{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T10:39:48Z","timestamp":1761129588844,"version":"build-2065373602"},"publisher-location":"Basel Switzerland","reference-count":25,"publisher":"MDPI","license":[{"start":{"date-parts":[[2018,10,17]],"date-time":"2018-10-17T00:00:00Z","timestamp":1539734400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.3390\/proceedings2191245","type":"proceedings-article","created":{"date-parts":[[2018,10,17]],"date-time":"2018-10-17T10:22:54Z","timestamp":1539771774000},"page":"1245","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["A Comparative Analysis of Windowing Approaches in Dense Sensing Environments"],"prefix":"10.3390","author":[{"given":"Bronagh","family":"Quigley","sequence":"first","affiliation":[{"name":"Pervasive Computing Research Group, School of Computing, Ulster University, Coleraine BT37 0QB, Northern Ireland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1250-265X","authenticated-orcid":false,"given":"Mark","family":"Donnelly","sequence":"additional","affiliation":[{"name":"Pervasive Computing Research Group, School of Computing, Ulster University, Coleraine BT37 0QB, Northern Ireland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1623-0014","authenticated-orcid":false,"given":"George","family":"Moore","sequence":"additional","affiliation":[{"name":"Pervasive Computing Research Group, School of Computing, Ulster University, Coleraine BT37 0QB, Northern Ireland"}]},{"given":"Leo","family":"Galway","sequence":"additional","affiliation":[{"name":"Pervasive Computing Research Group, School of Computing, Ulster University, Coleraine BT37 0QB, Northern Ireland"}]}],"member":"1968","published-online":{"date-parts":[[2018,10,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1321","DOI":"10.1109\/JSEN.2014.2370945","article-title":"Wearable Sensors for Human Activity Monitoring: A Review","volume":"15","author":"Mukhopadhyay","year":"2015","journal-title":"IEEE Sens."},{"key":"ref_2","unstructured":"Youngblood, G.M., Cook, D.J., and Holder, L.B. (August, January 30). Automation intelligence for the smart environment. Proceedings of the International Joint Conference on Artificial Intelligence, Edinburgh, UK."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ranasinghe, S., Machot, F., and Mayr, H.C. (2016). A Review on Applications of Activity Recognition Systems with regard to Performance and Evaluation. Int. J. Distrib. Sens. Netw., 12.","DOI":"10.1177\/1550147716665520"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Ghasemi, V., and Pouyan, A.A. (2016, January 14\u201315). Human activity recognition in ambient assisted living environments using a convex optimization problem. Proceedings of the 2nd International Conference of Signal Processing and Intelligent Systems (ICSPIS), Tehran, Iran.","DOI":"10.1109\/ICSPIS.2016.7869899"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Vrigkas, M., Nikou, C., and Kakadiaris, I. (2015). A Review of Human Activity Recognition Methods. Front. Robot. AI, 2.","DOI":"10.3389\/frobt.2015.00028"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.pmcj.2012.07.003","article-title":"Activity Recognition on streaming sensor data","volume":"10","author":"Krishnan","year":"2014","journal-title":"Pervasive Mob. Comput."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"6474","DOI":"10.3390\/s140406474","article-title":"Window Size Impact in Human Activity Recognition","volume":"14","author":"Banos","year":"2014","journal-title":"Sensors"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Yala, N., and Fergani, B. (2015, January 2\u20134). Feature extraction for human activity recognition on streaming data. Proceedings of the International Symposium on Inovations in Intelligent SysTems and Applications (INISTA), Madrid, Spain.","DOI":"10.1109\/INISTA.2015.7276759"},{"key":"ref_9","unstructured":"Machot, F.A., Mayr, H.C., and Ranasinghe, S. (2016, January 5\u20138). A windowing approach for activity recognition in sensor data streams. Proceedings of the 8th International Conference on Ubiquitous and Future Networks (ICUFN), Vienna, Austria."},{"key":"ref_10","unstructured":"Machot, F.A., and Mayr, H.C. (July, January 29). Improving Human Activity Recognition by Smart Windowing and Spatio-Temporal Feature Analysis. Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA) ACM, Corfu Island, Greece."