Cited by 14Vehicular Ad Hoc Networks (VANETs)Transportation Systems and LogisticsTraffic control and management

The Evolution of Intelligent Transportation Systems: Analyzing the Differences and Similarities between IoV and IoFV

Open access
Herich, Dušan, Vaščák, Ján·2024·Drones

Abstract

The Internet of Vehicles (IoV) and the Internet of Flying Vehicles (IoFV) are integral components of intelligent transportation systems with the potential to revolutionize the way we move people and goods. Although both the IoV and IoFV share a common goal of improving transportation efficiency, safety, and sustainability, they possess distinct characteristics and face unique challenges. To date, the existing literature has predominantly focused on specific aspects of either the IoV or IoFV, but a comprehensive review comparing and contrasting the two domains is still lacking. This review paper aims to address this gap by providing an in-depth analysis of the key differences between the IoV and IoFV systems. The review will examine the technological components, network infrastructure, communication protocols, data management, objectives, applications, challenges, and future trends associated with both domains. Additionally, this paper will explore the potential impact of technologies such as artificial intelligence, machine learning, and blockchain. Ultimately, the paper aims to contribute to a deeper understanding of the implications and potential of these technologies, both in the context of transportation systems and beyond.

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  • Drones have evolved significantly in terms of flight capability, onboard technology, and cost, making their use for maintenance on electrical networks increasingly viable and important.

    “Drones have evolved significantly in terms of their flight capability, onboard technology, and cost, making their use for maintenance on electrical networks increasingly viable and important, which was the main motivator for carrying out this work [2].”

    From Multicriteria Methodology for Prioritizing Predictive Maintenance Using RPASs (Drones) with Thermal Cameras on Transmission Lines (2025) · cites this paper as [2]

    Section 8.2 (page not provided) describes camera-equipped drones as a cost-effective way to inspect warehouse structures, supporting the general point that drones can be useful for inspection. The cited paper does not connect changes in flight capability, onboard technology, or cost to maintenance of electrical networks; the searches for power-line and electrical-grid maintenance found no such discussion. (LLM, conf=0.82)

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Research works printed but not linked: 8

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  8. De Simone, C.; Ceci, F.; Alaimo, C. Data Ecosystem and Data Value Chain: An Exploration of Drones Technology Applications. In Sustainable Digital Transformation: Paving the Way Towards Smart Organizations and Societies; Springer: Berlin/Heidelberg, Germany, 2022; pp. 203-218. 178.

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Authors
Herich, D., & Vaščák, J.
Affiliations
Technical University of Košice (SK)
Corresponding author
  • Herich, Dušan
  • Vaščák, Ján
Venue
Drones
Publisher
MDPI AG
Published
2024-01-24
Volume
8
Issue
2
Pages
34
ISSN
2504-446X (ISSN-L)
OpenAlex
W4391168045
Cited by
14
References
198
Citations by year
2026: 5 · 2025: 6 · 2024: 3
FWCI
1.45
Type
journal article
Language
en
Open access
Locations
  • Drones (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
VEGA grant EDEN: EDge-Enabled intelligeNt systems (1/0480/22)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
  • Physical Sciences › Engineering › Civil and Structural Engineering › Transportation Systems and Logistics
  • Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
Keywords
Internet of Vehicles, intelligent transportation systems, unmanned aerial vehicles, UAV networks, vehicle-to-vehicle communication, communication protocols, data management, network infrastructure, artificial intelligence in transportation, machine learning, blockchain, transport safety, transport efficiency

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