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Proceedings ArticleDOI

Modeling Vehicle Collision Events using Internet of Things

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TLDR
An IoT system that uses in-built sensors of a smartphone to report road accidents accurately is demonstrated, found to be highly accurate with a MAPE of 2.34 percent and 3.49 percent respectively.
Abstract
With the increase in road accidents in several countries, there is a need for an inexpensive and reliable system that can be retrofitted to any type of vehicle and can predict and report road accident events. This work aims to demonstrate an IoT system that uses in-built sensors of a smartphone to report road accidents accurately. NHTSA (National Highway Traffic Safety Administration) datasets have been used to train and test our accident prediction models. The prediction performance was found to be highly accurate with a MAPE of 2.34 percent and 3.49 percent respectively, for the datasets used.

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Citations
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Journal ArticleDOI

Vehicle accident sub-classification modeling using stacked generalization: A multisensor fusion approach

TL;DR: In this article , an Android smartphone-based end-to-end Internet of Things (IoT) system that can transmit accident information to emergency services and affected families once a vehicle accident is detected.
References
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Journal ArticleDOI

Mean Absolute Percentage Error for regression models

TL;DR: It is proved the existence of an optimal MAPE model and the universal consistency of Empirical Risk Minimization based on the MAPE is shown, and it is shown that finding the best model under theMAPE is equivalent to doing weighted Mean Absolute Error regression, and this weighting strategy is applied to kernel regression.
Journal ArticleDOI

Delay-Aware Accident Detection and Response System Using Fog Computing

TL;DR: The research proposed here leverages the advantages of sophisticated features of smartphones and fog computing to propose and develop a low-cost and delay-aware accident detection and response system, which is term Emergency Response and Disaster Management System (ERDMS).
Proceedings ArticleDOI

Real time in-vehicle air quality monitoring using mobile sensing

TL;DR: A novel mobile sensing system is proposed to monitor and understand change in VIAQ, built by using an Android Smartphone and a mobile sensor, is independent of car age and model, and monitors ViaQ at all times.
Journal ArticleDOI

A Real-time Fall Detection System Based on the Acceleration Sensor of Smartphone

TL;DR: In this article, a fall detection system that uses the acceleration sensor of a smartphone is proposed. But it is not suitable for the elderly people and it cannot be used in the case of wheelchairs.
Journal ArticleDOI

The effect of mass properties on road accident reconstruction

TL;DR: In this article, the influence of vehicle mass properties (mass, center of gravity location, inertia tensor) on accident reconstruction is investigated in the case of two colliding vehicles.
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