{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T06:45:25Z","timestamp":1778654725295,"version":"3.51.4"},"reference-count":59,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T00:00:00Z","timestamp":1624579200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2016YFB0502102"],"award-info":[{"award-number":["2016YFB0502102"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42001397"],"award-info":[{"award-number":["42001397"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Introduction &amp; Training Program of Young Creative Talents of Shandong Province","award":["0031802"],"award-info":[{"award-number":["0031802"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Floor positioning is an important aspect of indoor positioning technology, which is closely related to location-based services (LBSs). Currently, floor positioning technologies are mainly based on radio signals and barometric pressure. The former are impacted by the multipath effect, rely on infrastructure support, and are limited by different spatial structures. For the latter, the air pressure changes with the temperature and humidity, the deployment cost of the reference station is high, and different terminal models need to be calibrated in advance. In view of these issues, here, we propose a novel floor positioning method based on human activity recognition (HAR), using smartphone built-in sensor data to classify pedestrian activities. We obtain the degree of the floor change according to the activity category of every step and determine whether the pedestrian completes floor switching through condition and threshold analysis. Then, we combine the previous floor or the high-precision initial floor with the floor change degree to calculate the pedestrians\u2019 real-time floor position. A multi-floor office building was chosen as the experimental site and verified through the process of alternating multiple types of activities. The results show that the pedestrian floor position change recognition and location accuracy of this method were as high as 100%, and that this method has good robustness and high universality. It is more stable than methods based on wireless signals. Compared with one existing HAR-based method and air pressure, the method in this paper allows pedestrians to undertake long-term static or round-trip activities during the process of going up and down the stairs. In addition, the proposed method has good fault tolerance for the misjudgment of pedestrian actions.<\/jats:p>","DOI":"10.3390\/ijgi10070437","type":"journal-article","created":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T11:07:40Z","timestamp":1624619260000},"page":"437","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Research on HAR-Based Floor Positioning"],"prefix":"10.3390","volume":"10","author":[{"given":"Hongxia","family":"Qi","sequence":"first","affiliation":[{"name":"National Administration of Surveying, Mapping and Geo-Information (NASG) Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunjia","family":"Wang","sequence":"additional","affiliation":[{"name":"National Administration of Surveying, Mapping and Geo-Information (NASG) Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2964-7698","authenticated-orcid":false,"given":"Jingxue","family":"Bi","sequence":"additional","affiliation":[{"name":"College of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9743-2499","authenticated-orcid":false,"given":"Hongji","family":"Cao","sequence":"additional","affiliation":[{"name":"National Administration of Surveying, Mapping and Geo-Information (NASG) Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shenglei","family":"Xu","sequence":"additional","affiliation":[{"name":"National Administration of Surveying, Mapping and Geo-Information (NASG) Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,25]]},"reference":[{"key":"ref_1","first-page":"1316","article-title":"Indoor Positioning with Smartphones: The State-of-the-art and the Challenges","volume":"46","author":"Chen","year":"2017","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Furfari, F., Crivello, A., Barsocchi, P., Palumbo, F., and Potorti, F. (October, January 30). What is next for Indoor Localisation? Taxonomy, protocols, and patterns for advanced Location Based Services. Proceedings of the 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Pisa, Italy.","DOI":"10.1109\/IPIN.2019.8911759"},{"key":"ref_3","unstructured":"Li, B.H., Harvey, B., and Gallagher, T. (2013, January 28\u201331). Using barometers to determine the height for indoor positioning. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation 2013, Montbeliard, France."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Gu, F.Q., Blankenbach, J., Khoshelham, K., Grottke, J., and Valaee, S. ZeeFi: Zero-Effort Floor Identification with Deep Learning for Indoor. Proceedings of the 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, 9\u201313 December 2019.","DOI":"10.1109\/GLOBECOM38437.2019.9013801"},{"key":"ref_5","unstructured":"Wang, H., Lenz, H., Szabo, A., Hanebeck, U.D., and Bamberger, J. (2006, January 3\u20136). Fusion of Barometric Sensors, WLAN Signals and Building Information for 3-D Indoor\/Campus Localization. Proceedings of the International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2006), Heidelberg, Germany."