第一次看到通过智能手机传感器收集车辆数据

Michael Reininger, Seth Miller, Yanyan Zhuang, Justin Cappos
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引用次数: 33

摘要

智能手机是与外界联系的技术接口。这些设备具有嵌入式机载传感器(如加速度计、WiFi和gps),可以为调查用户需求和行为模式提供有价值的信息。同样,嵌入车辆中的计算机能够收集有价值的传感器数据,这些数据可以通过使用车载诊断(OBD)传感器由智能手机访问。本文描述了一个移动计算平台的原型,该平台可以通过使用智能手机和平板电脑访问车辆的传感器,而不会损害这些设备的安全性。通过使用WiFi车载诊断(OBD)传感器,从行驶中的车辆收集速度、发动机转速、油耗、GPS位置等数据,然后传回远程服务器进行实时和离线分析。我们描述了我们平台的设计和实现细节,为此我们开发了一个用于车载传感器访问的库,并创建了一个用于可扩展后端数据存储的非关系数据库。我们认为,我们的数据收集和可视化工具对分析驾驶行为很有用;我们还讨论了未来的应用,安全和隐私问题,具体到车载网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A first look at vehicle data collection via smartphone sensors
Smartphones serve as a technical interface to the outside world. These devices have embedded, on-board sensors (such as accelerometers, WiFi, and GPSes) that can provide valuable information for investigating users' needs and behavioral patterns. Similarly, computers that are embedded in vehicles are capable of collecting valuable sensor data that can be accessed by smartphones through the use of On-Board Diagnostics (OBD) sensors. This paper describes a prototype of a mobile computing platform that provides access to vehicles' sensors by using smartphones and tablets, without compromising these devices' security. Data such as speed, engine RPM, fuel consumption, GPS locations, etc. are collected from moving vehicles by using a WiFi On-Board Diagnostics (OBD) sensor, and then backhauled to a remote server for both real-time and offline analysis. We describe the design and implementation details of our platform, for which we developed a library for in-vehicle sensor access and created a non-relational database for scalable backend data storage. We propose that our data collection and visualization tools are useful for analyzing driving behaviors; we also discuss future applications, security, and privacy concerns specific to vehicular networks.
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