Authors: Akshara M. C., Harshitha T. S., Nithya Deepak, Priyanka B, Prof. Sharath H. A.
DOI Link: https://doi.org/10.22214/ijraset.2022.45810
Certificate: View Certificate
Generally, road accidents caused by a fatigue driver is a very serious problem causing in thousands of road accidents each year. According to the National Highway Traffic Safety Administration, every year about 1,00,000 police reported crashes involve drowsy driving. Drowsiness is one of the main causes of accidents alongside with other cases such as drunk driving, distractions, and so on. A way to overcome this issue would be with the use of sensors. They can detect, alert and can potentially save a person’s life. For drowsiness detection, there are certain bio-indicators that can detect the driver’s face for any signs of drowsiness and can alert them before anything harmful could happen. The buzzer will be activated if the driver’s eye-blink and the health parameters are found abnormal.
Countless of mishaps regarding road accidents are caused by fatigue, tiredness, and so on. About 50% of the accidents are road accidents. The road accidents can be due to inadequate way of driving, and these could arise if the driver is an alcoholic or drowsy. The drowsiness and the alcoholic condition of the driver has become a major cause for the road accidents. This also has led to major challenges in developing a system for the prevention of this issue. IOT-based innovation tends to be much more practical to work with since it runs on a real time system, and it can transfer all the data or information without any human interaction.
Fatigue is a safety problem that has not yet been deeply tackled by any country in the world mainly because of its nature. Drowsiness, in general, is very difficult to measure or observe unlike alcohol and drugs, which have clear key indicators and tests that are available easily. An IOT –based system is designed to avoid countless mishaps due to drowsy drivers’ behavioural and psychological changes by focusing on driver’s eye moments and health issues like heart attack, dizziness, and other health issues.
We’ll be focusing on the drowsiness aspect of it followed by checking other health parameters like pulse and alcohol detection. To obtain a solution to drowsy driving is extremely new and is set in motion. But the steps to prevent it with the help of IOT sensors and methodologies is what this paper discusses on IOT-based innovation will offer propelled dimensions of administrations and for all intents and purposes change the way individuals lead their day by day lives. Fatigue is a safety problem that has not yet been deeply tackled by any country in the world mainly because of its nature. Drowsiness, in general, is very difficult to measure or observe unlike alcohol and drugs, which have clear key indicators and tests that are available easily. An IOT –based system is designed to avoid countless mishaps due to drowsy drivers’ behavioural and psychological changes by focusing on driver’s eye moments and health issues like heart attack, dizziness, and other health issues. The main aim of this project is to develop a certain system which is efficient to predict the drowsiness and the health parameters of the driver using sensors to alert the driver and reduce the increasing number of accidents. The following are the problems we are going to tackle in our entire project:
The basic purpose of this system is to track the driver’s facial condition and eye movements if the driver is feeling drowsy, then the system will trigger a warning message. When the drowsiness is detected, the driver is alerted by a buzzer. Measurement of different parameters of the driver such as Pulse Rate, Alcoholic Condition and Eye blink using the sensors like Heartbeat Sensor, Alcohol Sensor and Eye Blink Sensor respectively. There are many products out there that provide the measure of fatigue level in the drivers which are implemented in many vehicles. The driver drowsiness detection and health monitoring system provide the similar functionality but with better results and additional benefits. Also, it alerts the user on reaching a certain saturation point of the drowsiness measure.
II. LITERATURE SURVEY
A. Hardware Components
The Arduino integrated development environment (IDE) is a cross-platform application (written for Operating systems like Microsoft Windows, macOS, and Linux) which is written in the Java. It includes a code editor with features like text cutting and pasting, searching, and replacing text, automatic indenting, brace matching, and syntax highlighting, and more. Message area, a text console, a toolbar with buttons for common functions and a hierarchy of operation menus are also included in Arduino IDE.
The Arduino IDE supports the languages C and C++ to work with different sensors and applications. There are different libraries which Arduino supports depending on the user’s choice, they can install and run it without the needs to re-install any of the main application.
