Working Principle and Performance of a Scalable Gravimetric System for the Monitoring of Access to Public Places.

access monitoring access security gravimetric platform gravimetric sensor gravimetric system

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
17 Dec 2020
Historique:
received: 13 11 2020
revised: 11 12 2020
accepted: 15 12 2020
entrez: 22 12 2020
pubmed: 23 12 2020
medline: 23 12 2020
Statut: epublish

Résumé

Here, we propose a novel application of a low-cost robust gravimetric system for public place access monitoring purposes. The proposed solution is intended to be exploited in a multi-sensor scenario, where heterogeneous information, coming from different sources (e.g., metal detectors and surveillance cameras), are collected in a central data fusion unit to obtain a more detailed and accurate evaluation of notable events. Specifically, the word "notable" refers essentially to two event categories: the first category is represented by irregular events, corresponding typically to multiple people passing together through a security gate; the second category includes some event subsets, whose notification can be interesting for assistance provision (in the case of people with disabilities), or for statistical analysis. The employed gravimetric sensor, compared to other devices existing in the literature, exhibits a simple scalable robust structure, made up of an array of rigid steel plates, each laid on four load cells. We developed a tailored hardware and software to individually acquire the load cell signals, and to post-process the data to formulate a classification of the notable events. The results are encouraging, showing a remarkable detectability of irregularities (95.3% of all the test cases) and a satisfactory identification of the other event types.

Identifiants

pubmed: 33348623
pii: s20247225
doi: 10.3390/s20247225
pmc: PMC7767313
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

Sensors (Basel). 2020 Oct 26;20(21):
pubmed: 33114594
Nat Commun. 2020 Sep 14;11(1):4609
pubmed: 32929087
Sensors (Basel). 2017 Apr 23;17(4):
pubmed: 28441748
Sensors (Basel). 2019 Sep 23;19(19):
pubmed: 31547624
Med Biol Eng Comput. 2017 Apr;55(4):685-695
pubmed: 27435068
ACS Appl Mater Interfaces. 2017 Aug 9;9(31):26126-26133
pubmed: 28707896

Auteurs

Tommaso Addabbo (T)

Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy.

Ada Fort (A)

Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy.

Matteo Intravaia (M)

Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy.

Marco Mugnaini (M)

Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy.

Marco Tani (M)

Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy.

Valerio Vignoli (V)

Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy.

Stefano De Muro (S)

Rete Ferroviaria Italiana S.p.A. Direzione Protezione Aziendale, Piazza della Croce Rossa 1, 00161 Roma, Italy.

Marco Tesei (M)

Rete Ferroviaria Italiana S.p.A. Direzione Protezione Aziendale, Piazza della Croce Rossa 1, 00161 Roma, Italy.

Classifications MeSH