},{"key":"ref_6","unstructured":"Bai, Y.C., Jia, W.Y., Zhang, H., Mao, Z.H., and Sun, M.G. (2013, January 3\u20137). Helping the blind to find the floor of destination in multistory buildings using a barometer. Proceedings of the 35th Annual International Conference of the IEEE EMBS, Osaka, Japan."},{"key":"ref_7","first-page":"32","article-title":"Indoor Map Information Based WiFi Positioning Technology for Multi-Floor Buildings","volume":"46","author":"Li","year":"2017","journal-title":"J. Univ. Electron. Sci. Technol. China"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"206674","DOI":"10.1109\/ACCESS.2020.3037221","article-title":"The IPIN 2019 Indoor Localisation Competition\u2014Description and Results","volume":"8","author":"Park","year":"2020","journal-title":"IEEE Access"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s40328-019-00264-6","article-title":"Fast floor identification method based on confidence interval of Wi-Fi signals","volume":"54","author":"Qi","year":"2019","journal-title":"Acta Geod. Geophys."},{"key":"ref_10","first-page":"114","article-title":"A K-Means Based Method to Identify Floor in WLAN Indoor Positioning System","volume":"33","author":"Deng","year":"2012","journal-title":"Software"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Alsehly, F., Sevak, Z., and Arslan, T. (2011, January 21\u201323). Indoor positioning with floor determination in multi story buildings. Proceedings of the Indoor Positioning and Indoor Navigation (IPIN), Guimar\u00e3es, Portugal.","DOI":"10.1109\/IPIN.2011.6071945"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Maneerat, K., Prommak, C., and Kaemarungsi, K. (2014, January 14\u201317). Floor estimation algorithm for wireless indoor multi-story positioning systems. Proceedings of the 2014 11th International Conference on Electrical Engineering\/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), Nakhon Ratchasima, Thailand.","DOI":"10.1109\/ECTICon.2014.6839893"},{"key":"ref_13","first-page":"212","article-title":"Locus: An Indoor Localization, Tracking and Navigation System for Multi-story Buildings Using Heuristics Derived from Wi-Fi Signal Strength","volume":"Volume 120","author":"Bhargava","year":"2013","journal-title":"Proceedings of the International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services, Tokyo, Japan, 2\u20134 December 2013"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Maneerat, K., and Prommak, C. (2014, January 30\u201331). An Enhanced Floor Estimation Algorithm for Indoor Wireless Localization Systems Using Confidence Interval Approach. Proceedings of the International Conference on Telecommunications and Network Engineering, Zurich, Switzerland.","DOI":"10.1109\/ECTICon.2014.6839893"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1007\/978-981-13-0029-5_61","article-title":"Floor Recognition Based on SVM for WiFi Indoor Positioning","volume":"Volume 499","author":"Zhang","year":"2018","journal-title":"China Satellite Navigation Conference (CSNC) 2018 Proceedings"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"793","DOI":"10.3390\/s16060793","article-title":"Robust Statistical Approaches for RSS-Based Floor Detection in Indoor Localization","volume":"16","author":"Alireza","year":"2016","journal-title":"Sensors"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Han, L.T., Jiang, L., Kong, Q.L., Wang, J., Zhang, A.G., and Song, S.M. (2019). Indoor Localization within Multi-Story Buildings Using MAC and RSSI Fingerprint Vectors. Sensors, 19.","DOI":"10.3390\/s19112433"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"10115","DOI":"10.1109\/JSEN.2018.2872827","article-title":"TrueStory: Accurate and Robust RF-Based Floor Estimation for Challenging Indoor Environments","volume":"18","author":"Elbakly","year":"2018","journal-title":"IEEE Sens. J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1289013","DOI":"10.1155\/2016\/1289013","article-title":"BigLoc: A Two-Stage Positioning Method for Large Indoor Space","volume":"2016","author":"Zheng","year":"2016","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"7857","DOI":"10.3390\/s150407857","article-title":"Using Multiple Barometers to Detect the Floor Location of Smart Phones with Built-in Barometric Sensors for Indoor Positioning","volume":"15","author":"Xia","year":"2015","journal-title":"Sensors"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Ebner, F., Fetzer, T., Deinzer, F., K\u00f6ping, L., and Grzegorzek, M. (2015, January 13\u201316). Multi sensor 3D indoor localization. Proceedings of the 2015 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Banff, AB, Canada.","DOI":"10.1109\/IPIN.2015.7346772"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Jaworski, W., Wilk, P., Zborowski, P., Chmielowiec, W., and Lee, A.Y.G. (2017, January 18\u201321). Real-time 3D indoor localization. Proceedings of the 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sapporo, Japan.","DOI":"10.1109\/IPIN.2017.8115874"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2557","DOI":"10.1002\/wcm.2706","article-title":"Scalable floor localization using barometer on smartphone","volume":"16","author":"Ye","year":"2016","journal-title":"Wirel. Commun. Mob. Comput."