Driver alert project pdf

This is because when the driver is not able to control his vehicle at very high speed on the road. This project can generate a model which can prevent such accidents. Temperature sensor and smoke sensor are used for further safety system in the vehicle.

Keywords: Eye blink sensor, Temperature sensor, Smoke sensor, relays, microcontrollers 1. In addition, long time The primary purpose of the Drowsy Driver Detector is to driving would result in perspiration on the sensors, develop a system that can reduce the number of accidents diminishing their ability to monitor accurately. The second from sleep driving of vehicle.

With our two monitoring technique is well suited for real world driving conditions steps, we can provide a more accurate detection. For the since it can be non-intrusive by using optical sensors of detecting stage, the eye blink sensor always monitor the eye video cameras to detect changes. It continuously monitor eye blink. If the monitoring is over, the collected data will be transmitted to a 2. If the warning feedback system is triggered, the Fixing the sensor in front of driver seat so that the sensor microcontroller makes a decision which alert needs to be monitor the eye movement of the driver periodically.

If the activated. The second application of this paper is to detect eye lid of driver is not showing any change for a period of the alcohol content or any leakage of gas from the vehicle, time, the caution will be given to the driver.

This sensor once it deduct such sensation the LED light glows indicating should be fixed in such a way that it shall sense the eye emergency and this project also deals with temperature movement when the driver bends or sets erect.

For the alert systems, we have a 2. The project code is developed in C language Thermistors are thermal sensitive resistors whose prime and then converted to hex code which is readable to the function is to exhibit a large, predictable and precise change microcontroller. Negative Temperature 2. Literature Survey Coefficient NTC thermistors exhibit a decrease in electrical resistance when subjected to an increase in body 2.

In case of any drowsiness of drivers. These techniques can be generally fire inside the vehicle the sensor will deduct it initially and divided into the following categories: sensing of safeguard the passengers from worst case. This technique is implemented in two ways: Measuring changes in physiological signals, such as brain Once when the temperature increases inside the vehicle the waves and eye blinking; and measuring physical changes sensor sense it and stops the engine from further running.

The first method, the most accurate, is not realistic, since sensing electrodes would have Volume 3 Issue 4, April Paper ID: www. So the output is given to The blinking of eye is necessary in this project, since it is microcontroller. This circuit is mainly used to for counting used to drive the device and to operate events.

Figure 4 In such case the sensor gives caution to the driver indicating that there is a leakage of gas in the vehicle glowing Figure 2 emergency light. Block Diagram Figure 3 2.

One important point is both IR transmitter and receiver should be placed parallel to each other. The signal is given to IR transmitter whenever the signal is high, the IR sensor is conducting it passes the 4.

Methodology and Implement IR rays to the receiver. The IR receiver is connected with comparator. The comparator is connected with operational Implementing an automated system to vehicles that provides amplifier. In the comparator circuit the reference voltage is high security to driver and the passengers, by designing an given to inverting input terminal of the circuit. The Non- eye blink sensor which continuously monitor number of inverting input terminal is connected to IR receiver.

When times the eye blinks, once when the eye blinks count there is an interruption in the IR rays between the IR decreases that means the driver is sleepy , buzzer indication transmitter and receiver, the IR receiver becomes not will be given and that wakes driver from sleep. This paper conducting. So the comparator non inverting input terminal involves measuring the eye blinks using IR sensor. More than half of all road traffic deaths are among vulnerable road users like motorist, cyclist.

The important factor in driver monitoring system is the accuracy of the face detection. This paper deals with the discussion of several methods which have been proposed for detecting driver behavior, preventing the accident and detecting the accident in case if it occurs and alerting the emergency services.

It equips the vehicle with the recent technology which can detect accidents and alert the emergency services such as friends and hospitals. With IoT automatic response and push notifications can be sent. In a fog environment, we have to utilise a large sum total of fog nodes. The computation gets distributed and the entire system or environment becomes less energy efficient.

We can place a set of fog servers in such a way that they give maximum service to all localised requirements however, this is a problem. This can result in breach in security as spiteful and malicious users can make use of a hoax IP address to retrieve information stored on a specific fog and this includes massive maintenance cost.

In [2] the authors proposed a system that uses IoT to detect the accident and send alert message to emergency services however this is not a quick method and causes delay in saving the life. This system uses only MEMS sensor to detect the accident and hence the accuracy of the information collected is reduced.

This system makes use of cloud computing so in case of any network issues because of any mishap there might be a downtime or difficulty in connecting to the cloud. No precautionary measures have been included in this system to prevent the accident. Cloud computing does not work well if the network connection is slow or poor.

This is a detection method which helps detect an accident in real time. It uses a communication technique called vehicle to vehicle. It makes use of random forest classifier algorithm which is highly complex as it requires more computational resources and occupies a lot of memory. The algorithm is more time consuming when it must be trained. A lot of trees are first generated and then based on the maximum votes, a decision is made. The predictions are lower which may create challenges for various applications.

It will only send the estimated location which is not exact or appropriate. In [4] they have proposed an accident detection and prevention System to minimise the hazards caused due to traffic using Infrared Sensors. These sensors require a line of sight which is practically not possible as there can be many obstructions in the line of sight of the driver.

It readily gets cut off by familiar objects and has a definite limited range. In this sensor, the data rate can be sluggish or slow. In [5] they had proposed a system for accident detection which monitored traffic in real time. It was vision based. It made use of Gaussian mixture model. The chief limitation of GMM algorithm is that it failed to work for problems of his dimensionality. To avoid this, the user had to fix the sum total of models which the algorithm can fit in the training dataset.

The user will have no clue about the number of models must be used. The user will also have to experiment with different models to find the exact number of models that will work for that classification problem. In [6] the authors have proposed a system called intelligent traffic accident detection system. This system follows the principle of mobile edge computing to detect accidents using smart phones. The smartphone utilizes existing datasets and is prone to errors.

This edge computing technology has limited redundancy or sometimes no redundancy. The outage time is much longer which in turn reduces the performance and efficiency of the system. The data or information can be easily corrupted. Figure 1 Proposed System Accident is detected by sensors and microprocessors the location will be sent to Wi-Fi module.

The notification is sent to the hospital, police station and emergency contacts from the Wi-Fi module. Once the accident impact is recorded, the device then finds the GPS coordinates of the vehicle that has met with an accident. The Wi-Fi module comes with an inbuilt IP address which is used to connect to the application in which we will be getting the alert message. In case if the accident is minor and the passengers are safe then the driver can press the button, which will send another message to emergency personnel stating that they are safe and it was only a minor accident.

Figure 2 Flow chart for working of the Proposed System 3. Voila Jones Algorithm This algorithm involves two stages that is training and detection. Adaboost stands for adaptive boosting in which the algorithm learns from the images we provide as input and it will determine the false positives and true negatives of the data hence this provides a highly accurate model. The detection window is where the detection takes place. A maximum and minimum window size is chosen.