Design And Implementation Of A Microcontroller Based Driver Impairment Monitoring System

Design And Implementation Of A Microcontroller Based Driver Impairment Monitoring System

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ABSTRACT

Facial expressions including eye and head movement can indicate driver weariness and drunkenness. By observing features including head movement, blinking eyes, and face angle, a driver impairment monitoring system has been developed, built, and tested. In this system, the tilt sensor, IR sensor, camera, GSM module, and microcontroller were employed along with the alcohol sensor (MQ3). The buzzer alerted the driver and an SMS was sent to the car owners when the driver's closed eyes, head tilt for tiredness, or consumption of alcohol were identified for a predetermined amount of time. Ten individuals were used to measure the face angle deviations, and it was discovered that the average accuracy was very high.

keyword: driver, sensor, alcohol, vehicle, and preventive.

1.INTRODUCTION

Driver impairment is a serious issue that can lead to accidents and fatalities on the road. Impairments such as drowsiness, alcohol or drug use, and distraction can significantly impact a driver's ability to operate a vehicle safely. To address this issue, a microcontroller-based driver impairment monitoring system can be developed to continuously monitor a driver's physiological and behavioral parameters and p[4]eye blink sensors are a critical technology in accident prevention, serving as a proactive safety measure to detect drowsiness or distraction in operators or drivers. They provide real-time monitoring of blink patterns, offering early warning systems that can trigger alarms or notifications. By improving safety outcomes, eye blink sensors help reduce accidents vehicle dynamics. The system processes the data

collected from these sensors in real-time to determine the driver's level of impairment. If impairment is detected, the system generates alerts, such as visual or auditory cues, to prompt the driver to take corrective action or pull over to ensure safe

The implementation of the system may involve the integration of multiple sensors and modules, such as an electrocardiogram (ECG) sensor to measure heart rate, an eye-tracking sensor to monitor eye movement, a camera to capture facial expressions, an accelerometer to measure vehicle dynamics, and a microcontroller to process and analyze the data. The microcontroller will run algorithms that use the sensor data to detect impairment and generate appropriate alerts The driver impairment monitoring system can be used in various applications, such as in personal vehicles, commercial fleets, and public transportation, to improve road safety and prevent accidents caused by impaired driving. It can also be integrated with other vehicle safety systems, such as collision avoidance and lane departure warning systems, to provide a comprehensive safety solution. Overall, the design and implementation of a microcontroller-based driver impairment monitoring system is a critical step towards addressing the issue of impaired driving and improving road safety. By continuously monitoring the driver's physiological and behavioral parameters, the system can detect impairments in real-time and provide timely alerts to prevent accidents and save lives.

1. RELATED WORK

   An accident prevention system using eye blink sensor technology has the potential to enhance safety by detecting fatigue, drowsiness, and distraction in individuals, providing real-time feedback and alerts to prevent accidents before they occur [1] . [2][3]An adaptive real-time eye blink detection system is a promising technology that has the potential to improve safety, usability, and health outcomes. By leveraging advanced learning techniques this system can accurately and efficiently detect eye blink in real time even under varying environmental conditions and different individuals.

   [4]eye blink sensors are a critical technology in accident prevention, serving as a proactive safety measure to detect drowsiness or distraction in operators or drivers. They provide real-time monitoring of blink patterns, offering early warning systems that can trigger alarms or notifications. By improving safety outcomes, eye blink sensors help reduce accidents caused by human error, enhance overall safety in critical environments, and contribute to preventing injuries or fatalities. Eye blink sensors are a valuable tool in promoting operator alertness and preventing accidents in diverse industries and applications where operator vigilance is essential.[5] Eye blink sensors in vehicle accident prevention systems has shown promising results. These sensors can accurately detect driver drowsiness and distraction by monitoring their eye blink patterns in real-time. Implementing eye blink sensors as part of a comprehensive vehicle safety system can significantly reduce the risk of accidents caused by driver fatigue or distraction, improving overall road safety. everywhere.[6] eye blink sensors for accident prevention in vehicles

   .Real-time monitoring of driver drowsiness and distraction through eye blink patterns. [7][8] the implementation of eye blink and alcohol sensors in accident prevention systems has the potential to significantly reduce the number of accidents caused by drowsy or drunk driving. These technologies can be integrated into existing vehicle safety systems or used as standalone devices to enhance safety on the roads. Further research and development are necessary to improve the accuracy and reliability of these sensors to ensure their effectiveness in preventing accidents[9] [10]eye blink and alcohol sensors in accident prevention systems can potentially save many lives on the road. The eye blink sensor can detect drowsiness and fatigue in drivers, alerting them to take a break or rest before continuing their journey. The alcohol sensor, on the other hand, can detect if a driver is over the legal limit and prevent them from operating their vehicle.