},{"key":"ref_24","unstructured":"Kim, S., Kim, J., and Han, D. (2017, January 18\u201321). Floor Detection Using a Barometer Sensor in a Smartphone. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sapporo, Japan."},{"key":"ref_25","unstructured":"Ye, H.B., Gu, T., Zhu, X.R., Xu, J.W., Tao, X.P., Lu, J., and Jin, N. (2012, January 19\u201323). FTrack: Infrastructure-free floor localization via mobile phone sensing. Proceedings of the IEEE International Conference on Pervasive Computing and Communications, Lugano, Switzerland."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Varshavsky, A., LaMarca, A., Hightower, J., and de Lara, E. (2007, January 19\u201323). The skyloc floor localization system. Proceedings of the Fifth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom\u201907), White Plains, NY, USA.","DOI":"10.1109\/PERCOM.2007.37"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Woodman, O., and Harle, R. (2008, January 21\u201324). Pedestrian localisation for indoor environments. Proceedings of the 10th International Conference on Ubiquitous Computing, Seoul, Korea.","DOI":"10.1145\/1409635.1409651"},{"key":"ref_28","first-page":"269","article-title":"Method to Identify Floor in WiFi Fingerprinting Location System","volume":"37","author":"Ai","year":"2015","journal-title":"J. WUT Inf. Manag. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Moder, T., Hafner, P., Wisiol, K., and Wieser, M. (2014, January 27\u201330). 3D indoor positioning with pedestrian dead reckoning and activity recognition based on Bayes filtering. Proceedings of the 5th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Busan, South Korea.","DOI":"10.1109\/IPIN.2014.7275549"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Xu, Z.Y., Wei, J.M., Zhu, J.X., and Yang, W.J. (2017, January 18\u201321). A robust floor localization method using inertial and barometer measurements. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sapporo, Japan.","DOI":"10.1109\/IPIN.2017.8115952"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Gupta, P., Bharadwaj, S., Ramakrishnan, S., and Balakrishnan, J. (March, January 28). Robust floor determination for indoor positioning. Proceedings of the 2014 Twentieth National Conference on Communications (NCC), Kanpur, India.","DOI":"10.1109\/NCC.2014.6811285"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Gansemer, S., Gro\u00dfmann, U., and Hakobyan, S. (2010, January 15\u201317). RSSI-based Euclidean Distance algorithm for indoor positioning adapted for the use in dynamically changing WLAN environments and multi-level buildings. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Zurich, Switzerland.","DOI":"10.1109\/IPIN.2010.5648247"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1007\/s11390-019-1957-1","article-title":"CBSC: A crowdsensing system for automatic calibrating of barometers","volume":"34","author":"Ye","year":"2019","journal-title":"J. Comput. Sci. Tech."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1109\/JSEN.2018.2852494","article-title":"A Sensor Fusion-Based Framework for Floor Localization","volume":"19","author":"Haque","year":"2019","journal-title":"Sens. J. IEEE"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3264914","article-title":"HyRise: A Robust and Ubiquitous Multi-Sensor Fusion-based Floor Localization System","volume":"2","author":"Elbakly","year":"2018","journal-title":"ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Ye, H.B., Gu, T., Tao, X.P., and Lu, J. (2014, January 16\u201319). F-Loc: Floor localization via crowdsourcing. Proceedings of the 2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS), Hsinchu, Taiwan.","DOI":"10.1109\/PADSW.2014.7097790"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Yan, S., Luo, H.Y., Zhao, F., Shao, W.H., Li, Z.H., and Crivello, A. (October, January 30). Wi-Fi RTT based indoor positioning with dynamic weighted multidimensional scaling. Proceedings of the 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Pisa, Italy.","DOI":"10.1109\/IPIN.2019.8911783"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Rajagopal, N., Lazik, P., Pereira, N., Chayapathy, S., Sinopoli, B., and Rowe, A. (2018, January 11\u201313). Enhancing indoor smartphone location acquisition using floor plans. Proceedings of the 2018 17th ACM\/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Porto, Portugal.","DOI":"10.1109\/IPSN.2018.00056"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Schr\u00f6der, Y., Heidorn, D., and Wolf, L. (October, January 30). Investigation of Multipath Effects on Phase-based Ranging. Proceedings of the 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Pisa, Italy.","DOI":"10.1109\/IPIN.2019.8911817"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Shen, X., Xu, K., Sun, X.Q., Wu, J., and Lin, J.T. (2011, January 18\u201321). Optimized indoor wireless propagation model in wifi-rof network architecture for rss-based localization in the internet of things. Proceedings of the 2011 International Topical Meeting on Microwave Photonics jointly held with the 2011 Asia-Pacific Microwave Photonics Conference, Singapore.","DOI":"10.1109\/MWP.2011.6088723"},{"key":"ref_41","unstructured":"Liang, Y. (2009). Statistical Modeling and Applications on Wireless Signal Propagation in WLAN Indoor Location Systems. [Master\u2019s Thesis, Harbin Institute of Technology]."