New AI software can sense when people drive and text

It is necessary to be cautious when you are driving as you never know what would be coming your way. Now, the engineering researchers from the University of Waterloo have developed computer algorithms that can precisely detect when driver texts or gets engaged in any diverting activities. Artificial intelligence and cameras are used by the system to identify hand movements that distract from normal driving behavior and classify or grade them in terms of likely safety threats.

Professor of Electrical & Computer Engineering at Waterloo, Fakhri Karray, said that data can be used to enhance road safety by notifying or cautioning drivers when they are dangerously distracted. And as sophisticated self-driving features are progressively incorporated in conventional cars, indications of serious driver diversion can be used to prompt protective measures.

Karray, Director of the Centre for Pattern Analysis and Machine Intelligence (CPAMI), said, “The car can, in fact, take over driving if there was a forthcoming threat, even for a short while, so as to circumvent crashes.” Algorithms at the technology’s heart were taught using machine-learning methods to identify actions such as talking, texting on a cellphone or getting into the backseat to get something. The significance of the action is evaluated on the basis of time and other factors.

That work put up on the prior extensive study at CPAMI on the identification of indications, including blinking frequently, that drivers are in chance of falling asleep while driving. Face and Head positioning are also significant signs of diversion. Now, the ongoing study at the center is seeking to merge the processing, grading, and detection of numerous different sorts of driver diversion in one system.

Karray said, “It has an enormous footprint on society,” mentioning estimates that diverted drivers are to blame for up to 75% of all traffic accidents across the globe. Another research project at CPAMI is investigating the employment of sensors to determine physiological signs such as rate of eye-blinking, heart-rate variability, and pupil size to assist in verifying whether a driver is paying satisfactory concentration on the road.

This is not the foremost technological solution to unfocused driving. There are other applications that lock the user’s phone when they are driving, applications that enable individuals to inform diverted drivers they identify on the road, a tool, “textalyzer,” that allows police to ensure if you have been texting, and iOS 11 update of Apple incorporates a “Do Not Disturb While Driving” approach. Earlier this year, Apple had faced a class-action proceeding for not incorporating patented technology that could fight diverted driving on their iPhones.


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