The emerging industrial relevance of vehicular sensor networks pushes towards their adoption for large-scale applications, from traffic routing and relief to environmental monitoring and distributed surveillance. With homeland security issues in mind, we have developed MobEyes, a fully distrib-uted opportunistic harvesting system for urban monitoring. In MobEyes, regular vehicles equipped with sensors collect and locally store monitoring data while moving on the streets. Sensors may gen-erate a sheer data amount, especially in the case of audio/video recording, thus making traditional reporting unfeasible. MobEyes originally adopts the guidelines of locally generating summaries of sensed data and of taking advantage of vehicle mobility and opportunistic one-hop communica-tions to pump summaries towards mobile collec-tors, with minimal overhead, reasonable complete-ness, and limited latency. To that purpose, it care-fully considers standard specifications to portably integrate with heterogeneous sensors, in particular by exploiting the Java Media Framework to inter-work with cameras, the JSR179 Location API to interface with heterogeneous localization systems, and the Java Communications API to access lower-layer environmental sensors.
P. Bellavista, M. Gerla, U. Lee, E. Magistretti (2007). Standard Integration of Sensing and Opportunistic Diffusion for Vehicular Sensor Networks Urban Monitoring: the MobEyes Architecture. NEW YORK : IEEE Press.
Standard Integration of Sensing and Opportunistic Diffusion for Vehicular Sensor Networks Urban Monitoring: the MobEyes Architecture
BELLAVISTA, PAOLO;MAGISTRETTI, EUGENIO
2007
Abstract
The emerging industrial relevance of vehicular sensor networks pushes towards their adoption for large-scale applications, from traffic routing and relief to environmental monitoring and distributed surveillance. With homeland security issues in mind, we have developed MobEyes, a fully distrib-uted opportunistic harvesting system for urban monitoring. In MobEyes, regular vehicles equipped with sensors collect and locally store monitoring data while moving on the streets. Sensors may gen-erate a sheer data amount, especially in the case of audio/video recording, thus making traditional reporting unfeasible. MobEyes originally adopts the guidelines of locally generating summaries of sensed data and of taking advantage of vehicle mobility and opportunistic one-hop communica-tions to pump summaries towards mobile collec-tors, with minimal overhead, reasonable complete-ness, and limited latency. To that purpose, it care-fully considers standard specifications to portably integrate with heterogeneous sensors, in particular by exploiting the Java Media Framework to inter-work with cameras, the JSR179 Location API to interface with heterogeneous localization systems, and the Java Communications API to access lower-layer environmental sensors.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.