Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Performance Evaluation of Area-Based Segmentation Technique on Ambient Sensor Data for Smart Home Assisted Living Subject The topic of the resource Activity Recognition; Elder Care; Machine Learning; Segmentation; Smart Home Description An account of the resource Activity recognition(AR) is a popular subject of research in the recent past. Recognition of activities performed by human beings, enables the addressing of challenges posed by many real-world applications such as health monitoring, providing security etc. Segmentation plays a vital role in AR. This paper evaluates the efficiency of Area-Based Segmentation using different performance measures. Area-Based segmentation was proposed in our earlier research work. The evaluation of the Area-Based segmentation technique is conducted on four real world datasets viz. Aruba17, Shib010, HH102, and HH113 comprising of data pertaining to an individual, living in the test bed home. Machine learning classifiers, SVM-R, SVM-P, NB and KNN are adopted to validate the performance of Area-Based segmentation. Amongst the four chosen classification algorithms SVM-R exhibits better in all the four datasets. Area-Based segmentation recognise the four test bed activities with accuracies of 0.74, 0.98, 0.66, and 0.99 respectively. The results reveal that Area based segmentation can efficiently segment sensor data stream which aids in accurate recognition of smart home activities. 2019 Procedia Computer Science. All rights reserved. Creator An entity primarily responsible for making the resource Kavitha R.; Binu S. Source A related resource from which the described resource is derived Procedia Computer Science, Vol-165, pp. 314-321. Publisher An entity responsible for making the resource available Elsevier B.V. Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.procs.2020.01.044" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.procs.2020.01.044</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081993451&amp;doi=10.1016%2Fj.procs.2020.01.044&amp;partnerID=40&amp;md5=cf42aceffd821d7f1c13d5da65a8b56f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081993451&amp;doi=10.1016%2fj.procs.2020.01.044&amp;partnerID=40&amp;md5=cf42aceffd821d7f1c13d5da65a8b56f</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 18770509 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kavitha R., CHRIST (Deemed to Be University), Bangalore, Karnataka, India; Binu S., Bangalore, Karnataka, India