{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T09:30:39Z","timestamp":1775899839247,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,2,6]],"date-time":"2020-02-06T00:00:00Z","timestamp":1580947200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Swedish Knowledge Foundation (KKS)","award":["E-care@home"],"award-info":[{"award-number":["E-care@home"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As research in smart homes and activity recognition is increasing, it is of ever increasing importance to have benchmarks systems and data upon which researchers can compare methods. While synthetic data can be useful for certain method developments, real data sets that are open and shared are equally as important. This paper presents the E-care@home system, its installation in a real home setting, and a series of data sets that were collected using the E-care@home system. Our first contribution, the E-care@home system, is a collection of software modules for data collection, labeling, and various reasoning tasks such as activity recognition, person counting, and configuration planning. It supports a heterogeneous set of sensors that can be extended easily and connects collected sensor data to higher-level Artificial Intelligence (AI) reasoning modules. Our second contribution is a series of open data sets which can be used to recognize activities of daily living. In addition to these data sets, we describe the technical infrastructure that we have developed to collect the data and the physical environment. Each data set is annotated with ground-truth information, making it relevant for researchers interested in benchmarking different algorithms for activity recognition.<\/jats:p>","DOI":"10.3390\/s20030879","type":"journal-article","created":{"date-parts":[[2020,2,7]],"date-time":"2020-02-07T03:13:27Z","timestamp":1581045207000},"page":"879","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Open-Source Data Collection and Data Sets for Activity Recognition in Smart Homes"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7776-2116","authenticated-orcid":false,"given":"Uwe","family":"K\u00f6ckemann","sequence":"first","affiliation":[{"name":"Centre for Applied Autonomous Sensor Systems (AASS), \u00d6rebro University, 70182 \u00d6rebro, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4001-2087","authenticated-orcid":false,"given":"Marjan","family":"Alirezaie","sequence":"additional","affiliation":[{"name":"Centre for Applied Autonomous Sensor Systems (AASS), \u00d6rebro University, 70182 \u00d6rebro, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2385-9470","authenticated-orcid":false,"given":"Jennifer","family":"Renoux","sequence":"additional","affiliation":[{"name":"Centre for Applied Autonomous Sensor Systems (AASS), \u00d6rebro University, 70182 \u00d6rebro, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3139-2564","authenticated-orcid":false,"given":"Nicolas","family":"Tsiftes","sequence":"additional","affiliation":[{"name":"RISE SICS, RISE Research Institutes of Sweden, 16440 Stockholm, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1953-6086","authenticated-orcid":false,"given":"Mobyen Uddin","family":"Ahmed","sequence":"additional","affiliation":[{"name":"School of Innovation Design and Engineering (IDT), M\u00e4lardalen University, 72220 V\u00e4ster\u00e5s, Sweden"}]},{"given":"Daniel","family":"Morberg","sequence":"additional","affiliation":[{"name":"School of Innovation Design and Engineering (IDT), M\u00e4lardalen University, 72220 V\u00e4ster\u00e5s, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1940-1747","authenticated-orcid":false,"given":"Maria","family":"Lind\u00e9n","sequence":"additional","affiliation":[{"name":"School of Innovation Design and Engineering (IDT), M\u00e4lardalen University, 72220 V\u00e4ster\u00e5s, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3122-693X","authenticated-orcid":false,"given":"Amy","family":"Loutfi","sequence":"additional","affiliation":[{"name":"Centre for Applied Autonomous Sensor Systems (AASS), \u00d6rebro University, 70182 \u00d6rebro, Sweden"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Jahn, M., Jentsch, M., Prause, C.R., Pramudianto, F., Al-Akkad, A., and Reiners, R. (2010, January 21\u201323). The Energy Aware Smart Home. Proceedings of the 2010 5th International Conference on Future Information Technology, Busan, South Korea.","DOI":"10.1109\/FUTURETECH.2010.5482712"},{"key":"ref_2","first-page":"544","article-title":"Smart home energy management system including renewable energy based on ZigBee and PLC","volume":"60","author":"Han","year":"2014","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_3","unstructured":"Cook, D.J., Youngblood, M., Heierman, E.O., Gopalratnam, K., Rao, S., Litvin, A., and Khawaja, F. (2003, January 26\u201326). MavHome: An agent-based smart home. Proceedings of the First IEEE International Conference on Pervasive Computing and Communications 2003 (PerCom 2003), Fort Worth, TX, USA."