基于Android智能手机传感器估算路面粗糙度的简单模型

Viengnam Douangphachanh, H. Oneyama
{"title":"基于Android智能手机传感器估算路面粗糙度的简单模型","authors":"Viengnam Douangphachanh, H. Oneyama","doi":"10.1109/ISSNIP.2014.6827694","DOIUrl":null,"url":null,"abstract":"It is increasingly common to find many useful sensors on today's smartphones. Beside the use in the smartphones' user interface and features, many researchers and developers have also adopted the sensors for use in numerous applications in several fields and purposes. In this study, a simple model has been formulated to estimate road surface roughness condition from Android smartphone sensor data. The goal is to explore the use of smartphones, as a low cost and easy to implement approach, in the field of road maintenance management and continuous monitoring. The formulation of the model is based on an experiment and frequency domain analysis, in which it has been found that the sensor data, such as 3 axis acceleration and speed, has a linear relationship with road surface roughness condition. In our preliminary simulations on example road network with various settings, we have found that the performance and results of the model are very encouraging.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Formulation of a simple model to estimate road surface roughness condition from Android smartphone sensors\",\"authors\":\"Viengnam Douangphachanh, H. Oneyama\",\"doi\":\"10.1109/ISSNIP.2014.6827694\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is increasingly common to find many useful sensors on today's smartphones. Beside the use in the smartphones' user interface and features, many researchers and developers have also adopted the sensors for use in numerous applications in several fields and purposes. In this study, a simple model has been formulated to estimate road surface roughness condition from Android smartphone sensor data. The goal is to explore the use of smartphones, as a low cost and easy to implement approach, in the field of road maintenance management and continuous monitoring. The formulation of the model is based on an experiment and frequency domain analysis, in which it has been found that the sensor data, such as 3 axis acceleration and speed, has a linear relationship with road surface roughness condition. In our preliminary simulations on example road network with various settings, we have found that the performance and results of the model are very encouraging.\",\"PeriodicalId\":269784,\"journal\":{\"name\":\"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSNIP.2014.6827694\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSNIP.2014.6827694","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

摘要

在今天的智能手机上发现许多有用的传感器越来越普遍。除了在智能手机的用户界面和功能中使用外,许多研究人员和开发人员还将传感器用于多个领域和目的的众多应用中。在本研究中,我们建立了一个简单的模型,利用Android智能手机传感器数据来估计路面粗糙度状况。目标是探索使用智能手机,作为一种低成本和易于实施的方法,在道路养护管理和持续监控领域。该模型的建立基于实验和频域分析,其中发现传感器数据,如3轴加速度和速度,与路面粗糙度状况呈线性关系。在我们对不同设置的道路网络的初步仿真中,我们发现模型的性能和结果是非常令人鼓舞的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Formulation of a simple model to estimate road surface roughness condition from Android smartphone sensors
It is increasingly common to find many useful sensors on today's smartphones. Beside the use in the smartphones' user interface and features, many researchers and developers have also adopted the sensors for use in numerous applications in several fields and purposes. In this study, a simple model has been formulated to estimate road surface roughness condition from Android smartphone sensor data. The goal is to explore the use of smartphones, as a low cost and easy to implement approach, in the field of road maintenance management and continuous monitoring. The formulation of the model is based on an experiment and frequency domain analysis, in which it has been found that the sensor data, such as 3 axis acceleration and speed, has a linear relationship with road surface roughness condition. In our preliminary simulations on example road network with various settings, we have found that the performance and results of the model are very encouraging.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Wireless sensors networks for Internet of Things Efficient sequential-hierarchical deployment strategy for heterogeneous sensor networks Development of silicon photonics dual disks resonators as chemical sensors An efficient power control scheme for a 2.4GHz class-E PA in 0.13-μm CMOS Action recognition from motion capture data using Meta-Cognitive RBF Network classifier
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1