<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>33985</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>21800</pageFirst>
    <pageLast>21800</pageLast>
    <pageNumber>1</pageNumber>
    <edition/>
    <issue>14</issue>
    <volume>24</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-09-05</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Guest editorial special issue on smartness and robustness of spatial environment perception in automated systems</title>
    <abstract language="eng">As the curtains close on this special issue dedicated to advanced sensor research, we reflect on the critical role sensor technology plays in the future of automation. Throughout this issue, we have explored significant advancements and ongoing challenges in developing intelligent, resilient automated systems. A key theme is the vital need for smarter, more robust sensing systems. Modern sensors, now more adaptable, adjust their operations based on external changes, crucial for maximizing automation in varied real-world situations. Efforts to enhance sensor robustness have produced improvements in performance in extreme conditions, cybersecurity, cost-effective solutions, and flexible system requirements while preserving performance. The addition of self-monitoring and calibration features allows for continuous refinement of sensor accuracy and rapid problem detection, boosting system reliability. The capacity for seamlessly integrating alternative technologies when specific sensors fail further strengthens system resilience. This issue includes 33 manuscripts selected from 65 submissions, exploring these diverse aspects.</abstract>
    <parentTitle language="eng">IEEE Sensors Journal</parentTitle>
    <identifier type="issn">1558-1748</identifier>
    <identifier type="doi">10.1109/JSEN.2024.3409137</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Tai</firstName>
      <lastName>Fei</lastName>
    </author>
    <submitter>
      <firstName>Madlen</firstName>
      <lastName>Herzig</lastName>
    </submitter>
    <author>
      <firstName>Subhas</firstName>
      <lastName>Mukhopadhyay</lastName>
    </author>
    <author>
      <firstName>João Paulo Javidi</firstName>
      <lastName>Da Costa</lastName>
    </author>
    <author>
      <firstName>Markus</firstName>
      <lastName>Gardill</lastName>
    </author>
    <author>
      <firstName>Shengheng</firstName>
      <lastName>Liu</lastName>
    </author>
    <author>
      <firstName>Chirasree</firstName>
      <lastName>Roychaudhuri</lastName>
    </author>
    <author>
      <firstName>Lan</firstName>
      <lastName>Lan</lastName>
    </author>
    <author>
      <firstName>Nevine</firstName>
      <lastName>Demitri</lastName>
    </author>
    <collection role="institutes" number="1101">FG Elektronische Systeme und Sensorik</collection>
  </doc>
</export-example>