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Fong, A., and Fong, B. (2011, January 14\u201317). Indoor air quality control for asthma patients using smart home technology. Proceedings of the 2011 IEEE 15th International Symposium on Consumer Electronics (ISCE), Singapore.","DOI":"10.1109\/ISCE.2011.5973774"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Majumder, S., Aghayi, E., Noferesti, M., Memarzadeh-Tehran, H., Mondal, T., Pang, Z., and Deen, M. (2017). Smart homes for elderly healthcare\u2014Recent advances and research challenges. Sensors, 17.","DOI":"10.3390\/s17112496"},{"key":"ref_6","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_7","unstructured":"Gallissot, M.G., Caelen, J., Bonnefond, N., Meillon, B., and Pons, S. (2011). Using the Multicom Domus Dataset, Laboratoire d\u2019Informatique de Grenoble (LIG). Research Report RR-LIG-020."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Alemdar, H., Ertan, H., Incel, O.D., and Ersoy, C. (2013, January 5\u20138). ARAS human activity datasets in multiple homes with multiple residents. Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare, Venice, Italy.","DOI":"10.4108\/pervasivehealth.2013.252120"},{"key":"ref_9","unstructured":"Twomey, N., Diethe, T., Kull, M., Song, H., Camplani, M., Hannuna, S., Fafoutis, X., Zhu, N., Woznowski, P., and Flach, P. (2016). The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data. arXiv."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Br\u00e9zillon, P., Turner, R., and Penco, C. (2017). The ContextAct@A4H Real-Life Dataset of Daily-Living Activities. Modeling and Using Context, Springer International Publishing.","DOI":"10.1007\/978-3-319-57837-8"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"14162","DOI":"10.3390\/s150614162","article-title":"Simulation of smart home activity datasets","volume":"15","author":"Synnott","year":"2015","journal-title":"Sensors"},{"key":"ref_12","unstructured":"Masciadri, A., Veronese, F., Comai, S., Carlini, I., and Salice, F. (2018, January 22\u201326). Disseminating Synthetic Smart Home Data for Advanced Applications. Proceedings of the First Workshop on Knowledge-driven Analytics Impacting Human Quality of Life (KDAH), Turin, Italy."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Renoux, J., and Klugl, F. (2018, January 9\u201312). Simulating daily activities in a smart home for data generation. Proceedings of the 2018 Winter Simulation Conference (WSC), Gothenburg, Sweden.","DOI":"10.1109\/WSC.2018.8632226"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Duquennoy, S., Nahas, B.A., Landsiedel, O., and Watteyne, T. (2015, January 1\u20134). Orchestra: Robust Mesh Networks through Autonomously Scheduled TSCH. Proceedings of the International Conference on Embedded Networked Sensor Systems (ACM SenSys), Seoul, Korea.","DOI":"10.1145\/2809695.2809714"},{"key":"ref_15","unstructured":"Open Mobile Alliance (2017). Lightweight Machine to Machine Technical Specification, Open Mobile Alliance. Approved Version 1.0.1."},{"key":"ref_16","unstructured":"Eriksson, J., Finne, N., Tsiftes, N., Duquennoy, S., and Voigt, T. (2018, January 14\u201316). Scaling RPL to Dense and Large Networks with Constrained Memory. Proceedings of the 2018 International Conference on Embedded Wireless Systems and Networks (EWSN 2018), Madrid, Spain."