Modern smartphones integrate multiple functionalities into a single device: they can establish peer-to-peer wireless links, they can sense the environment through several embedded sensors, they are provided with a multi-core CPU. Hence, they can play a crucial role on emergency scenarios, where there is need of acquiring data from the environment, processing, and quickly conveying them to the people involved. In this paper, we describe how to turn a group of dense and heterogeneous smartphones into a phone-sensing platform, through the SENSE-ME software. This latter integrates three layers: (i) a network layer, that allows the creation of a spontaneous device-to-device communication structure; (ii) a sensing layer, that allows retrieving local and remote sensing data; (iii) a decision layer, that allows mining the sensed data, in order to extract context-aware information and -based on them-infer decisions about proper actions to take. In the following, we describe the SENSE-ME architecture and some enabling technologies at each layer. Moreover, we discuss the open challenges that must be addressed for the complete system deployment.

A mobile phone-sensing system for emergency management: The SENSE-ME platform

DI FELICE, MARCO;
2016

Abstract

Modern smartphones integrate multiple functionalities into a single device: they can establish peer-to-peer wireless links, they can sense the environment through several embedded sensors, they are provided with a multi-core CPU. Hence, they can play a crucial role on emergency scenarios, where there is need of acquiring data from the environment, processing, and quickly conveying them to the people involved. In this paper, we describe how to turn a group of dense and heterogeneous smartphones into a phone-sensing platform, through the SENSE-ME software. This latter integrates three layers: (i) a network layer, that allows the creation of a spontaneous device-to-device communication structure; (ii) a sensing layer, that allows retrieving local and remote sensing data; (iii) a decision layer, that allows mining the sensed data, in order to extract context-aware information and -based on them-infer decisions about proper actions to take. In the following, we describe the SENSE-ME architecture and some enabling technologies at each layer. Moreover, we discuss the open challenges that must be addressed for the complete system deployment.
2016
Proceedings of the 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI)
1
6
Aloi, G.; Di Felice, M.; Ruggeri, G.; Savazzi, S.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/599857
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