返回
Road Anomalies Detection System Evaluation
DOI:10.3390/s18071984.png)
摘要
En 中文
Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper analyses the difference between the deployment of a road anomalies detection and identification system in a conditioned and a real world setup, where the system performed worse compared to the conditioned setup. It also presents a system performance analysis based on the analysis of the training data sets; on the analysis of the attributes complexity, through the application of PCA techniques; and on the analysis of the attributes in the context of each anomaly type, using acceleration standard deviation attributes to observe how different anomalies classes are distributed in the Cartesian coordinates system. Overall, in this paper, we describe the main insights on road anomalies detection challenges to support the design and deployment of a new iteration of our system towards the deployment of a road anomaly detection service to provide information about roads condition to drivers and government entities.
Keyword:
road anomalies
PCA
Fi-Ware
data-mining
collaborative mobile sensing
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.5
论文数:
7.2W
被引数:
20.9W
机构
引用论文
Room temperature synthesis of reduced graphene oxide nanosheets as anode material for supercapacitors室温合成还原氧化石墨烯纳米片作为超级电容器负极材料的研究

