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

Crowdsourcing and mobile device for wide areas monitoring

GUERRIERO, Andrea;
2015

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
IEEE Workshop on Environmental, Energy and Structural Monitoring Systems, EESMS 2015
978-1-4799-8214-1
978-1-4799-8215-8
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11589/18260
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