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ahmed, M.U., Fotouhi, H., K\u00f6ckemann, U., Lind\u00e9n, M., Tomasic, I., Tsiftes, N., and Voigt, T. (2017, January 24\u201325). Run-Time Assurance for the E-care@home System. Proceedings of the International Conference on IoT Technologies for HealthCare, Angers, France.","DOI":"10.1007\/978-3-319-76213-5_15"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Hoque, E., Dickerson, R.F., and Stankovic, J.A. (2014, January 29\u201331). Vocal-diary: A voice command based ground truth collection system for activity recognition. Proceedings of the Wireless Health 2014 on National Institutes of Health, Bethesda, MD, USA.","DOI":"10.1145\/2668883.2669587"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Ayuningtyas, C., Leitner, G., Hitz, M., Funk, M., Hu, J., and Rauterberg, M. (2014). Activity monitoring for multi-inhabitant smart homes. SPIE Newsroom.","DOI":"10.1117\/2.1201412.005697"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Chen, C., Das, B., and Cook, D.J. (2010, January 19\u201321). A Data Mining Framework for Activity Recognition in Smart Environments. Proceedings of the 2010 Sixth International Conference on Intelligent Environments, Kuala Lumpur, Malaysia.","DOI":"10.1109\/IE.2010.22"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"903","DOI":"10.3233\/SW-180303","article-title":"SmartEnv as a network of ontology patterns","volume":"9","author":"Alirezaie","year":"2018","journal-title":"Semantic Web"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T., and Thiele, S. (2008, January 9\u201313). Engineering an Incremental ASP Solver. Proceedings of the 24th International Conference on Logic Programming, Udine, Italy.","DOI":"10.1007\/978-3-540-89982-2_23"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Alirezaie, M., Renoux, J., K\u00f6ckemann, U., Kristoffersson, A., Karlsson, L., Blomqvist, E., Tsiftes, N., Voigt, T., and Loutfi, A. (2017). An ontology-based context-aware system for smart homes: E-care@home. Sensors, 17.","DOI":"10.3390\/s17071586"},{"key":"ref_24","first-page":"59","article-title":"A survey of human-sensing: Methods for detecting presence, count, location, track, and identity","volume":"5","author":"Teixeira","year":"2010","journal-title":"ACM Comput. Surv."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1186\/2193-1801-3-299","article-title":"Pedestrian counting with grid-based binary sensors based on Monte Carlo method","volume":"3","author":"Fujii","year":"2014","journal-title":"SpringerPlus"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/s00138-015-0739-1","article-title":"Counting pedestrians with a zenithal arrangement of depth cameras","volume":"27","author":"Vera","year":"2016","journal-title":"Mach. Vis. Appl."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kameas, A., and Stathis, K. (2018). Online Guest Detection in a Smart Home Using Pervasive Sensors and Probabilistic Reasoning. Ambient Intelligence, Springer International Publishing.","DOI":"10.1007\/978-3-030-03062-9"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1016\/j.robot.2008.06.006","article-title":"Autonomous functional configuration of a network robot system","volume":"56","author":"Lundh","year":"2008","journal-title":"Robot. Auton. Syst."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"K\u00f6ckemann, U., and Karlsson, L. (2017, January 4\u20139). Configuration Planning with Temporal Constraints. Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), San Francisco, CA, USA.","DOI":"10.1609\/aaai.v31i1.11186"},{"key":"ref_30","unstructured":"K\u00f6ckemann, U., Tsiftes, N., and Loutfi, A. (2018, January 13\u201315). Integrating Constraint-based Planning with LwM2M for IoT Network Scheduling. Proceedings of the Workshop on AI for Internet of Things (AI4IoT), Stockholm, Sweden."},{"key":"ref_31","unstructured":"K\u00f6ckemann, U., Alirezaie, M., Karlsson, L., and Loutfi, A. (2018, January 13). Integrating Ontologies for Context-based Constraint-based Planning. Proceedings of the Tenth International Workshop Modelling and Reasoning in Context Co-Located with the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) and the 23rd European Conference on Artificial Intelligence (ECAI 2018), Stockholm, Sweden."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"820","DOI":"10.1136\/jech.2009.100503","article-title":"Sleep disturbance and daytime sleepiness predict vascular dementia","volume":"65","author":"Elwood","year":"2011","journal-title":"J. Epidemiol. Community Health"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/3\/879\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T08:55:30Z","timestamp":1760172930000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/3\/879"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,6]]},"references-count":32,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2020,2]]}},"alternative-id":["s20030879"],"URL":"https:\/\/doi.org\/10.3390\/s20030879","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,2,6]]}}}