle and the target object. When a risk of collision is predicted, an alert will be triggered to avoid a collision.