Deployment of IoV for Smart Cities: Applications, Architecture, and Challenges

Ang, Li-Minn; Seng, Kah Phooi; Ijemaru, Gerald K.; Zungeru, Adamu Murtala · 2019 · DOAJ

DOI: 10.1109/ACCESS.2018.2887076

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Summary

This paper addresses the evolving role of the Internet of Vehicles (IoV) within smart city environments, arguing that current research disproportionately focuses on intelligent transportation systems (ITS) such as driver safety and traffic efficiency. The authors identify a significant gap in the literature regarding the IoV’s potential for large-scale data sensing, collection, and processing for broader smart city applications. To bridge this gap, the study provides a comprehensive review of IoV paradigms and proposes a new Universal IoV (UIoV) architecture designed to support diverse communication models and big data requirements in urban settings. The methodology involves a systematic review of existing IoV architectures and communication models, categorized by applications, architectural layers, and challenges. The authors analyze previous works that typically utilize three- to five-layered structures tailored for ITS, noting their inadequacy for handling the heterogeneous nature of big data and multimedia content generated by smart city objects. Based on this analysis, the paper introduces the UIoV, a seven-layer architecture comprising: vehicle identification, object, inter-intra devices, communication, servers and cloud services, big data and multimedia computation, and application layers. This design explicitly incorporates functional units for big data analytics and multimedia processing, addressing the limitations of prior models that lacked robust mechanisms for data aggregation from static smart objects like garbage cans or infrastructure sensors. Key findings highlight the dual utility of vehicles in smart cities: as nodes for ITS applications and as mobile data mules for urban sensing. The review cites experimental evidence, such as a study in Rome where 320 taxis achieved 80% data collection coverage of the downtown area within 24 hours, and another in Sydney where vehicular sensor networks reduced sensing report costs by up to 92%. The paper identifies critical challenges for IoV deployment, including the impact of increasing vehicle density and node mobility on packet delivery success rates. The authors note that existing IoT protocols fail to account for the dynamic network structures inherent in IoV, necessitating new approaches for reliable data transmission in high-mobility scenarios. The significance of this work lies in its expansion of the IoV scope beyond transportation to include comprehensive smart city infrastructure management. By proposing the UIoV architecture, the paper provides a framework for integrating big data processing and multimedia analytics into vehicular networks. This enables vehicles to serve as distributed computing resources and data collectors for environmental monitoring, structural health assessment, and urban surveillance. The study concludes by emphasizing the need for future research to address the technical complexities of packet delivery in dynamic networks and to develop strategies for managing the massive volumes of data generated by the convergence of mobile internet and IoT technologies.

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• v2x connected vehicle