Artificial Intelligence in Vehicles
According to statistics, around 1.25 million lives are lost in road auto collisions yearly around the world, which means that about 3,500 people die in auto collisions every day around the world. Among all the auto collisions, the ones caused by blind spots and driver behavior count towards the highest incidents. As a leading company in the intelligent automotive electronics industry, we have contributed to the advancement of 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 safer driving and accident reduction.
Pedestrian Identification Technology
Pedestrian identification technology, which is a big data-based deep learning technology that can intelligently detect whether there are targets in front of the vehicle, such as pedestrians and cyclists, while accurately analyzing information such as the speed and distance between the vehicle and the target object. To avoid a collision, an alert will be triggered when a collision risk is predicted.
Motion Sensor Technology
As an AI technology based on a vision algorithm, the motion sensor technology can detect moving objects with a certain size and a relative speed of more than 5 km/h, such as pedestrians, cyclists, or other cars, etc. It will warn the driver and inform the locations of the moving objects so the driver can respond in a timely manner. Thus the risk of a traffic accident can be minimized.
Face Indentification Technology
Face Identification technology is used 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 an intelligent analysis. The technology identifies the driver by comparing the data to the features of a registered identity image. If an unregistered identity is identified, the system will raise an alarm and activate the recording function, that would effectively prevent the vehicle from being stolen and can be used for preliminary investigation and collection of evidence.
Exhausted Driving Monitoring Technology
Via multi-layer neural network technology, fatigue driving monitoring technology reliably locates multiple driver face feature points and integrates clustering and neural network algorithms to determine the state of the human face. It can detect whether the driver is sleepy, regardless of whether it is night or day, or even if the driver is wearing glasses or sunglasses. The system would automatically activate a warning to wake up the driver and start recording at the same time to prevent serious accidents if the driver is found to be driving exhausted.
Inattentive Driving Monitoring Technology
Inattentive driving detection technology is based on video image recognition technology that can reliably determine if the driver has distracted driving actions by positioning the driver's head posture and angle of deflection, etc. To prevent incidents, an alarm will be activated immediately.
Mobile Phone Use Monitoring Technology
Mobile phone usage monitoring technology will reliably determine whether the driver is using or making a phone call. When it is detected that the driver has spent more than 2-4 seconds on the phone while driving, a warning will be activated automatically to prevent accidents.