IoT Based Frame work for Automatic accident Intimation System

According to a recent research, over 10 million individuals die each year as a result of roadway accidents. Accidents kill more people than terrorism or natural disasters around the world. In many scenarios the vehicle accident information is not reported to the emergency center department. As a res...

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Bibliographic Details
Main Authors: G, Jaffino, T, Palaniappan, MK, Samuel Swamidoss, G, Gugapriya, Kumar, Madhu manikya, Jose, J Prabin
Format: Conference Proceeding
Language:English
Subjects:
accident
Cloud computing
Communication systems
Embedded systems
Internet of Things
Internet of things (IOT)
neural network
Neural networks
Rider optimization algorithm
Servers
Terrorism
thingSpeak
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Summary:According to a recent research, over 10 million individuals die each year as a result of roadway accidents. Accidents kill more people than terrorism or natural disasters around the world. In many scenarios the vehicle accident information is not reported to the emergency center department. As a result of this, many people are died in accident because of delayed ambulance service. The goal of this work is to develop an Internet of Things (IOT) based automatic accident notification system. The designed setup has to intimate the accident status immediately to the emergency center, inorder to reduce the death rate in accidents. In the first step, the Sensor module is designed to extract the sensor data from the vehicle. In the second step TM4C123GXL texas embedded processor is used to transfer the sensor data to thingSpeak cloud server. In the final step, Expectation-Maximization Rider optimization algorithm (EM-ROA) is utilized to train the neural network and identify the conventional sensor data and accident time sensor data in the cloud server. The EM-ROA approach has generated better results with maximum precision of 91.25%
ISSN:2575-7288
DOI:10.1109/ICACCS54159.2022.9785220