SynthesisSensors (Basel, Switzerland)2022
Road Condition Monitoring Using Smart Sensing and Artificial Intelligence: A Review.
Synthesis in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- LiDAR-Based Road Surface Damage Classification: A Survey.Sensors (Basel, Switzerland) · 2026Review
- A lightweight YOLO11n seg framework for real time surface crack detection with segmentation.Scientific reports · 2026Article
- Predicting Polymerase Chain Reaction Success: Integrating theCombinatorial chemistry & high throughput screening · 2026Article
- Deep Learning Meets InSAR for Infrastructure Monitoring: A Systematic Review of Models, Applications, and Challenges.Sensors (Basel, Switzerland) · 2025Review
- Automotive Radar Range Spectrum-Based Road Surface Classification by Using Machine Learning.Sensors (Basel, Switzerland) · 2025Article
- Vehicle-as-a-Sensor Approach for Urban Track Anomaly Detection.Sensors (Basel, Switzerland) · 2025Article
- Advanced deep learning framework for underwater object detection with multibeam forward-looking sonar.Structural health monitoring · 2025Article
- Image processing and artificial neural network based determination of surface mean texture depth on lab-controlled chip seal pavement samples.Scientific reports · 2024Article
- Sensors for Distributed Monitoring.Sensors (Basel, Switzerland) · 2024Article
- A Review of Vision-Based Pothole Detection Methods Using Computer Vision and Machine Learning.Sensors (Basel, Switzerland) · 2024Review
- Evaluation of data representation techniques for vibration based road surface condition classification.Scientific reports · 2024Article
- A Vibration-Based Methodology to Monitor Road Surface: A Process to Overcome the Speed Effect.Sensors (Basel, Switzerland) · 2024Article
- Sensor Fusion in Autonomous Vehicle with Traffic Surveillance Camera System: Detection, Localization, and AI Networking.Sensors (Basel, Switzerland) · 2023Article
- The Use of Terrestrial and Maritime Autonomous Vehicles in Nonintrusive Object Inspection.Sensors (Basel, Switzerland) · 2022Review
- Data Augmentation for Deep-Learning-Based Multiclass Structural Damage Detection Using Limited Information.Sensors (Basel, Switzerland) · 2022Article
- Dissecting Latency in 360° Video Camera Sensing Systems.Sensors (Basel, Switzerland) · 2022Article
- LiDAR-Based Structural Health Monitoring: Applications in Civil Infrastructure Systems.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Road condition monitoring (RCM) has been a demanding strategic research area in maintaining a large network of transport infrastructures. With advancements in computer vision and data mining techniques along with high computing resources, several innovative pavement distress evaluation systems have been developed in recent years. The majority of these technologies employ next-generation distributed sensors and vision-based artificial intelligence (AI) methodologies to evaluate, classify and localize pavement distresses using the measured data. This paper presents an exhaustive and systematic literature review of these technologies in RCM that have been published from 2017-2022 by utilizing next-generation sensors, including contact and noncontact measurements. The various methodologies and innovative contributions of the existing literature reviewed in this paper, together with their limitations, promise a futuristic insight for researchers and transport infrastructure owners. The decisive role played by smart sensors and data acquisition platforms, such as smartphones, drones, vehicles integrated with non-intrusive sensors, such as RGB, and thermal cameras, lasers and GPR sensors in the performance of the system are also highlighted. In addition to sensing, a discussion on the prevalent challenges in the development of AI technologies as well as potential areas for further exploration paves the way for an all-inclusive and well-directed futuristic research on RCM.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.