An Intra-Vehicular Wireless Multimedia Sensor Network for Smartphone-Based Low-Cost Advanced Driver-Assistance Systems.
An Intra-Vehicular Wireless Multimedia Sensor Network for Smartphone-Based Low-Cost Advanced Driver-Assistance Systems.
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DOI：
10.3390/s22083026
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发表时间：
2022-04-15
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影响因子：
--
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高级驾驶辅助系统（ADAS）在高端车辆中比在低端车辆中更为普遍。ADAS中视觉传感器的有线解决方案已经存在，但价格昂贵且不适合低端车辆。一般ADAS采用有线线束通信；这种方法消除了电缆利用的需要，因此，测试了一种新型无线ADAS解决方案的实用性。提出了一种低成本的替代方案，利用基于摄像头的无线传感器网络扩展智能手机的传感器感知能力。本文介绍了一种低成本的ADAS替代方案的设计，该方案使用由Wi-Fi Direct拓扑结构构成的车载无线传感器网络，使用智能手机作为处理平台。该系统使更便宜的车辆也可以使用ADAS功能，并研究了在车内环境中使用无线网络通信ADAS信息的可能性。其他ADAS智能手机方法利用智能手机的板载传感器；然而，本文展示了在智能手机的ADAS应用程序上开发的基本ADAS功能的应用，通过使用无线传感器数据对车辆进行车道检测和碰撞检测。利用智能手机的处理能力，通过卷积神经网络，利用感官网络的视频流，将其用作通用目标检测器。对网络的性能进行了分析，以保证网络能够实时进行检测。一款搭载智能手机的低成本CMOS摄像头传感器网络找到了一个应用程序，使用Wi-Fi Direct创建车内无线网络，作为一种低成本的高级驾驶员辅助系统。
Advanced driver-assistance system(s) (ADAS) are more prevalent in high-end vehicles than in low-end vehicles. Wired solutions of vision sensors in ADAS already exist, but are costly and do not cater for low-end vehicles. General ADAS use wired harnessing for communication; this approach eliminates the need for cable harnessing and, therefore, the practicality of a novel wireless ADAS solution was tested. A low-cost alternative is proposed that extends a smartphone’s sensor perception, using a camera-based wireless sensor network. This paper presents the design of a low-cost ADAS alternative that uses an intra-vehicle wireless sensor network structured by a Wi-Fi Direct topology, using a smartphone as the processing platform. The proposed system makes ADAS features accessible to cheaper vehicles and investigates the possibility of using a wireless network to communicate ADAS information in a intra-vehicle environment. Other ADAS smartphone approaches make use of a smartphone’s onboard sensors; however, this paper shows the application of essential ADAS features developed on the smartphone’s ADAS application, carrying out both lane detection and collision detection on a vehicle by using wireless sensor data. A smartphone’s processing power was harnessed and used as a generic object detector through a convolution neural network, using the sensory network’s video streams. The network’s performance was analysed to ensure that the network could carry out detection in real-time. A low-cost CMOS camera sensor network with a smartphone found an application, using Wi-Fi Direct, to create an intra-vehicle wireless network as a low-cost advanced driver-assistance system.
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发表时间：
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