Road Sensing through a Connected Vehicle Fog Approach for Smart Cities

智慧城市的车辆道路传感涉及大量物联网（IoT）设备，这些设备可以生成大量数据。车辆可以成为“眼睛和耳朵”，作为一种非常有效的城市传感工具，收集和分发有关道路状况、交通状况、天气、空气质量、车辆状态等数据。据估计，智能汽车中各种传感器收集的数据量约为25 GB/h。在这种环境中，需要对数据进行挖掘、过滤、存储、处理，然后及时分发给目标参与者。然而，在大规模和动态系统，如车辆网络的主要困难之一在于客观和有效地访问信息。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，并且在应用于车辆网络时无法提供快速反馈响应以及其他限制。另一个挑战在于如何以比现有机制更智能和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感测数据。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同时，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，以促进通过智能城市的联网车辆雾平台收集，处理和分发道路传感数据。更具体地说，本研究计划将：（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辆雾计算资源分配方案;（c）研究如何将上下文数据集成到拟议的道路传感平台中;（d）设计和开发一个智能和选择性的数据传输系统;（e）设计和开发一个智能和选择性的数据传输系统。（e）通过模拟使用最相关的基准评估拟议的技术;一个创新的湿滑道路警告系统，展示拟议的道路传感平台。人们高度期望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的强烈兴趣的创新进步。因此，所提出的道路传感平台是及时的，并且绝对可以提供一种有效的工具来收集和分发城市数据，并在智能城市环境中帮助进行交通和资源管理。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，并为加拿大人提供智能和定制的服务，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.