School of Electronics Engineering, Vellore Institute of Technology, Chennai 600127, India.
Department of Information Technology, MIT Campus, Anna University, Chennai 600025, India.
Sensors (Basel). 2023 Mar 24;23(7):3423. doi: 10.3390/s23073423.
In conventional modern vehicles, the Internet of Things-based automotive embedded systems are used to collect various data from real-time sensors and store it in the cloud platform to perform visualization and analytics. The proposed work is to implement computer vision-aided vehicle intercommunication V2V (vehicle-to-vehicle) implemented using the Internet of Things for an autonomous vehicle. Computer vision-based driver assistance supports the vehicle to perform efficiently in critical transitions such as lane change or collision avoidance during the autonomous driving mode. In addition to this, the main work emphasizes observing multiple parameters of the In-Vehicle system such as speed, distance covered, idle time, and fuel economy by the electronic control unit are evaluated in this process. Electronic control unit through brake control module, powertrain control module, transmission control module, suspension control module, and battery management system helps to predict the nature of drive-in different terrains and also can suggest effective custom driving modes for advanced driver assistance systems. These features are implemented with the help of the vehicle-to-infrastructure protocol, which collects data through gateway nodes that can be visualized in the IoT data frame. The proposed work involves the process of analyzing and visualizing the driver-influencing factors of a modern vehicle that is in connection with the IoT cloud platform. The custom drive mode suggestion and improvisation had been completed with help of computational analytics that leads to the deployment of an over-the-air update to the vehicle embedded system upgradation for betterment in drivability. These operations are progressed through a cloud server which is the prime factor proposed in this work.
在传统的现代车辆中，基于物联网的汽车嵌入式系统用于从实时传感器收集各种数据，并将其存储在云平台中以执行可视化和分析。拟议的工作是使用物联网为自动驾驶车辆实现计算机视觉辅助车辆间通信 V2V（车对车）。基于计算机视觉的驾驶员辅助支持车辆在自动驾驶模式下在关键过渡（例如变道或避碰）中高效运行。除此之外，主要工作强调通过电子控制单元评估车辆系统的多个参数，例如速度、行驶距离、空闲时间和燃油经济性。电子控制单元通过制动控制模块、动力总成控制模块、变速器控制模块、悬架控制模块和电池管理系统帮助预测不同地形的行驶性质，还可以为高级驾驶员辅助系统建议有效的自定义驾驶模式。这些功能是借助车辆到基础设施协议实现的，该协议通过网关节点收集数据，这些数据可以在物联网数据帧中可视化。拟议的工作涉及分析和可视化与物联网云平台连接的现代车辆的驾驶员影响因素的过程。借助计算分析完成了自定义驾驶模式建议和改进，从而实现了对车辆嵌入式系统的空中更新部署，以提高驾驶性能。这些操作是通过云服务器进行的，这是本工作提出的主要因素。
