The Collaborative Internet of Things (C-IoT) is an emerging paradigm that involves many communities with the idea of cooperating in data gathering and service sharing. Many fields of application, such as Smart Cities and environmental monitoring, use the concept of crowdsensing in order to produce the amount of data that such IoT scenarios need in order to be pervasive. In our paper we introduce an architecture, namely SenSquare, able to handle both the heterogeneous data sources coming from open IoT platform and crowdsensing campaigns, and display a unified access to users. We inspect all the facets of such a complex system, spanning over issues of different nature: we deal with heterogeneous data classification, Mobile Crowdsensing (MCS) management for environmental data, information representation and unification, IoT service composition and deployment. We detail our proposed solution in dealing with such tasks and present possible methods for meeting open challenges. Finally, we demonstrate the capabilities of SenSquare through both a mobile and a desktop client.
Federico Montori, L.B. (2018). A Collaborative Internet of Things Architecture for Smart Cities and Environmental Monitoring. IEEE INTERNET OF THINGS JOURNAL, 5(2), 592-605 [10.1109/JIOT.2017.2720855].
A Collaborative Internet of Things Architecture for Smart Cities and Environmental Monitoring
Federico Montori
;Luca Bedogni;Luciano Bononi
2018
Abstract
The Collaborative Internet of Things (C-IoT) is an emerging paradigm that involves many communities with the idea of cooperating in data gathering and service sharing. Many fields of application, such as Smart Cities and environmental monitoring, use the concept of crowdsensing in order to produce the amount of data that such IoT scenarios need in order to be pervasive. In our paper we introduce an architecture, namely SenSquare, able to handle both the heterogeneous data sources coming from open IoT platform and crowdsensing campaigns, and display a unified access to users. We inspect all the facets of such a complex system, spanning over issues of different nature: we deal with heterogeneous data classification, Mobile Crowdsensing (MCS) management for environmental data, information representation and unification, IoT service composition and deployment. We detail our proposed solution in dealing with such tasks and present possible methods for meeting open challenges. Finally, we demonstrate the capabilities of SenSquare through both a mobile and a desktop client.File | Dimensione | Formato | |
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