Cloud-based driver monitoring and vehicle diagnostic with OBD2 telematics

Malintha Amarasinghe, Sasikala Kottegoda, A. Arachchi, Shashika Ranga Muramudalige, H. Bandara, A. Azeez
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引用次数: 62

Abstract

We present a cloud-based vehicular data acquisition and analytics system for real-time driver behavior monitoring, trip analysis, and vehicle diagnostics. Our system consists of an On Board Diagnostics (OBD) port to Bluetooth dongle, a mobile app running on a smart phone, and a cloud-based backend. We use a Complex Event Processor (CEP) at both the smart phone and the backend to detect and notify unsafe and anomalous events in real time. For example, CEP engine at the smart phone can alert the driver about rising coolant temperature and rapid fuel drops. It also provides a trip log and filter out what messages to be send to the backend, saving both the bandwidth and power. CEP on the cloud detects reckless driving in real time based on the sensor data provided through the OBD port. Historical data is also used by the backend CEP engine to detect driving anomalies and to predict impeding sensor failures. The mobile app visualizes both real-time data from sensors and alerts. A web-based interface is provided to access the backend information. We tested the system on actual vehicles and demonstrated that the computing, bandwidth, and power consumption of the smart phone is reasonable. App is currently available in Google Play.
基于云的驾驶员监控和车辆诊断与OBD2远程信息处理
我们提出了一个基于云的车辆数据采集和分析系统,用于实时驾驶员行为监控、行程分析和车辆诊断。我们的系统包括一个车载诊断(OBD)端口到蓝牙加密狗,一个运行在智能手机上的移动应用程序,以及一个基于云的后端。我们在智能手机和后端都使用复杂事件处理器(CEP)来实时检测和通知不安全和异常事件。例如,智能手机上的CEP发动机可以在冷却液温度上升和燃料快速下降时提醒驾驶员。它还提供行程日志并过滤要发送到后端的消息,从而节省带宽和功率。云上的CEP根据通过OBD端口提供的传感器数据实时检测鲁莽驾驶。后端CEP引擎还使用历史数据来检测驾驶异常并预测阻碍传感器故障。这款手机应用程序可以显示来自传感器和警报的实时数据。提供了一个基于web的接口来访问后端信息。我们在实际车辆上测试了该系统,并证明了智能手机的计算,带宽和功耗是合理的。应用程序目前可在谷歌播放。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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