The system is aimed at detecting drowsiness in two-wheeler vehicle drivers or drivers of vehicles that do not have the luxury of installing a video front faced footage of their activities. Hence the avoidance of facial rec-ognition patterns. This meant that we had to explore other parameters in the driver that indicate signs of drowsiness, thus being able to alert the driver. 500 participants of maximum age 45 were monitored under the condition of being awake and about to fall asleep. We measured the vital body signs such as pulse rate, temperature, blood pressure and respiratory rate. The comparison of the vital changes in each patient was plotted and the changes over time were noted. Based on this a prediction system was formed to check for the changes and allow priority of the signals. As to deal with a non-ideal environment, we constructed a checklist format procedure to notice changes. Appropriate hardware is used to collect vital parameters from the subject in real-time and process the data to check for any signs of drowsiness and alert the user accordingly.
Volume 11 | 03-Special Issue
Pages: 1347-1356