A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit <a rel="external noopener" href="http://orca.cf.ac.uk/134046/1/1301.1084.pdf">the original URL</a>. The file type is <code>application/pdf</code>.
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gkdb6bz2lvbm3g7bnv3mc6o2lq" style="color: black;">2012 IEEE International Conference on Green Computing and Communications</a>
Internet of Things (IoT) will connect billions of sensors deployed around the world together. This will create an ideal opportunity to build a sensing-as-a-service platform. Due to large number of sensor deployments, there would be number of sensors that can be used to sense and collect similar information. Further, due to advances in sensor hardware technology, new methods and measurements will be introduced continuously. In the IoT paradigm, selecting the most appropriate sensors which can<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/greencom.2012.128">doi:10.1109/greencom.2012.128</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/greencom/PereraZCG12.html">dblp:conf/greencom/PereraZCG12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/k56p6zo74jgsbfkbqn5zpd272e">fatcat:k56p6zo74jgsbfkbqn5zpd272e</a> </span>
more »... vide relevant sensor data to address the problems at hand among billions of possibilities would be a challenge for both technical and non-technical users. In this paper, we propose the Context Awareness for Internet of Things (CA4IOT) architecture to help users by automating the task of selecting the sensors according to the problems/tasks at hand. We focus on automated configuration of filtering, fusion and reasoning mechanisms that can be applied to the collected sensor data streams using selected sensors. Our objective is to allow the users to submit their problems, so our proposed architecture understands them and produces more comprehensive and meaningful information than the raw sensor data streams generated by individual sensors.
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201104113149/http://orca.cf.ac.uk/134046/1/1301.1084.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/3d/04/3d04d7b4fc6d33fa11ffb2ebaf89bbe440596ea2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/greencom.2012.128"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>