Inference of driver behavior using correlated IoT data from the vehicle telemetry and the driver mobile phone

Daniel Alves da Silva, José Alberto Sousa Torres, Alexandre Pinheiro, Francisco L. de Caldas Filho, Fábio L. L. Mendonça, B. Praciano, Guilherme Oliveira Kfouri, Rafael Timóteo de Sousa Júnior
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引用次数: 2

Abstract

Drivers’ behavior in traffic is a determining factor for the rate of accidents on roads and highways. This paper presents the design of an intelligent IoT system capable of inferring and warning about road traffic risks and danger zones, based on data obtained from the vehicles and their drivers mobile phones, thus helping to avoid accidents and seeking to preserve the lives of the passengers. The proposed approach is to collect vehicle telemetry data and mobile phone sensors data through an IoT network and then to analyze the driver’s behavior while driving, along with data from the environment. The results of the inference serve to alert drivers about incidents in their trajectory as well as to provide feedback on how they are driving. The proposal is validated using a developed prototype to test its data collection and inference features in a small scale experiment.
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使用来自车辆遥测和驾驶员手机的相关物联网数据推断驾驶员行为
司机的交通行为是道路和高速公路事故率的决定因素。本文介绍了一种智能物联网系统的设计,该系统能够根据从车辆及其驾驶员手机获得的数据推断和警告道路交通风险和危险区域,从而帮助避免事故并寻求保护乘客的生命。提议的方法是通过物联网网络收集车辆遥测数据和手机传感器数据,然后分析驾驶员在驾驶时的行为以及来自环境的数据。推理的结果可以提醒驾驶员注意他们行驶轨迹上的事故,并就他们的驾驶方式提供反馈。在小型实验中,利用开发的原型验证了该方案的数据收集和推理特性。
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