J. Ferreira, V. Monteiro, J. Afonso, A. Martins, J. Afonso
{"title":"Mobile device sensing system for urban goods distribution logistics","authors":"J. Ferreira, V. Monteiro, J. Afonso, A. Martins, J. Afonso","doi":"10.1109/SOLI.2017.8120992","DOIUrl":null,"url":null,"abstract":"This paper presents a low cost mobile application (app) integrated on an Internet of Things (IoT) ecosystem, which uses varied sensor information collected by mobile devices to track and assist on the logistics of urban goods distribution processes. The proposed approach is leveraged by the trend of decreasing costs for mobile data communication in urban environments. Taking into account basic sensor data available in mobile devices (e.g., GPS, accelerometer and magnetometer), it is possible to track the users' movements and adopted routes, identify transit times and driving styles, identify the quality of roads, and track the process of loading/unloading of urban goods. This data can also be analyzed through a data mining process to identify patterns, present driving advice and perform a resource optimization process.","PeriodicalId":190544,"journal":{"name":"2017 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOLI.2017.8120992","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents a low cost mobile application (app) integrated on an Internet of Things (IoT) ecosystem, which uses varied sensor information collected by mobile devices to track and assist on the logistics of urban goods distribution processes. The proposed approach is leveraged by the trend of decreasing costs for mobile data communication in urban environments. Taking into account basic sensor data available in mobile devices (e.g., GPS, accelerometer and magnetometer), it is possible to track the users' movements and adopted routes, identify transit times and driving styles, identify the quality of roads, and track the process of loading/unloading of urban goods. This data can also be analyzed through a data mining process to identify patterns, present driving advice and perform a resource optimization process.