<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>43597</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>8</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>2017</volume>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace>Zurich, Switzerland</publisherPlace>
    <creatingCorporation>Eidgenössische Materialprüfungsanstalt (EMPA)</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Humidity monitoring in concrete using Bluetooth Low Energy sensors</title>
    <abstract language="eng">The vulnerability of low quality concrete to changing weather conditions is well known. The constant exposure to temperature changes, biological activity, and humidity ends up in damage to buildings and structures which contain this material. It is therefore necessary to take preventive measures to control the extent of the damage done by weathering and possible penetration of adverse chemicals into structures which need public safety.&#13;
The Federal Institute for Materials Research and Testing (BAM), in cooperation with the small enterprise LinTech GmbH, is working on a project to monitor humidity changes in concrete by analyzing the changes in signal strength (RSSI) from Bluetooth Low Energy sensors. In this paper, we show results which demonstrate the influence of changing water content in concrete on the received RSSI. We observed that as water content in concrete decreases, the received RSSI improves. However, the damping effect is not linearly proportional to water content, rather exponentially proportional. This suggests that changes in the received signal strength are more easily observed when water content in concrete is higher. Finally, we reconstructed a RSSI distribution map using computed tomography.</abstract>
    <parentTitle language="eng">SMAR 2017</parentTitle>
    <identifier type="url">http://www.smar-conferences.org/smar/SMAR_2017_Proceedings/papers/153.pdf</identifier>
    <enrichment key="eventName">SMAR 2017</enrichment>
    <enrichment key="eventPlace">Zurich, Switzerland</enrichment>
    <enrichment key="eventStart">13.09.2017</enrichment>
    <enrichment key="eventEnd">15.09.2017</enrichment>
    <author>Filipe Jorge Santos Ferreira Adão</author>
    <author>Helmerich Rosemarie</author>
    <author>Voigt Gerrit</author>
    <author>Moldenhauer Laura</author>
    <author>Patrick P. Neumann</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Bluetooth Low Energy Computed Tomography</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>RSSI</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Concrete</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Water</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Monitoring</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Computed Tomography</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
  </doc>
</export-example>
