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Road Anomaly Detection Through Deep Learning Approaches [PDF]
IEEE Access, 2020 This paper addresses road anomaly detection by formulating it as a classification problem and applying deep learning approaches to solve it. Besides conventional road anomalies, additional ones are introduced from the perspective of a vehicle.
Dawei Luo, Jianbo Lu, Gang Guo
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QDetect: Time Series Querying Based Road Anomaly Detection [PDF]
IEEE Access, 2020 Road anomaly detection has attracting increasing attention in recent years due to its significant role in the public transportation of modern cities. A few methods has been proposed to detect road anomaly with inertial sensors (e.g., accelerometer and ...
Zengwei Zheng +4 more
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Road Traffic Anomaly Detection by Human-Attention-Assisted Text–Vision Learning [PDF]
SensorsWith the rapid development of society, the number of road vehicles has increased significantly, leading to a growing severity of traffic accident issues.
Yachuang Chai, Wushouer Silamu
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Toward Practical Crowdsourcing-Based Road Anomaly Detection With Scale-Invariant Feature
IEEE Access, 2019 Road anomaly detection with crowdsourced sensor data has become an increasingly important field of research over the last few years. Traditional ways for road anomaly detection are either threshold-based detection techniques or feature-based detection ...
Yuanyi Chen +3 more
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Spatiotemporal Road Traffic Anomaly Detection: A Tensor-Based Approach
Applied Sciences, 2021 The increased development of urban areas results in a larger number of vehicles on the road network, leading to traffic congestion, which often leads to potentially dangerous situations that can be described as anomalies. The tensor-based methods emerged
Leo Tišljarić +3 more
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TinyML-enabled fuzzy logic for enhanced road anomaly detection in remote sensing [PDF]
Scientific ReportsAdvanced techniques for detecting and classifying road anomalies are crucial due to road networks’ rapid expansion and increasing complexity. This study introduces a novel integration of Tiny Machine Learning (TinyML), remote sensing, and fuzzy logic ...
Amna Khatoon +4 more
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Dynamic Road Anomaly Detection: Harnessing Smartphone Accelerometer Data with Incremental Concept Drift Detection and Classification [PDF]
SensorsEffective monitoring of road conditions is crucial for ensuring safe and efficient transportation systems. By leveraging the power of crowd-sourced smartphone sensor data, road condition monitoring can be conducted in real-time, providing valuable ...
Imen Ferjani, Suleiman Ali Alsaif
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Enabling real-time road anomaly detection via mobile edge computing
International Journal of Distributed Sensor Networks, 2019 To discover road anomalies, a large number of detection methods have been proposed. Most of them apply classification techniques by extracting time and frequency features from the acceleration data. Existing methods are time-consuming since these methods
Zengwei Zheng +4 more
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Anomaly detection in urban lighting systems using autoencoder and transformer algorithms [PDF]
Scientific ReportsThe study aims to present the effectiveness of anomaly detection algorithms in lighting systems based on analyzing records from electricity meters. The road lighting management system operates continuously and in real-time, requiring online anomaly ...
Tomasz Śmiałkowski, Andrzej Czyżewski
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Applied Sciences, 2022 Road surfaces suffer from sources of deterioration, such as weather conditions, constant usage, loads, and the age of the infrastructure. These sources of decay generate anomalies that could cause harm to vehicle users and pedestrians and also develop a ...
Erick Axel Martinez-Ríos +2 more
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