Main Components That Are Analysed To Calculate Driver Fatigue

The digital landscape has been evolving at a constant and unbroken space, and one of the major reasons for this technological innovation in today’s day-and-age is the widespread adoption of the Internet of Things services in multiple industries. One industry in particular that is currently utilising this technology to the fullest is the automotive industry, that has embraced these IoT solutions to help augment themselves in more ways than one. Its’s pretty obvious that automotive IoT technology will transform the industry in more ways than one, and one such development that needs to be discussed is the enablement of driver fatigue detection through a smart integration of these IoT services to track relevant data. This will help – among other things – reduce the number of accidents caused by human error, and provide drivers with a better perspective about their condition and whether they’re fit to drive in the first place.

Innovative technology such as HARMAN Connected Services helps immensely when it comes to improving the functionality of this technology to help analyse the various elements involved in calculating driver fatigue. These parameters are explained in detail below:

1.       Eye-blink rate: One of the biggest indicators that reveal whether a person is tired or not is the rate at which said person blinks their eyes every 30 seconds. Through the smart integration of connected car services, the system can gauge whether a person is tired or not, and inform them promptly if it’s analysis forms a conclusion that the driver doesn’t have enough energy to stay awake while driving.

2.       Rate of yawning: When it comes to gauging whether a particular person is tired or not, a dead giveaway is the rate at which the driver yawns every 120 seconds (in the case of HARMAN Connected Services). The neural network set up in the vehicle that’s fuelled through the application of IoT solutions can track this data, which is taken into factor while the AI makes a final judgement as to whether the driver is rested enough to drive in the first place.

3.       Tracking PERCLOS (percentage of eyelid closure): People who are tired have a hard time keeping their eyes open, which is extremely dangerous when this person is at the helm of a moving vehicle. The inability to stay aware about your surrounding can prove to be extremely costly in this particular situation. To prevent this, connected car technology can be used extensively to prevent such a detrimental situation, and a proven way to do so is by tracking PERCLOS, and calculating how many times is falls below 50% in a 30-second interval.

Through a combination of these parameters that’s integrated through the efficient utilisation of connected car services, one can facilitate the technology of driver fatigue detection and help reduce the volume of roadside accidents caused largely by human error.

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Created on Nov 8th 2017 00:34. Viewed 261 times.

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