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Environmental Monitoring for Smart Cities

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 01 Dec 2017 Italy Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Sensors Journal, volume 17, pages 7,767-7,774 (issn: 1530-437X, eissn: 2379-9153,

Authors: Bacco F M; Delmastro F; Ferro E; Gotta A;

doi: 10.1109/jsen.2017.2722819

arXiv: http://arxiv.org/abs/2205.15147

handle: 20.500.14243/335620

Environmental Monitoring for Smart Cities

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Abstract

This work presents an innovative, multidisciplinary and cost-effective ecosystem of ICT solutions able to collect, process and distribute geo-referenced information about the influence of pollution and micro-climatic conditions on the quality of life in Smart Cities. The system has been developed and experimentally evaluated in the framework of the research project SHE, co-funded by the Tuscany Region (Italy). Specifically, an innovative monitoring network has been developed, constituted by fixed and mobile sensor nodes, which provided comparable measurements in stationary and mobile conditions. In addition, sensor data have been enriched with those generated by citizens through the use of a dedicated mobile application, exploiting participatory sensing and MSN paradigms.

Country

Italy

Related Organizations

Keywords

Computer Science - Networking and Internet Architecture, Smart city, Mobile social networks, Mobile sensor networks, Participatory sensing, Environmental monitoring

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	74
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%