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Smart Cities have emerged as an efficient infrastructure to contribute to so-called global sensing or situation-awareness applications. One example of large scale deployment of sensors in the city is the SmartSantander test-bed. Most of the deployment so far propose traditional scalar physical measures such as temperature or luminosity for a number of environment-related applications. The EAR-IT project moves a step further and proposes large-scale "real-life" experimentations of intelligent acoustics for supporting high societal value applications. One scenario that will be demonstrated is an on-demand acoustic data streaming feature for surveillance systems and management of emergencies. In this paper, we will present experimentations on streaming encoded acoustic data on low-resources devices. We will highlight the main sources of delays assuming no flow control nor congestion control to determine the best case performance level and will demonstrate that streaming acoustic data can be realized in a multi-hop manner on the SmartSantander infrastructure.
Pham et al. (Thu,) studied this question.