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Road Hazard Detection and Sharing with Multimodal Sensor Analysis on Smartphones

机译:智能手机上多模式传感器分析的道路危害检测与共享

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The sensing, computing and communicating capabilities of smart phones bring new possibilities for creating smart applications, including in-car mobile applications for smart cities. However, due to the dynamic nature of vehicles, many requirements such as sensor management, signal and image processing or information sharing needs exist when developing a smart sensor-based in-car mobile application. On the other hand, most in-car applications generally employ single-modal sensor analysis, which also yields limited results. Using the advanced capabilities of smart phones, this study proposes a framework with built-in multimodal sensor analysis capability, and enables easy and rapid development of signal and image processing-based smart mobile applications. Within this framework, an abstraction for fast access to synchronized sensor readings, a plug in based multimodal analysis interface for signal and image processing applications, and a toolset to connect to other users or servers for sharing the results are provided built-in. As part of this study, a sample mobile application is also developed to demonstrate the applicability of the framework. This application is used for detecting defects on the road, such as potholes and speed bumps, and it automatically extracts the video section and the image of the corresponding road segment containing the defect. Upon such critical hazard detection, the application instantly informs nearby users about the incident. A good detection rate of speed bumps is obtained in the performed tests, while the advantage of automatic image extraction based on the multimodal approach is also demonstrated.
机译:智能手机的感测,计算和通信功能为创建智能应用程序(包括用于智能城市的车载移动应用程序)带来了新的可能性。但是,由于车辆的动态特性,在开发基于智能传感器的车载移动应用程序时,存在许多要求,例如传感器管理,信号和图像处理或信息共享需求。另一方面,大多数车内应用通常采用单模式传感器分析,这也会产生有限的结果。利用智能手机的高级功能,本研究提出了一个具有内置多模式传感器分析功能的框架,并可以轻松,快速地开发基于信号和图像处理的智能移动应用程序。在此框架内,内置了用于快速访问同步传感器读数的抽象,用于信号和图像处理应用程序的基于插件的多峰分析接口,以及用于连接其他用户或服务器以共享结果的工具集。作为这项研究的一部分,还开发了一个示例移动应用程序来演示该框架的适用性。该应用程序用于检测道路上的缺陷(例如坑洼和减速带),并自动提取包含该缺陷的相应路段的视频部分和图像。在检测到此类严重危害后,该应用程序会立即将该事件通知附近的用户。在进行的测试中获得了良好的减速带检测率,同时还展示了基于多模式方法的自动图像提取的优势。

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