Driver Attention Warning/Drowsiness Detection

DAWS case studies

Introduction


Driver attention warning is part of an ADAS system that monitors driver eye and head movements for signs of drowsiness or distraction.

 A possible danger if detected will caution the driver, possible dangers could include heuristics as well non heuristic behaviors, anything from blinking their eyes more frequently as an attempt to focus back on the road ahead, moving their head to refocus their eyes, or pulling over until the driver is fully awake again. 

The Driver Alert System market size was valued at USD 7.7 billion in 2022 and is anticipated to grow at a CAGR of 12% between 2023 and 2032.

How does DAWS monitoring work 


  • Driver eye monitoring 
  • Driver head movement monitoring.

Driver Eye Monitoring

Furthermore, driver eyesight cameras use infrared light to determine where a driver’s eyes are looking. In addition to how open they are and for how long. Some driver eyesight cameras will even monitor pupil size, indicating fatigue or drowsiness while driving to measure driver attention level.

Driver Head Movement Monitoring

Head movement driver attention warning systems monitor head movements and alert drivers who exhibit signs of drowsiness or distraction and those who do not appear to look in the direction of travel before changing lanes.

Use Cases we help

  • Data Procurement

Developing a mature global DAWS system requires a diverse set of imagery as well as video data to ascertain model functionality across diverse set of conditions (outdoor & well as in-cabin)  as well as ethnicities 

Here’s a set of examples of representative data exhibiting our data sourcing for Europe’s largest OEM.

Data Procurement
Data Procurement.
  • Data Annotation & Labeling

As explained above, accurate detection of the driver’s eye and head movements will warrant model accuracy and performance. Thus, our expert human-in-the-loop data labellers ensure the highest accuracy to enable you to develop high-performance hyperparameterized convolutional neural network models without any need for fitting.

Data Label – Red, Driver Eye Closed, Face roll

Moreover, these systems help the driver maintain control of the vehicle in slippery conditions. It can also apply the brakes to the vehicle’s wheels to help keep it on track and prevent it from skidding uncontrollably

Data Label – Green, eye open, Attentive

Additionally, they are highly beneficial in stop-and-go traffic situations or on highways, as advanced cruise control can automatically accelerate, slow down, and, at times, stop the vehicle, depending on the actions of other objects in the immediate area.

The Macgence Way

TAT

Lastly, compliant high-quality data is available at your disposal, which comes with customization benefits and can be quickly delivered.

QUALITY

Our dataset goes through rigorous 2-level quality checks before delivery

COMPLIANCE

Adherence to both the mandatory compliances of HIPAA & GDPR

ACCURACY

Provides gives ~90% accuracy across different annotation types and model datasets

NO. OF USE CASES SOLVED

Experience across a diverse range of use cases



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