Detection of Road Condition Defects Using Multiple Sensors and IoT Technology: A Review

A. Alrajhi; Kaushik Roy; Letu Qingge; James D Kribs

doi:10.1109/OJITS.2023.3237480

Detection of Road Condition Defects Using Multiple Sensors and IoT Technology: A Review

Research output: Contribution to journal › Review article › peer-review

31 Scopus citations

Abstract

The transportation efficiency and driving safety of road networks, which play an essential role in economic prosperity, are impacted significantly by damage and defects on the road surface. In current practice, it can take weeks or even months before related government departments repair such road conditions, mainly due to lack of awareness of any damage. This paper reviews the current status and limitation of a framework for sensors devices and assessment of road surface conditions. The review also incorporates the most relevant machine learning-based methods, challenges, and future trends to underpin large-scale deployment of road defects automation identification. It is expected that the technology can provide both qualitative and quantitative information about the road surface condition and thus enable timely maintenance to improve transportation efficiency and driving safety.

Original language	English
Pages (from-to)	372-392
Number of pages	21
Journal	IEEE Open Journal of Intelligent Transportation Systems
Volume	4
DOIs	https://doi.org/10.1109/OJITS.2023.3237480
State	Published - Jan 1 2023

Keywords

Internet of Things
machine learning
networked sensor
road surface condition
transportation

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10.1109/OJITS.2023.3237480

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title = "Detection of Road Condition Defects Using Multiple Sensors and IoT Technology: A Review",

abstract = "The transportation efficiency and driving safety of road networks, which play an essential role in economic prosperity, are impacted significantly by damage and defects on the road surface. In current practice, it can take weeks or even months before related government departments repair such road conditions, mainly due to lack of awareness of any damage. This paper reviews the current status and limitation of a framework for sensors devices and assessment of road surface conditions. The review also incorporates the most relevant machine learning-based methods, challenges, and future trends to underpin large-scale deployment of road defects automation identification. It is expected that the technology can provide both qualitative and quantitative information about the road surface condition and thus enable timely maintenance to improve transportation efficiency and driving safety.",

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AB - The transportation efficiency and driving safety of road networks, which play an essential role in economic prosperity, are impacted significantly by damage and defects on the road surface. In current practice, it can take weeks or even months before related government departments repair such road conditions, mainly due to lack of awareness of any damage. This paper reviews the current status and limitation of a framework for sensors devices and assessment of road surface conditions. The review also incorporates the most relevant machine learning-based methods, challenges, and future trends to underpin large-scale deployment of road defects automation identification. It is expected that the technology can provide both qualitative and quantitative information about the road surface condition and thus enable timely maintenance to improve transportation efficiency and driving safety.

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Detection of Road Condition Defects Using Multiple Sensors and IoT Technology: A Review

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