Road Sensing through a Connected Vehicle Fog Approach for Smart Cities

智慧城市的车载道路传感涉及大量的物联网（IoT）设备，这些设备可以产生大量的数据。作为一种非常高效的城市感知工具，车辆可以成为“眼睛和耳朵”，收集和分发道路状况、交通状况、天气、空气质量、车辆状况等数据。据估计，智能汽车中各种传感器收集的数据量约为每小时25 GB。在这种环境中，数据需要被挖掘、过滤、存储、处理，然后及时传播给目标玩家。然而，在像车联网这样的大规模动态系统中，客观、高效地获取信息是一个主要的难点。目前在智慧城市中存储和处理物联网数据的解决方案涉及集中式云方法。然而，集中式方法缺乏实时计算特性，无法提供快速反馈响应，以及应用于车载网络时的其他限制。另一个挑战在于如何以比现有机制更智能、更有选择性的方式向智能交通系统（ITS）应用的最终用户提供道路传感数据。为了克服现有方案的不足，在考虑实时处理约束、车辆移动性和资源异构性的前提下，迫切需要一种车载雾计算资源编排方案。因此，本研究将调查、设计、实施和评估算法和工具，通过智能城市的联网车辆雾平台，促进道路传感数据的收集、处理和分发。更具体地说，该研究计划将：(a)调查现有的车辆雾计算资源管理方案；(b)设计和开发一种新的车载雾计算资源分配方案；(c)研究如何将有关数据纳入拟议的道路感应平台；(d)设计和发展一个聪明和有选择的数据传送系统；(e)通过模拟，利用最相关的基准评价拟议的技术；(f)设计及实施一套智能交通系统应用系统，例如创新的湿滑路面警告系统，以展示拟议的道路感应平台。人们高度期待这项研究的成果将促进ICT公司、政府机构、市政当局和其他利益相关者强烈感兴趣的创新进步。因此，所提出的道路传感平台是及时的，绝对可以为智慧城市环境中城市数据的收集和分发以及交通和资源管理提供有效的工具。这项工作将使服务提供商能够开发新的应用程序，这些应用程序将利用拟议的数据分发平台，为加拿大人提供智能和量身定制的服务，以改善他们的通勤和安全，减少碳排放，并为创新解决方案铺平道路。

Vehicular road sensing for smart cities involves a large number of Internet of Things (IoT) devices that can generate a massive volume of data. Vehicles can be the "eyes and ears" as a very efficient urban sensing tool, collecting and distributing data about road condition, traffic status, weather, air quality, vehicle status, just to mention a few. The amount of data collected by the various sensors in a smart vehicle has been estimated to be around 25 GB/h. In this kind of environment, data needs to be mined, filtered, stored, processed, and then disseminated to target players in a timely fashion. However, one of the major difficulties in large scale and dynamic systems such as vehicular networks lies in accessing information objectively and efficiently. Current solutions for storing and processing IoT data in smart cities involve centralized cloud approaches. However, centralized methods lack real-time computation properties and fail to provide quick feedback responses, among other limitations when applied to vehicular networks. Another challenge lies in how to deliver road sensing data to intelligent transportation system (ITS) application's end users in a more intelligent and selective way than existing mechanisms. In order to overcome the shortcomings of existing schemes, a vehicular fog computing resource orchestration scheme is highly needed while considering real-time processing constraints, vehicles mobility, and resource heterogeneity. Therefore, this research will investigate, design, implement and evaluate algorithms and tools to facilitate the collection, processing, and distribution of road sensing data through a connected vehicle fog platform for smart cities. More specifically, this research program will: (a) investigate the existing vehicular fog computing resource management schemes; (b) Design and develop a novel vehicular fog computing resource allocation scheme; (c) Study how contextual data can be integrated into the proposed road sensing platform; (d) Design and develop a smart and selective data delivery system; (e) Evaluate the proposed technologies using the most relevant benchmarks through simulations; (f) Design and implement an ITS application, e.g., an innovative slippery road warning system, to showcase the proposed road sensing platform. It is highly expected that the outcomes of this research will foster innovative advances of strong interest to ICT companies, government agencies, municipalities, and other stakeholders. Thus, the proposed road sensing platform is timely and can definitely provide an efficient tool to harvest and distribute urban data and aid in traffic and resource management in a smart city environment. This work will enable service providers to develop novel applications that will tap into the proposed data distribution platform and provide Canadians with smart and tailored services to improve their commutes and safety, reduce carbon emissions, and pave the way for innovative solutions.