Shebin Jose Jacob has published a new project to the Edge Impulse website providing details on how an Arduino Nicla Vision board has been used to help detect driver drowsiness with FOMO. Once actve if the system detects a driver’s eyes are closed for two seconds or longer, and alert will trigger to wake the driver up and remind them to stay focused and concentrate on the road ahead. Alerts can be generated in the form of a visual or auditory signal, such as a flashing light or a loud beep depending on your preference.
As well as detecting drowsy driving, the project can also be used to monitor other road safety metrics, such as distracted driving or impairment due to drugs or alcohol. “By alerting drivers to these behaviors and reminding them to stay focused and alert, we can help to reduce the risk of accidents and keep our roads safer for everyone” explains Shebin Jose Jacob .
Detect driver drowsiness
“Driver drowsiness is a major contributing factor to motor vehicle accidents and can have serious consequences, including injury or death. There are several reasons why driver drowsiness can lead to accidents. When a person is tired, their reaction time slows down, their decision-making abilities are impaired, and they may have difficulty maintaining their focus on the road. As a result, they may miss important visual cues, fail to notice hazards or make poor decisions while driving.”
“In addition to these physical effects, drowsy driving is also a cognitive impairment, meaning it affects a person’s ability to think and make good decisions. When a driver is tired, their judgment and awareness are impaired, which can lead to risky or dangerous behavior behind the wheel. The risk of drowsy driving is higher for certain groups of people, including commercial truck drivers, shift workers, and those with undiagnosed or untreated sleep disorders. However, anyone can be at risk for drowsy driving if they do not get enough sleep or if they are driving for long periods of time without taking breaks.”
“Our solution combines the power of Computer Vision and Artificial Intelligence (AI) to monitor the driver’s eyes and detect when they are closed for two seconds in a row. To ensure the accuracy and reliability of our system, we have trained and deployed an AI algorithm (model) on to an Arduino Nicla Vision. These algorithms are trained to recognize patterns and trends in the data collected by the camera and to identify when the driver’s eyes are closed for an extended period of time.”
Source : AB : Edge Impulse
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