Cited by 59Human-Automation Interaction and SafetyImage and Video Quality AssessmentAutonomous Vehicle Technology and Safety

Modeling Quality of IoT Experience in Autonomous Vehicles

Minovski, Dimitar, Ahlund, Christer, Mitra, Karan·2020·IEEE Internet of Things Journal

Abstract

Today's research on Quality of Experience (QoE) mainly addresses multimedia services. With the introduction of the Internet of Things (IoT), there is a need for new ways of evaluating the QoE. Emerging IoT services, such as autonomous vehicles (AVs), are more complex and involve additional quality requirements, such as those related to machine-to-machine communication that enables self-driving. In fully autonomous cases, it is the intelligent machines operating the vehicles. Thus, it is not clear how intelligent machines will impact end-user QoE, but also how end users can alter and affect a self-driving vehicle. This article argues for a paradigm shift in the QoE area to cover the relationship between humans and intelligent machines. We introduce the term Quality of IoT-experience (QoIoT) within the context of AV, where the quality evaluation, besides end users, considers quantifying the perspectives of intelligent machines with objective metrics. Hence, we propose a novel architecture that considers Quality of Data (QoD), Quality of Network (QoN), and Quality of Context (QoC) to determine the overall QoIoT in the context of AVs. Finally, we present a case study to illustrate the use of QoIoT.

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Crossref · 10.1109/jiot.2020.2975418

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93 of 93 references verified0 citation errors · 0 not checkable

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  • Machine performance is measured in terms of decision-making, reasoning, and optimized machine operations.

    “Machine performance is measured in terms of decision-making, reasoning, and optimized machine operations.”

    From QoE in IoT: a vision, survey and future directions (2021) · cites this paper as [19]

  • QoME measures machine performance objectively.

    “QoME measures machine performance objectively.”

    From QoE in IoT: a vision, survey and future directions (2021) · cites this paper as [19]

  • In the existing literature on IoT, only one reference [19] looks to define and evaluate the quality of IoT applications.

    “In the existing literature on IoT, we found only one reference which looks to define and evaluate the quality of IoT applications [19].”

    From QoE in IoT: a vision, survey and future directions (2021) · cites this paper as [19]

  • In an IoT ecosystem, there is a need to consider device-to-device interactions that can impact the quality of the application and hence the need for more objective measures to assess QoE.

    “However, as mentioned above, in an IoT ecosystem, there is a need to consider device to device interactions that can impact the quality of the application and hence the need for more objective measures to assess QoE [19,22].”

    From QoE in IoT: a vision, survey and future directions (2021) · cites this paper as [19]

  • QoE considers only the end-user's objective and subjective experience but does not measure the overall machine performance.

    “QoE considers only the end-user's objective and subjective experience but does not measure the overall machine performance.”

    From QoE in IoT: a vision, survey and future directions (2021) · cites this paper as [19]

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Authors
Minovski, D., Ahlund, C., & Mitra, K.
Affiliations
Luleå University of Technology (SE)
Venue
IEEE Internet of Things Journal
Published
2020-05
Volume
7
Issue
5
Pages
3833-3849
ISSN
  • 2327-4662 (ISSN-L)
  • 2372-2541
OpenAlex
W3008326113
Cited by
59
References
95
Citations by year
2026: 3 · 2025: 11 · 2024: 6 · 2023: 3 · 2022: 16 · 2021: 14 · 2020: 6
FWCI
10.66
Type
journal article
Language
en
Open access
closed
Locations
IEEE Internet of Things Journal (publishedVersion)
Topics
  • Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
  • Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
Keywords
autonomous vehicles, quality of experience, human-machine interaction, machine-to-machine communication, data quality, quality of context

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