{"title":"众包和移动设备用于广域监测","authors":"A. Guerriero, F. Giuliani, D. Nitti","doi":"10.1109/EESMS.2015.7175847","DOIUrl":null,"url":null,"abstract":"This paper presents the architecture of an extended area monitoring system based on crowdsourcing and mobile devices. In particular areas (as very large historical sites) it can be difficult or impossible to install fixed cameras due to the huge number of candidate points of interest (POI) to monitoring or to the significant impact on site (i.e. cameras or other sensors could be too invasive towards historic walls or ancient materials). For these sites we propose a system based on a distribute architecture, a server that runs change detection algorithms and clients that run on visitors' smartphones and assists the acquisition of new pictures comparable to reference photos of the monitored areas. Server contains geo-referenced images of the POI and can automatically add new images of the same POI under partly different observation conditions (like angle of view or light or shadows distribution). The client section, the app on the mobile devices, shows all the POI in the neighboring area of the user, provides a map to reach a selected POI, compares in real time the reference photo of the POI provided by the server with the live view of the smartphone camera and supplies the user directions to obtain the correct overlap of the images.","PeriodicalId":346259,"journal":{"name":"2015 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS) Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Crowdsourcing and mobile device for wide areas monitoring\",\"authors\":\"A. Guerriero, F. Giuliani, D. Nitti\",\"doi\":\"10.1109/EESMS.2015.7175847\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the architecture of an extended area monitoring system based on crowdsourcing and mobile devices. In particular areas (as very large historical sites) it can be difficult or impossible to install fixed cameras due to the huge number of candidate points of interest (POI) to monitoring or to the significant impact on site (i.e. cameras or other sensors could be too invasive towards historic walls or ancient materials). For these sites we propose a system based on a distribute architecture, a server that runs change detection algorithms and clients that run on visitors' smartphones and assists the acquisition of new pictures comparable to reference photos of the monitored areas. Server contains geo-referenced images of the POI and can automatically add new images of the same POI under partly different observation conditions (like angle of view or light or shadows distribution). The client section, the app on the mobile devices, shows all the POI in the neighboring area of the user, provides a map to reach a selected POI, compares in real time the reference photo of the POI provided by the server with the live view of the smartphone camera and supplies the user directions to obtain the correct overlap of the images.\",\"PeriodicalId\":346259,\"journal\":{\"name\":\"2015 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS) Proceedings\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS) Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EESMS.2015.7175847\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EESMS.2015.7175847","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Crowdsourcing and mobile device for wide areas monitoring
This paper presents the architecture of an extended area monitoring system based on crowdsourcing and mobile devices. In particular areas (as very large historical sites) it can be difficult or impossible to install fixed cameras due to the huge number of candidate points of interest (POI) to monitoring or to the significant impact on site (i.e. cameras or other sensors could be too invasive towards historic walls or ancient materials). For these sites we propose a system based on a distribute architecture, a server that runs change detection algorithms and clients that run on visitors' smartphones and assists the acquisition of new pictures comparable to reference photos of the monitored areas. Server contains geo-referenced images of the POI and can automatically add new images of the same POI under partly different observation conditions (like angle of view or light or shadows distribution). The client section, the app on the mobile devices, shows all the POI in the neighboring area of the user, provides a map to reach a selected POI, compares in real time the reference photo of the POI provided by the server with the live view of the smartphone camera and supplies the user directions to obtain the correct overlap of the images.