Distributed Road Surface Condition Monitoring Using Mobile Phones
作者： Mikko Perttunen , Oleksiy Mazhelis , Fengyu Cong , Mikko Kauppila , Teemu Leppänen
DOI: 10.1007/978-3-642-23641-9_8
关键词: Support vector machine 、 Anomaly detection 、 Global Positioning System 、 Computer science 、 Preprocessor 、 Condition monitoring 、 Road surface 、 Accelerometer 、 Feature extraction 、 Computer vision 、 Artificial intelligence
摘要: The objective of this research is to improve traffic safety through collecting and distributing up-to-date road surface condition information using mobile phones. Road seen useful for both travellers the network maintenance. problem we consider detect anomalies that, when left unreported, can cause wear vehicles, lesser driving comfort vehicle controllability, or an accident. In work developed a pattern recognition system detecting from accelerometer GPS readings. We present experimental results real urban data that demonstrate usefulness system. Our contributions are: 1) Performing throughout spectral analysis tri-axis acceleration signals in order get reliable anomaly labels. 2) Comprehensive preprocessing signals. 3) Proposing speed dependence removal approach feature extraction demonstrating its positive effect multiple sets detection task. 4) A framework visually analyzing classifier predictions over validation
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