Toward Social Internet of Vehicles: Concept, Architecture, and Applications

Alam, Kazi Masudul; Saini, Mukesh; Saddik, Abdulmotaleb El

doi:10.1109/access.2015.2416657

Cited by 347 publications

(151 citation statements)

References 33 publications

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“…With the significant development of smart vehicle produces, intelligent vehicle based Internet of Vehicle (IoV) technologies have received widespread attention of many giant Internet businesses [160][161][162]. The IoV technologies include the communication between different vehicles and vehicles to sensors, roads, and humans.…”

Section: Speech Recognition and Verification For The Internet Ofmentioning

confidence: 99%

A Survey on Machine Learning‐Based Mobile Big Data Analysis: Challenges and Applications

Xie

Song

et al. 2018

Wireless Communications and Mobile Computing

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This paper attempts to identify the requirement and the development of machine learning-based mobile big data (MBD) analysis through discussing the insights of challenges in the mobile big data. Furthermore, it reviews the state-of-the-art applications of data analysis in the area of MBD. Firstly, we introduce the development of MBD. Secondly, the frequently applied data analysis methods are reviewed. Three typical applications of MBD analysis, namely, wireless channel modeling, human online and offline behavior analysis, and speech recognition in the Internet of Vehicles, are introduced, respectively. Finally, we summarize the main challenges and future development directions of mobile big data analysis.

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Section: Speech Recognition and Verification For The Internet Ofmentioning

confidence: 99%

A Survey on Machine Learning‐Based Mobile Big Data Analysis: Challenges and Applications

Xie

Song

et al. 2018

Wireless Communications and Mobile Computing

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“…In their seminal work, Alam et al [20] envisioned the concept of a social network among cars as a cyber-physical layer on top of the physical vehicular network. Based on this concept, the authors proposed application scenarios that target both drivers, authorities and cars and discussed privacy issues that arise from such a system.…”

Section: Mobile Applicationsmentioning

confidence: 99%

“…To date, there are very few approaches in the literature that specifically target SIoVs. Most notably, the proposed SIoV architecture in [20] attempts to address privacy issues. However, their approach has three weaknesses.…”

Section: Privacy-enhancing Technologies For the Siovmentioning

confidence: 99%

Social Internet of Vehicles for Smart Cities

Μαγλαράς

Al-Bayatti

et al. 2016

JSAN

134

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Digital devices are becoming increasingly ubiquitous and interconnected. Their evolution to intelligent parts of a digital ecosystem creates novel applications with so far unresolved security issues. A particular example is a vehicle. As vehicles evolve from simple means of transportation to smart entities with new sensing and communication capabilities, they become active members of a smart city. The Internet of Vehicles (IoV) consists of vehicles that communicate with each other and with public networks through V2V (vehicle-to-vehicle), V2I (vehicle-to-infrastructure) and V2P (vehicle-to-pedestrian) interactions, which enables both the collection and the real-time sharing of critical information about the condition on the road network. The Social Internet of Things (SIoT) introduces social relationships among objects, creating a social network where the participants are not humans, but intelligent objects. In this article, we explore the concept of the Social Internet of Vehicles (SIoV), a network that enables social interactions both among vehicles and among drivers. We discuss technologies and components of the SIoV, possible applications and issues of security, privacy and trust that are likely to arise.

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“…The federated cloud computing utilities when coupled to physical systems and cyber systems form cyber physical clouds (CPC). CPCs constitute "CYBER" of cyber physical systems (CPS) and their services can be adopted by SGs, aggregators, independent system operators (ISO) as well as xEV users in social environments as defined by [38], [41], to enhance the controllability, efficiency and reliability of the transport oriented cities.…”

Section: High Performance Analyticsmentioning

confidence: 99%

“…social internet of vehicles (SIoV) [38], social transportation [14], vehicular crowdsourcing [39], platoon research [40] etc, from concept phase to implementation phase. Analytics in such domains will enrich the reliability of decisions obtained in TOSCs and extend the service range to infotainment, safety, traffic scheduling etc.…”

Section: High Performance Analyticsmentioning

confidence: 99%

Federated Cloud Analytics Frameworks in Next Generation Transport Oriented Smart Cities (TOSCs) - Applications, Challenges and Future Directions

Hussain¹,

Alam²,

Beg³

2018

EAI Endorsed Transactions on Smart Cities

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Electric, plug-in electric and plug-in hybrid electric vehicles (xEVs) are receiving a global attention from automotive industries, vehicle vendors, R&D organizations, power sectors and policymakers in the intelligent transportation era. Penetration of xEV fleet into the contemporary charging infrastructure(s) in the absence of robust integration network imbalances the power grid and potentially jeopardize the execution of emerging distributed generation systems. However, smart grid technologies in collaboration with smart charging management strategies can circumvent such operational disparities, thus enabling a reliable, efficient, consistent and optimal electric energy management in the power system. This work employs the notion of Cloud of Things (CoT) to propose a comprehensive cloud aware Transport Oriented Smart City (TOSC) framework intended to provide intelligent solutions to the contemporary transportation infrastructures in the emerging sustainable smart cities. The proposed work also demonstrates a commercially viable vehicle to cloud (V2C) fleet charging framework for charging management of xEVs through micro grids/ smart grid. The unprecedented data breeding across V2C, cloud to grid (C2G) and grid to vehicle (G2V) bidirectional communication interfaces elucidates the need for computationally efficient analytics. A state-of-the-art Big-Data to Knowledge (B2K) workflow structure is thus proposed for translating the generated data into efficient knowledge for noble decisions and inferences. Finally, the substantial Mobility as a service (MaaS) adoption challenges and data science prospects are outlined along with the emerging technologies that can co-work with the proposed framework to ensure commercial viability and optimal implementation in emerging TOSCs.

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Toward Social Internet of Vehicles: Concept, Architecture, and Applications

Cited by 347 publications

References 33 publications

A Survey on Machine Learning‐Based Mobile Big Data Analysis: Challenges and Applications

A Survey on Machine Learning‐Based Mobile Big Data Analysis: Challenges and Applications

Social Internet of Vehicles for Smart Cities

Federated Cloud Analytics Frameworks in Next Generation Transport Oriented Smart Cities (TOSCs) - Applications, Challenges and Future Directions

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