A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit <a rel="external noopener" href="http://eprints.pascal-network.org:80/archive/00010302/01/khan_buildsys2014.pdf">the original URL</a>. The file type is <code>application/pdf</code>.
Occupancy monitoring using environmental & context sensors and a hierarchical analysis framework
<span title="">2014</span>
<i title="ACM Press">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5j2fcrioqzharcoeonnjm7exwq" style="color: black;">Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings - BuildSys '14</a>
</i>
Preserved Fulltext
Saving energy in residential and commercial buildings is of great interest due to diminishing resources. Heating ventilation and air conditioning systems, and electric lighting are responsible for a significant share of energy usage, which makes it desirable to optimise their operations while maintaining user comfort. Such optimisation requires accurate occupancy estimations. In contrast to current, often invasive or unreliable methods we present an approach for accurate occupancy estimation
<span class="external-identifiers">
<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2674061.2674080">doi:10.1145/2674061.2674080</a>
<a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/sensys/KhanNMJLLHCOP14.html">dblp:conf/sensys/KhanNMJLLHCOP14</a>
<a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nzj322ghhfej3gdf53qsva4jji">fatcat:nzj322ghhfej3gdf53qsva4jji</a>
</span>
more »
... ng a wireless sensor network (WSN) that only collects non-sensitive data and a novel, hierarchical analysis method. We integrate potentially uncertain contextual information to produce occupancy estimates at different levels of granularity and provide confidence measures for effective building management. We evaluate our framework in real-world deployments and demonstrate its effectiveness and accuracy for occupancy monitoring in both low-and high-traffic area scenarios. Furthermore, we show how the system is used for analysing historical data and identify effective room misuse and thus a potential for energy saving.
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20150305193158/http://eprints.pascal-network.org:80/archive/00010302/01/khan_buildsys2014.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext">
<button class="ui simple right pointing dropdown compact black labeled icon button serp-button">
<i class="icon ia-icon"></i>
Web Archive
[PDF]
<div class="menu fulltext-thumbnail">
<img src="https://blobs.fatcat.wiki/thumbnail/pdf/1e/63/1e631aa80bb838998ed113c3f3b629b3e47c0d95.180px.jpg" alt="fulltext thumbnail" loading="lazy">
</div>
</button>
</a>
<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2674061.2674080">
<button class="ui left aligned compact blue labeled icon button serp-button">
<i class="external alternate icon"></i>
acm.org
</button>
</a>