Drive Alert (Intel - IOT)

Detecting Drowsy Driving which can lead to fatality.Improving drivers efficiency using the captured data.

Automobiles Sector, Airlines, Heavy Vehicles Industry Anyone and everyone owning a four wheeler vehicle in current version.Truck/Cab Fleet Owners who would like to monitor their drivers driving habits and as well asleep the roads safe.

We capture the face of the vehicle driver and do image processing using openCV to identify the closure of eyelids. If the eyelids are closed for more than a while a buzzer is triggered which alerts and wakes the driver up.We capture the drivers driving behavior by placing touch sensors/ button below the pedals of clutch/gear/accelerator and the steering wheels. We log this data in the cloud and then will do analytics offline.

Sending sensor data to server whenever connectivity is available. The analysed data will be pulled to a mobile app in next phase of implementation.

We use touch sensor to determine the drivers grip on the steering wheel.The buttons below the pedals to track pedal usage habit.Web cam to capture video feed.

We use the Intel XDK to push and run nodejs code to the Intel Edison board.

Sensors : Touch/Pressure/Button from the groove starter kit.

Intel Edison Board

Sensors ::

Firstly, Intel XDK should be installed. Sigup to use XDK and make sure the dashboard is ready.

Next you will see templates , select the touch notifier to check for steering alert and use the button in the same way for pressure sensing.

and push the code into edison board.

Image Processing :::

Next install open CV on the edison board. There are online tutorials for that (refer any) .

Now , for image detection use the algorithms mentioned in the open CV documentation.

AlertDrive will keep you awake even if you want to sleep while driving.As a result of stress and fatigue, the vehicle driver can experience micro sleep. Micro sleep is the phenomenon of falling asleep for a few seconds.This is very common for heavy vehicle drivers who operate under long working hours or shift workers.We track the drivers drowsiness based on eyelid closure and alert him when he starts to get into microsleep.

We also track all his interactions with the vehicle's component viz. steering wheel, accelerometer and brakes. Using this data we give them feedback on their driving pattern to improve their overall efficiency of driving.