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      A Wireless Sensor Network for the Real-Time Remote Measurement of Aeolian Sand Transport on Sandy Beaches and Dunes

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          Abstract

          Direct measurements of aeolian sand transport on coastal dunes and beaches is of paramount importance to make correct decisions about coast management. As most of the existing studies are mainly based on a statistical approach, the solution presented in this paper proposes a sensing structure able to orient itself according to wind direction and directly calculate the amount of wind-transported sand by collecting it and by measuring its weight. Measurements are performed remotely without requiring human action because the structure is equipped with a ZigBee radio module, which periodically sends readings to a local gateway. Here data are processed by a microcontroller and then transferred to a remote data collection centre, through GSM technology. The ease of installation, the reduced power consumption and the low maintenance required, make the proposed solution able to work independently, limiting human intervention, for all the duration of the expected experimental campaign. In order to analyze the cause-effect relationship between the transported sand and the wind, the sensing structure is integrated with a multi-layer anemoscope-anemometer structure. The overall sensor network has been developed and tested in the laboratory, and its operation has been validated in field through a 48 h measurement campaign.

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          Wireless sensor networks: a survey

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            Rates of erosion and sediment evacuation by glaciers: A review of field data and their implications

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              Shoreline Definition and Detection: A Review

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                08 March 2018
                March 2018
                : 18
                : 3
                : 820
                Affiliations
                [1 ]Department of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy; irene.cappelli@ 123456student.unisi.it (I.C.); alessandro.mecocci@ 123456unisi.it (A.M.)
                [2 ]Department of Earth Sciences, University of Pisa, 56126 Pisa, Italy; duccio.bertoni@ 123456unipi.it (D.B.); giovanni.sarti@ 123456unipi.it (G.S.)
                [3 ]Department of Architecture and Urbanism, Faculty of Uniasselvi Group FAMEG, Guaramirim 89270-000, Brazil; alquini@ 123456gmail.com
                Author notes
                [* ]Correspondence: alessandro.pozzebon@ 123456unisi.it ; Tel.: +39-349-424-5468
                Author information
                https://orcid.org/0000-0003-3991-8858
                https://orcid.org/0000-0003-4323-2437
                https://orcid.org/0000-0002-6327-4768
                Article
                sensors-18-00820
                10.3390/s18030820
                5877124
                29518060
                c2908f89-a587-49aa-b9b0-ed0f72a716b9
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 25 January 2018
                : 28 February 2018
                Categories
                Article

                Biomedical engineering
                wsn,zigbee,sand transport,load cell,iot,wind dynamics,coastal dynamics,environmental monitoring

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