L. C. Lima, V. J. Amorim, I. M. Pereira, Filipe Nunes Ribeiro, Ricardo A. O. Oliveira
{"title":"使用众包技术和移动设备进行沥青路面质量识别","authors":"L. C. Lima, V. J. Amorim, I. M. Pereira, Filipe Nunes Ribeiro, Ricardo A. O. Oliveira","doi":"10.1109/SBESC.2016.029","DOIUrl":null,"url":null,"abstract":"Currently, many developing countries based their transportation infrastructure on roads. These roads qualities have a significant influence on how fast products are delivered and how much it costs. Due to the lack of low-cost solutions or negligence, roadways pavement quality inspections are usually set aside or hardly performed at some places. This fact leads to higher casualties rates, driving discomfort, vehicle damage, and money prejudice. A cheap and accurate way to solve this problem is the use of typical smartphones with accelerometers and GPS sensors to measure the impact inflicted on the car when driving over a poor quality road surface. This scrutiny helps to raise data that can be used by road maintenance staff. Most current systems tend to translate its output to an international standard called IRI (International Roughness Index) but, this practice demands high computer processing. Here is presented \"RoadScan\", a crowdsourcing Android application that determines pavements quality in a simple and lightweight way. Our approach allows the mobile device to be placed at any position in the car. Considered tests and results are promising, identifying in most cases road regions that have some deformity.","PeriodicalId":336703,"journal":{"name":"2016 VI Brazilian Symposium on Computing Systems Engineering (SBESC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Using Crowdsourcing Techniques and Mobile Devices for Asphaltic Pavement Quality Recognition\",\"authors\":\"L. C. Lima, V. J. Amorim, I. M. Pereira, Filipe Nunes Ribeiro, Ricardo A. O. Oliveira\",\"doi\":\"10.1109/SBESC.2016.029\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Currently, many developing countries based their transportation infrastructure on roads. These roads qualities have a significant influence on how fast products are delivered and how much it costs. Due to the lack of low-cost solutions or negligence, roadways pavement quality inspections are usually set aside or hardly performed at some places. This fact leads to higher casualties rates, driving discomfort, vehicle damage, and money prejudice. A cheap and accurate way to solve this problem is the use of typical smartphones with accelerometers and GPS sensors to measure the impact inflicted on the car when driving over a poor quality road surface. This scrutiny helps to raise data that can be used by road maintenance staff. Most current systems tend to translate its output to an international standard called IRI (International Roughness Index) but, this practice demands high computer processing. Here is presented \\\"RoadScan\\\", a crowdsourcing Android application that determines pavements quality in a simple and lightweight way. Our approach allows the mobile device to be placed at any position in the car. Considered tests and results are promising, identifying in most cases road regions that have some deformity.\",\"PeriodicalId\":336703,\"journal\":{\"name\":\"2016 VI Brazilian Symposium on Computing Systems Engineering (SBESC)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 VI Brazilian Symposium on Computing Systems Engineering (SBESC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SBESC.2016.029\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 VI Brazilian Symposium on Computing Systems Engineering (SBESC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SBESC.2016.029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Crowdsourcing Techniques and Mobile Devices for Asphaltic Pavement Quality Recognition
Currently, many developing countries based their transportation infrastructure on roads. These roads qualities have a significant influence on how fast products are delivered and how much it costs. Due to the lack of low-cost solutions or negligence, roadways pavement quality inspections are usually set aside or hardly performed at some places. This fact leads to higher casualties rates, driving discomfort, vehicle damage, and money prejudice. A cheap and accurate way to solve this problem is the use of typical smartphones with accelerometers and GPS sensors to measure the impact inflicted on the car when driving over a poor quality road surface. This scrutiny helps to raise data that can be used by road maintenance staff. Most current systems tend to translate its output to an international standard called IRI (International Roughness Index) but, this practice demands high computer processing. Here is presented "RoadScan", a crowdsourcing Android application that determines pavements quality in a simple and lightweight way. Our approach allows the mobile device to be placed at any position in the car. Considered tests and results are promising, identifying in most cases road regions that have some deformity.