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Machot, F.A., Mosa, A.H., Ali, M., and Kyamakya, K. (2017). Activity Recognition in Sensor Data Streams for Active and Assisted Living Environments. IEEE Trans. Circuits Syst. Video Technol.","DOI":"10.1109\/TCSVT.2017.2764868"},{"key":"ref_12","unstructured":"Blond, A., Liu, W., and Cardell-Oliver, R. (2013, January 13\u201315). An Investigation on window size selection for human activity recognition. Proceedings of the 11th Australian Data-mining Conference, Canberra, Australia."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2010","DOI":"10.1016\/j.patcog.2007.11.016","article-title":"Gesture Spotting with body-worn inertial sensors to detect user activities","volume":"41","author":"Junker","year":"2008","journal-title":"Pattern Recognit."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.asoc.2015.04.060","article-title":"A supervised approach to automatically extract a set of rules to support fall detection in an mHealth system","volume":"34","author":"Sannino","year":"2015","journal-title":"J. Appl. Soft Comput."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Sannino, I., Falco, I.D., and Pietro, G.D. (2017, January 16\u201318). Detection of falling events through windowing and automatic extraction of sets of rules: Preliminary results. Proceedings of the 14th International Conference on Networking, Sensing and Control (ICNSC), Calabria, Italy.","DOI":"10.1109\/ICNSC.2017.8000169"},{"key":"ref_16","first-page":"126","article-title":"The Effect of Window Length on Accuracy of Smartphone-Based Activity Recognition","volume":"43","author":"Bashir","year":"2016","journal-title":"IAENG Int. J. Comput. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Lee, J., and Kim, J. (2016). Energy-Efficient Real-Time Human Activity Recognition on Smart Mobile Devices. Mob. Inf. Syst.","DOI":"10.1155\/2016\/2316757"},{"key":"ref_18","unstructured":"Fahad, L.G., Ali, A., and Rajarajan, M. (2013, January 24\u201326). Long term analysis of daily activities in a smart home. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2682","DOI":"10.3390\/s130202682","article-title":"A unified framework for activity recognition-based behavior analysis and action prediction in smart homes","volume":"13","author":"Fatima","year":"2013","journal-title":"Sensors"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/MC.2012.328","article-title":"CASAS: A Smart Home in a Box","volume":"46","author":"Cook","year":"2013","journal-title":"Computer"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.pmcj.2010.12.001","article-title":"A hierarchical approach to real-time activity recognition in body sensor networks","volume":"8","author":"Wang","year":"2012","journal-title":"J. Pervasive Mob. Comput."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1961189.1961199","article-title":"LIBSVM: A library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_23","first-page":"61","article-title":"Probablistic outputs for support vector machines and comparison to regularized likelihood methods","volume":"10","author":"Platt","year":"1999","journal-title":"Adv. Large Margin Classifiers"},{"key":"ref_24","unstructured":"Novakovic, J. (2009, January 24\u201326). Using information gain attribute evaluation to classify sonar targets. Proceedings of the 17th Telecommunications Forum TELFOR, Belgrade, Serbia."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Roggen, D., Calatroni, A., Rossi, M., Holleczek, T., Tr\u00f6ster, G., Lukowicz, P., Pirkl, G., Bannach, D., Ferscha, A., and Doppler, J. (2010, January 15\u201318). Collecting complex activity data sets in highly rich networked sensor environments. Proceedings of the 7th International Conference on Networked Sensing Systems (INSS\u201910), Kassel, Germany.","DOI":"10.1109\/INSS.2010.5573462"}],"event":{"name":"The International Conference on Ubiquitous Computing and Ambient \u202aIntelligence\u202c\u202c","acronym":"UCAmI 2018"},"container-title":["UCAmI 2018"],"original-title":[],"link":[{"URL":"https:\/\/www.mdpi.com\/2504-3900\/2\/19\/1245\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:26:11Z","timestamp":1760196371000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2504-3900\/2\/19\/1245"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,17]]},"references-count":25,"alternative-id":["proceedings2191245"],"URL":"https:\/\/doi.org\/10.3390\/proceedings2191245","relation":{},"subject":[],"published":{"date-parts":[[2018,10,17]]}}}