An IoT based accident severity detection for automobiles with alerting the appropriate location of the accident - An innovative attempt
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Although occupant protection systems are aiding the present means of transportation like cars etc., the statistics of crash severity surveyed from past few years indicate that the mortality rate has increased to about 35% indicating the need of augmenting the quality of service to be given to the citizens. An article from Times of India tells that 27% of the deaths caused in India are due to the lack of medical attention and delay in the medical help which has been a persistent cause for deaths mainly for the accidents occurring on the highways. NHTSA(National Highway Traffic Safety Administration) says that on an average about 15,913 accidents occur per day in the USA based on the statistics of a survey for a period of 5 years. For an instance consider a place on a long highway where there exists only one hospital with basic requirements like emergency ward, ambulance service and an Operational Theatre and let us suppose that 4 to 5 accidents had happened in the same province of the hospital. Now, the hospital authorities will be in a dilemma because there is uncertainty in the decision to where the ambulance must be sent first. If the ambulance is sent to the nearest place where the severity of the accident is very low, the person with a big hit will succumb to death fastly. The problem lies in intimating the severity of the accident to the hospital. There are systems designed to detect the collision and implant the airbags and safety measures, but many systems don’t measure the severity level of the accident. So, here we introduce a system to measure and intimate the severity of the accident and even our system provides the geotag i.e., details of the place where the accident has happened and time stamp. The whole system is built with Force sensitive resistors(FSR) which are capable of detecting an impact accurately and a GPS module is used to get the data of the longitude and latitude of the area of the crash. The data from the sensors are processed using a python script which checks whether the crash has occurred or not. This system mainly strives in decreasing the delay in the time of arrival of medical services to the place of accident or crash. It also helps the hospitals in deciding the right place for the medical services to be sent in case of multiple accidents at the same time by using Severity level. ...learn more
Project status: Published/In Market
Overview / Usage
The challenge we are trying to solve with this system is to intimate the severity level of an accident to hospitals thereby priority in providing medical aids is given to the accident with highest severity level by using IoT(Internet of Things) and Sensors. According to some of the surveys, it is found that the average response time for an ambulance to reach the site of an accident inside a district or town in India is approximately 18 to 19 minutes and with 3 ambulances it was brought down to 15 to 16 minutes. So from the above statistics, we can say that it takes approximately 20 minutes for the treatment to start which is a huge time for the patient. Now, if we extend the same problem for multiple accidents occurred at the same time in near premises from each other, it will become a knotty situation for the hospital authorities and creates confusion in sending the ambulance and due to lack of knowledge on the severity of the accident, wrong priority allocation takes place and medical aids may be sent to places with lesser severity. So, in order to overcome these types of problems we have come up with a solution which can predict the severity of the accident and conveys the location coordinates, google maps link to the hospitals in order to reduce the chances of wrong priority allocation. When there is an accident in a deserted place or long highways or in deep forest roads, there will be a lot of delay in noticing the accident which may cost the life of a person. In order to avoid it, our system immediately intimates the hospitals the place of the accident by which they can provide the medical aids immediately.
Methodology / Approach
Our proposed system uses a collision sensor which is practically used in cars for detecting whether the collision has happened or not, FSR(Force Sensitive Resistor) which measures the impact experienced by the car, GPS module for getting the Exact location of the car. If a collision has occurred then the FSR data, GPS data is sent to the server like Raspberry pi for data analytics to classify the severity level which immediately sends the timestamp, pin code, latitude, longitude, severity level, Google maps link data of the collision to a website for the reference of hospitals. This website can be used by the hospitals to know the information about nearby accidents and their severity level to provide emergency services accordingly. For the prototype purpose, we constructed a localhost database and HTML page for storing and displaying collision data using Xampp, phpmyadmin.
Technologies Used
IoT, Force Sensitive Resistor, GPS, Microcontroller, Data Analytics
Repository
https://www.youtube.com/watch?v=mQr68dIJD-U&index=7&list=PL3uLubnzL2Tml5Nn3IpDjAc097eTpQevy