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High-quality meets ...
High-quality meets low-cost : Approaches for hybrid-mobility sensor networks
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- Winkler, Nicolas P., 1991- (författare)
- Örebro universitet,Institutionen för naturvetenskap och teknik,Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany,AASS Research Centre
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- Neumann, Patrick P. (författare)
- Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany
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- Säämänen, Arto (författare)
- Occupational Safety, Finnish Institute of Occupational Health, Tampere, Finland
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- Schaffernicht, Erik, 1980- (författare)
- Örebro universitet,Institutionen för naturvetenskap och teknik,AASS Research Centre
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- Lilienthal, Achim J., 1970- (författare)
- Örebro universitet,Institutionen för naturvetenskap och teknik,AASS Research Centre
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(creator_code:org_t)
- Elsevier, 2020
- 2020
- Engelska.
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Ingår i: MATERIALS TODAY-PROCEEDINGS. - : Elsevier. ; , s. 250-253
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Air pollution within industrial scenarios is a major risk for workers, which is why detailed knowledge about the dispersion of dusts and gases is necessary. This paper introduces a system combining stationary low-cost and high-quality sensors, carried by ground robots and unmanned aerial vehicles. Based on these dense sampling capabilities, detailed distribution maps of dusts and gases will be created. This system enables various research opportunities, especially on the fields of distribution mapping and sensor planning. Standard approaches for distribution mapping can be enhanced with knowledge about the environment's characteristics, while the effectiveness of new approaches, utilizing neural networks, can be further investigated. The influence of different sensor network setups on the predictive quality of distribution algorithms will be researched and metrics for the quantification of a sensor network's quality will be investigated.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Mobile robot olfaction
- Air quality monitoring
- Wireless sensor network
- Gas distribution mapping
- Occupational health
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)