Big Data Processing and Analysis in Internet of Vehicles: Architecture, Taxonomy, and Open Research Challenges

Arooj, Ansif; Farooq, Muhammad Shoaib; Akram, Aftab; Sharma, Ashutosh

doi:10.1007/s11831-021-09590-x

Cited by 49 publications

(23 citation statements)

References 105 publications

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“…In addition, intelligent traffic management systems can use big data insights to increase mobility efficiency and decrease congestion and travel time for commuters. Addressing big data in IoV can revolutionize ITS and pave the way for smart cities (Hemmati et al, 2023d;Arooj et al, 2022).…”

Section: Overview Of Big Data In Internet Of Vehiclesmentioning

confidence: 99%

Big data challenges and opportunities in Internet of Vehicles: a systematic review

Hemmati,

Zarei,

Rahmani

2024

IJPCC

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Purpose Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research. Design/methodology/approach This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis. Findings This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues. Research limitations/implications This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted. Originality/value This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.

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Section: Overview Of Big Data In Internet Of Vehiclesmentioning

confidence: 99%

Big data challenges and opportunities in Internet of Vehicles: a systematic review

Hemmati,

Zarei,

Rahmani

2024

IJPCC

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“…As a weakness, this study lacks a full review of data-centric approaches in the IoV. Arooj et al 17 provided a systematic review of big data in the IoV to highlight opportunities, methodologies, and future challenges. They suggested some analysis methods, tools, and strategies in this field by presenting a taxonomy and provided some recommendations for big data challenges.…”

Section: Background and Related Workmentioning

confidence: 99%

Data‐centric approaches in the Internet of Vehicles: A systematic review on techniques, open issues, and future directions

Partovi

Zarei

Rahmani

2022

Int J Communication

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The Internet of Vehicles (IoV) is an emerging network of connected vehicles as a branch of dynamic objects in the Internet of Things (IoT) ecosystem. With the rapid development of IoV, real-time data-centric applications would be a significant concern in academia and industry to promote efficiency and realize modern services in such high dynamic networks. In this paper, we aim to present a systematic literature review (SLR) for the IoV networks to investigate the different attitudes in the field of data-centric approaches. This paper systematically categorizes the 48 recent articles on data-driven techniques in the IoV field published from 2017 to March 2022. A complete technical taxonomy is presented for the data-centric approaches in IoV according to the content of current studies. Collected methods are chosen with the SLR process, and they are investigated considering some technical classifications including IoV security, data traffic, vehicular social network, data propagation, energy, and multimedia categories. The achievements, drawbacks, and new findings of studies are carefully investigated for addressing the deficiencies, as well as emphasizing future research direction and open issues of data-driven approaches in IoV. K E Y W O R D S data trading system, data traffic management, data transmission, Internet of Vehicles, IoV | INTRODUCTIONVehicular ad hoc networks (VANETs) as highly dynamic but well-organized emerging networks play an effective role in accelerating the improvement of the intelligent transportation systems (ITS) application. 1 Today ITS applications in many nations are expanding, whereby the rapid growth of networked sensors and context-aware computing systems, along with emerging communication technologies, have made the recognition of smart cities possible shortly. 2 The Internet of Things (IoT) technology has faced an increase in the number of dynamic objects, including connected vehicles, which formed the Internet of Vehicles (IoV), and made our lives easier, safer, and smarter. [3][4][5] VANETs, as the central infrastructure of the IoV ecosystem, aim to help drivers with possible inter-vehicle communication (IVC) and realtime data propagation even in high mobility, helping safety driving and receiving alerts for road hazardous. 6,7 Plug-in electric vehicles (PEVs) and unmanned aerial vehicles (UAVs), as an emerging part of energy-aware VANETs, have a significant impact on the formation of the IoV. 8 Connected vehicles in IoV are intelligent vehicles with a complicated software platform. Promoting vehicles from high dynamic nodes to intelligent vehicles with diverse communication

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“…Integrated with three networks: intra-vehicle network, inter-vehicle network, and onboard mobile Internet, the CV, also known as the "Internet of Vehicles" (IoV), is intrinsically a large distributed communication system for V2X interaction, where X involves other CVs, individuals, and networks [82]. As a profound scenario for the application of the Internet of Things (IoT) in the intelligent transportation system (ITS), the CVs enable a multifunctional network that supports intelligent transportation management, intelligent dynamical information services, and intelligent driving control [83].…”

Section: Technologiesmentioning

confidence: 99%

Trends and Emerging Technologies for the Development of Electric Vehicles

Liu

Lau

et al. 2022

Energies

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In response to severe environmental and energy crises, the world is increasingly focusing on electric vehicles (EVs) and related emerging technologies. Emerging technologies for EVs have great potential to accelerate the development of smart and sustainable transportation and help build future smart cities. This paper reviews new trends and emerging EV technologies, including wireless charging, smart power distribution, vehicle-to-home (V2H) and vehicle-to-grid (V2G) systems, connected vehicles, and autonomous driving. The opportunities, challenges, and prospects for emerging EV technologies are systematically discussed. The successful commercialization development cases of emerging EV technologies worldwide are provided. This review serves as a reference and guide for future technological development and commercialization of EVs and offers perspectives and recommendations on future smart transportation.

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Big Data Processing and Analysis in Internet of Vehicles: Architecture, Taxonomy, and Open Research Challenges

Cited by 49 publications

References 105 publications

Big data challenges and opportunities in Internet of Vehicles: a systematic review

Big data challenges and opportunities in Internet of Vehicles: a systematic review

Data‐centric approaches in the Internet of Vehicles: A systematic review on techniques, open issues, and future directions

Trends and Emerging Technologies for the Development of Electric Vehicles

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