2. Thinger.io Console
Thinger.io is a cloud IoT Platform that provides every needed tool to prototype, scale and manage connected products in a very simple way.
a. Free IoT platform: Thinger.io provides a freemium account with only few limitations in terms of the number of sensors that can be connected, however if the user wishes to work with a greater number of sensors, they can choose the premium licensed version which has many more options to choose from compared to the free version.
b. Simple but Powerful: All in the matter of working with components in the platform is so much easier to connect to obtain the values and just in few minutes and is powerful and quick to run the application.
c. Hardware agnostic: Any device from any manufacturer can be easily integrated with Thinger.io's infrastructure.
d. Extremely scalable & efficient infrastructure: The IoT server subscribes device resources to retrieve data only when it is necessary, a single Thinger.io instance can manage thousands of IoT devices with low computational load, bandwidth, and latencies.
e. Open-Source: It can be made available to the public to view, and it is also extremely easy to import/export from GitHub for ready-made codes.
IV. PROPOSED SYSTEM
Our proposed system consists of two microcontrollers: Arduino Nano and ESP32 where the ignition key, Ignition relay, buzzer, Eye-blink sensor, pulse sensor, ultrasonic sensor and alcohol sensor are connected to the Arduino Nano board. The GPS, GSM and the water sprinkler are connected to the ESP32 board. All the values from these sensors are being sent to the cloud server. The reason why we are using two microcontrollers is that the Arduino Nano does not have internet connectivity hence the usage of the ESP32.
The thinger.io displays:
In our proposed system, the driver must wear the goggles and the pulse sensor to detect the drowsiness and the health parameter. Once the ignition key gets turned ON all the components gets activated and the heartbeat of the driver is measured through pulse sensor and is displayed in the cloud. If the driver eyes is closed for more than 4 seconds the eye blink sensor attached to the goggles will detect and buzzer alerts the driver, similarly if the driver eyes is closed for 3 times along with the buzzer the water get sprinkled on the face of the driver, the ignition key gets turned OFF automatically, in cloud the value gets updated and a message is send to the family members along with the location of driver. The MQ3 sensor in our proposed system detects the alcoholic condition of the driver and it will also be indicated in the cloud as well as a message will be sent to the family member along with the location of driver. Ultrasonic sensor in our proposed system detects objects whenever the driver is drowsy, alcoholic or is unwell due to health parameter and alerts the driver through the buzzer which helps to reduce accidents.
Our project has a capability of detecting the drowsiness, alcohol, pulse rate and obstacle detection to reduce accidents. If the alcohol and drowsiness is detected the ignition key is turned off and the SMS will be sent to the respective family member and the location of the driver as shown in Fig 4. Having that feature allows the driver’s family or relatives to locate the driver quickly if gotten to any accidents.
Drowsy driving is one of the main causes of road traffic accidents around the world of around 21% and counting. By contrast, around 28% of accidents are caused by drunk driving and is increasing rapidly. According to the study of all the research papers at hand, each paper had a different approach with detecting driver drowsiness but followed similar practices in reducing/preventing it. From the comparations between other drowsy detection techniques, we have found that the eye state analysis-based techniques are the better methodology for detecting drowsiness/fatigue. Eye-state analysis- based methods has many benefits such as being non-intrusive and having low computation costs, high robustness, high accuracy and so on. Some of the research papers also measures certain parameters like pulse rate, temperature, alcohol consumption and based on that the vehicle stops/reduces its speed. Based on these findings, our goal is to implement a system that ensures the safety of the driver and avert vehicle accidents.
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Copyright © 2022 Akshara M. C., Harshitha T. S., Nithya Deepak, Priyanka B, Prof. Sharath H. A.. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Authors : Nithya Deepak
Paper Id : IJRASET45810
Publish Date : 2022-07-20
ISSN : 2321-9653
Publisher Name : IJRASET
DOI Link : Click Here