Automatic Driver and Vehicle Safety Monitoring System

Background/Objectives: Accident is increasing rapidly and is mostly due to drunk driving and drowsiness of drivers. A novel approach is presented in this paper to monitor the physical condition of driver and alert system to reduce human errors by means of an embedded system. Methods: To find a particular person’s blood alcohol concentration in their bloodstream, breathalyzer which is also known as breath alcohol detector is used. IR sensor and biomedical sensors are used to detect the drowsiness by monitoring eyes pattern, EMG and EOG signals. These were the basic inspiration for creating the embedded system introduced here. The proposed system includes microcontrollers, alcohol sensor, biomedical sensor, IR sensor, camera modules, GPS, Wi-fi adapter, ZigBee module, solenoid valve and ignition switch circuitry. Findings: The proposed vehicle safety monitoring system will detect blood alcohol concentration (BAC) percentage from the particular person’s breath samples. The EOG, EMG and IR sensors are used to monitor driver condition. The warning alarm and ignition switch circuitry are enabled and disabled based on the input values of the monitoring system. Thus, the condition of the driver is continuously monitored and calibrated on a scale. When it exceeds a particular limit, the alarm unit is enabled. GPS and camera module are used to trace the vehicle and driver. The monitored values are serially transferred to the master controller and further upload the data to cloud space by means of Internet which can be accessed or streamed. This data is used to track the vehicle and detect who is driving the car at any instant of time. Conclusion/Improvements: Non-intrusive nature of this system helps to detect driver’s physical condition without making inconvenience to him. Real-time and online data transfer system of this system helps the respective authority to take immediate actions. This device can be very helpful for law enforcement department to solve vehicle theft, accident and hit-and-run cases.