2. BLOCK DIAGRAM AND WORKING

   Driver impairment is a critical factor in road accidents, and a microcontroller-based monitoring system can play a crucial role in detecting and alerting drivers about their impaired state. The system incorporates various sensors, such as eye-tracking, heart rate, and breathalyzer sensors, to continuously monitor the driver's physical and physiological state in real-time.

   The microcontroller processes the sensor data using predefined algorithms and decision- making logic to analyze the driver's impairment level and generate an output display for the driver.The output display can be a graphical user interface (GUI) or an LED display, providing real-time feedback to the driver, enabling them to take appropriate actions to ensure safer driving practices.The implementation of a microcontroller-based driver impairment monitoring system has the potential to significantly reduce the risk of accidents caused by impaired driving, making it a valuable addition to modern vehicle safety systems.

   Fig 3.Block Diagram

   1. PIC MICRO CONTROLLER

      PIC microcontroller is a compact integrated circuit that serves as the brain of an embedded system, executing instructions and controlling various tasks.It typically consists of a CPU for processing instructions and memory for storing program instructions and data, making it a versatile and powerful solution for embedded applications

      Fig 3.1.Pic Microcontroller

   2. NODE MCU

      Node MCU is an open source firmware for which open source prototyping board designs are available. The name "Node MCU" combines "node" and "MCU" (micro-controller unit). Strictly speaking, the term "Node MCU" refers to the firmware rather than the associated development kits devices

      The NodeMCU (Node MicroController Unit) is an open source software and hardware development environment that is built around a very inexpensive System-on-a-Chip (SoC) called the ESP8266.

      Fig 3.2 Node MCU

   3. GSM MODULE

      A GSM modem or GSM module is a device that uses GSM mobile telephone technology to provide a wireless data link to a network. GSM modems are used in mobile telephones and other equipment that communicates with mobile telephone networks. They use SIMs to identify their device to the network

      Fig 3.3GSM Module

   4. TILT SENSOR

      Tilt Sensors are also known as inclinometers. They are a type of position sensor used to measure angles or the slope of an object. Inclinometers are one of the most common types of position sensors available and are used throughout many industries.

      Fig 3.4 Tilt sensor

   5. ALCOHOL SENSOR

      The alcohol sensor is technically referred to as a MQ3 sensor which detects ethanol in the air. When a drunk person breathes near the alcohol sensor it detects the ethanol in his breathe and provides an output based on alcohol concentration. If there is more alcohol concentration more LED's would lit.

      Fig 3.5 Alcohol Sensor

   6. EYE BLINK SENSOR

The eye blinking is a natural protection system which defends the eye from environmental exposure. The spontaneous eye blink is considered to be a suitable indicator for fatigue diagnostics during many, different tasks of human being activity. The detection function is used to detect the spontaneous eye blink action. Eye blink Sensor is a relatively simple sensor used to detect eye blinks.

Fig 3.6 Eye Blink Sensor

4.CONCLUSIONS

A driver impairment monitoring system can greatly improve safety on the road by alerting drivers when they are exhibiting signs of impairment. This can prevent accidents and save lives.

Reduced liability: By implementing a driver impairment monitoring system, companies and organizations can reduce their liability in the event of an accident caused by an impaired driver. This can save money in legal fees and settlements, as well as protect their reputation.

5.REFERENCES

1. mai K Galab and H M Abduldhar Adaptive real time eye blink sensor detection system-GSM technology 2014

2. Deepa k and Ankit kumar Accident preventing by eye blink and alcohol sensor – GPS are used in this system 2015

3. Hari prakash and manikandan vehicle accident prevention using eye blink sensor- one sensor is used 2016

4 Nisi K A smart vehicle for accident prevention -eye blink sensor is used 2016 5.Nishanth P R and Ancy john Real time embedded system for accident prevention – embadded system is used 2017

1. Rajavardhan Rishi and V Bansone sifya yede Automatic messaging system for vehicle tracking and accident detection GPS technology 2020

2. M P Harinee and R Sendhil smart detection and prevention system for drowsiness-GSM module technology 2021

3. Ugochi A Okengwu Design and implementation of in vehicle alcohol detection and speed control system -alcohol sensor used 2022

4. priti navanath kadam Accident prevention using eye blink sensor -NODE MCU used 2019

5. suhas katkar Accident prevention system- GPS technology 2019