},{"key":"ref_42","unstructured":"Sadeghi, J., and Mahmood, S. (2017). A 3D Ubiquitous Multi-Platform Localization and Tracking System for Smartphones. [Ph.D. Thesis, University of Toronto]."},{"key":"ref_43","unstructured":"Chen, Y.S. (2016). The Mixed Floor Localization System Based on Barometer and WiFi. [Master\u2019s Thesis, Hangzhou Dianzi University]."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Muralidharan, K., Khan, A.J., Misra, A., Balan, R.K., and Agarwal, S. (2014, January 26\u201327). Barometric phone sensors\u2014More hype than hope!. Proceedings of the 15th Workshop on Mobile Computing Systems and Applications, Santa Barbara, CA, USA.","DOI":"10.1145\/2565585.2565596"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1080\/10095020.2019.1631573","article-title":"Floor positioning method indoors with smartphone\u2019s barometer","volume":"22","author":"Yu","year":"2019","journal-title":"Geospat. Inf. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Alshami, I.H., Ahmad, N.A., Sahibuddin, S., and Firdaus, F. (2017). Adaptive Indoor Positioning Model Based on WLAN-Fingerprinting for Dynamic and Multi-Floor Environments. Sensors, 17.","DOI":"10.3390\/s17081789"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Fetzer, T., Ebner, F., Bullmann, M., Deinzer, F., and Grzegorzek, M. (2018). Smartphone-Based Indoor Localization within a 13th Century Historic Building. Sensors, 18.","DOI":"10.3390\/s18124095"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Jimenez, A.R., Seco, F., Prieto, C., and Guevara, J. (2009, January 26\u201328). A comparison of Pedestrian Dead-Reckoning algorithms using a low-cost MEMS IMU. Proceedings of the IEEE International Symposium on Intelligent Signal Processing, Budapest, Hungary.","DOI":"10.1109\/WISP.2009.5286542"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2059","DOI":"10.3390\/s150102059","article-title":"A Survey of Online Activity Recognition Using Mobile Phones","volume":"15","author":"Shoaib","year":"2015","journal-title":"Sensors"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.patrec.2018.02.010","article-title":"Deep Learning for Sensor-based Activity Recognition: A Survey","volume":"119","author":"Wang","year":"2019","journal-title":"Pattern Recognit. Lett."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1192","DOI":"10.1109\/SURV.2012.110112.00192","article-title":"A Survey on Human Activity Recognition using Wearable Sensors","volume":"15","author":"Lara","year":"2013","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_52","first-page":"188","article-title":"Human activity recognition based on sensors of smart phone","volume":"52","author":"Liu","year":"2016","journal-title":"Comput. Eng. Appl."},{"key":"ref_53","unstructured":"Sun, Z.H. (2016). Research on Mobile Phone and Wearable Devices Based Human Activity Recognition Technologies. [Ph.D. Thesis, University of Science and Technology of China]."},{"key":"ref_54","first-page":"169","article-title":"Real-time human activity pattern recognition based on time domain features of acceleration","volume":"49","author":"Liu","year":"2015","journal-title":"J. Shanghai Jiao Tong Univ."},{"key":"ref_55","first-page":"1","article-title":"Recognition system of human daily physical activity based on a 3D acceleration sensor","volume":"9","author":"Li","year":"2013","journal-title":"Instrum. Technol."},{"key":"ref_56","first-page":"630","article-title":"Walking pattern recognition based on inertial sensing","volume":"28","author":"Wang","year":"2014","journal-title":"J. Electron. Meas. Instrum."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2015\/946457","article-title":"Multifloor Wi-Fi Localization System with Floor Identification","volume":"2015","author":"Sun","year":"2015","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1109\/TII.2015.2491264","article-title":"HYFI: Hybrid Floor Identification Based on Wireless Fingerprinting and Barometric Pressure","volume":"13","author":"Zhao","year":"2017","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1109\/MPRV.2013.23","article-title":"Evaluating AAL solutions through competitive benchmarking: The localization competition","volume":"12","author":"Barsocchi","year":"2013","journal-title":"IEEE Pervasive Comput. Mag."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/7\/437\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:24:08Z","timestamp":1760163848000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/7\/437"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,25]]},"references-count":59,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["ijgi10070437"],"URL":"https:\/\/doi.org\/10.3390\/ijgi10070437","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,25]]}}}