A Comprehensive Study on IoT Based Accident Detection Systems for Smart Vehicles
Abstract : With population growth, the demand for vehicles has increased tremendously, which has created an alarming situation in terms of traffic hazards and road accidents. The road accidents percentage is growing exponentially and so are the fatalities caused due to accidents. However, the primary cause of the increased rate of fatalities is due to the delay in emergency services. Many lives could be saved with efficient rescue services. The delay happens due to traffic congestion or unstable communication to the medical units. The implementation of automatic road accident detection systems to provide timely aid is crucial. Many solutions have been proposed in the literature for automatic accident detection. The techniques include crash prediction using smartphones, vehicular ad-hoc networks, GPS/GSM based systems, and various machine learning techniques.With such high rates of deaths associated with road accidents, road safety is the most critical sector that demands significant exploration. In this paper, we present a critical analysis of various existing methodologies used for predicting and preventing road accidents, highlighting their strengths, limitations, and challenges that need to be addressed to ensure road safety and save valuable lives.
? In the speed of the vehicle has monitored with the help of GPS receiver and detected accident by comparing the previous and current speed of vehicles.
? The data regarding accidents were collected using Accelerometer, Gyroscope and four force sensors attached at each side of the vehicle.
? Though the system sent a text message to the emergency contact or public safety, the response time depends on the distance between the location of the accident and the public safety service center.
? The system detected accident by comparing the previous and current speed of the vehicle. While an accident detected it sent the location to an Alert Service Center.
? IoT has vast uses and benefits in different sectors and solves many problems, but still it has various challenges and limitations.
? In order to use the IoT devices, it’s need of time that problem of storing power in devices should be solved.
? The main issue in VANETs is, it’s highly dynamic topology due, to which different problems like network congestion, frequent disconnections etc. may arise.
? The problem of the system is that it relies only on a single sensor for accident detection which has high chance of generating false positives.
? One of the major issue to implement IoT is mobility, because IoT is expected to offer services to the mobile users as well.
• In our proposed system we use the GPS device to find the exact accident location.
• Proposed system will provide an automatic detection and alert of accident it also locates the location of the vehicle and send it to emergency numbers and registered mobile number and send alert on email.
• The system we made is the lower cost then others as we are not using any expensive device like gsm and other sensors.
• The system just uses the node mcu as a main controller of the system and other than that we are using MPU-6050 3 Axis Accelerometer and Gyroscope sensor to detect the accident occurs and NE0-6M gps module to locate the exact position of the vehicle.
? The major advantage of the approach is that, representation learning can capture more intelligent features from raw input data as compared to manual methods.
? It can monitor it’s performance and can process the data to choose the one that needs maintenance.
? The performance of routing protocols is analyzed based on the routing techniques used by the protocols.
? However, its main limitation is that there could be a false alarm in case when the person sitting next to driver is drunk but the driver is not drunk, moreover external interference of air can also affect the performance of alcohol sensor.
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