{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T15:54:26Z","timestamp":1782834866185,"version":"3.54.5"},"reference-count":56,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,12,17]],"date-time":"2018-12-17T00:00:00Z","timestamp":1545004800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["769643"],"award-info":[{"award-number":["769643"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Indoor localization has become a mature research area, but further scientific developments are limited due to the lack of open datasets and corresponding frameworks suitable to compare and evaluate specialized localization solutions. Although several competitions provide datasets and environments for comparing different solutions, they hardly consider novel technologies such as Bluetooth Low Energy (BLE), which is gaining more and more importance in indoor localization due to its wide availability in personal and environmental devices and to its low costs and flexibility. This paper contributes to cover this gap by: (i) presenting a new indoor BLE dataset; (ii) reviewing several, meaningful use cases in different application scenarios; and (iii) discussing alternative uses of the dataset in the evaluation of different positioning and navigation applications, namely localization, tracking, occupancy and social interaction.<\/jats:p>","DOI":"10.3390\/s18124462","type":"journal-article","created":{"date-parts":[[2018,12,18]],"date-time":"2018-12-18T02:15:59Z","timestamp":1545099359000},"page":"4462","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":63,"title":["Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction"],"prefix":"10.3390","volume":"18","author":[{"given":"Paolo","family":"Baronti","sequence":"first","affiliation":[{"name":"Institute of Information Science and Technologies, National Research Council, 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6862-7593","authenticated-orcid":false,"given":"Paolo","family":"Barsocchi","sequence":"additional","affiliation":[{"name":"Institute of Information Science and Technologies, National Research Council, 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1248-9478","authenticated-orcid":false,"given":"Stefano","family":"Chessa","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Pisa, 56127 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6982-242X","authenticated-orcid":false,"given":"Fabio","family":"Mavilia","sequence":"additional","affiliation":[{"name":"Institute of Information Science and Technologies, National Research Council, 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9778-7142","authenticated-orcid":false,"given":"Filippo","family":"Palumbo","sequence":"additional","affiliation":[{"name":"Institute of Information Science and Technologies, National Research Council, 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,17]]},"reference":[{"key":"ref_1","unstructured":"Evans, D. (2011). The Internet of Things: How the Next Evolution of the Internet Is Changing Everything, Cisco. CISCO White Paper."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MCE.2017.2717198","article-title":"Sensing a City\u2019s State of Health: Structural Monitoring System by Internet-of-Things Wireless Sensing Devices","volume":"7","author":"Barsocchi","year":"2018","journal-title":"IEEE Consum. Electron. Mag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.comnet.2015.06.006","article-title":"On service discovery in mobile social networks: Survey and perspectives","volume":"88","author":"Girolami","year":"2015","journal-title":"Comput. Netw."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1109\/MCOM.2016.7509387","article-title":"Empowering mobile crowdsensing through social and ad hoc networking","volume":"54","author":"Chessa","year":"2016","journal-title":"IEEE Commun. Mag."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Barsocchi, P., Crivello, A., La Rosa, D., and Palumbo, F. (2016, January 4\u20137). A multisource and multivariate dataset for indoor localization methods based on WLAN and geo-magnetic field fingerprinting. Proceedings of the IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN), Alcala de Henares, Spain.","DOI":"10.1109\/IPIN.2016.7743678"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Torres-Sospedra, J., Montoliu, R., Mart\u00ednez-Us\u00f3, A., Avariento, J.P., Arnau, T.J., Benedito-Bordonau, M., and Huerta, J. (2014, January 27\u201330). UJIIndoorLoc: A new multi-building and multi-floor database for WLAN fingerprint-based indoor localization problems. Proceedings of the IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN), Busan, South Korea.","DOI":"10.1109\/IPIN.2014.7275492"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1109\/MSP.2017.2713817","article-title":"The microsoft indoor localization competition: Experiences and lessons learned","volume":"34","author":"Lymberopoulos","year":"2017","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1109\/MPRV.2013.23","article-title":"Evaluating ambient assisted living solutions: The localization competition","volume":"12","author":"Barsocchi","year":"2013","journal-title":"IEEE Pervasive Comput."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1109\/TSMCC.2007.905750","article-title":"Survey of wireless indoor positioning techniques and systems","volume":"37","author":"Liu","year":"2007","journal-title":"IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.)"},{"key":"ref_10","unstructured":"Bluetooth Special Interest Group (SIG) (2016). Bluetooth Specification Version 5.0. Specification of the Bluetooth System, Bluetooth Special Interest Group (SIG)."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Palumbo, F., Barsocchi, P., Chessa, S., and Augusto, J.C. (2015, January 25\u201328). A stigmergic approach to indoor localization using bluetooth low energy beacons. Proceedings of the 12th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Karlsruhe, Germany.","DOI":"10.1109\/AVSS.2015.7301734"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2418","DOI":"10.1109\/JSAC.2015.2430281","article-title":"Location fingerprinting with bluetooth low energy beacons","volume":"33","author":"Faragher","year":"2015","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_13","unstructured":"Potort\u00ec, F., Crivello, A., and Palumbo, F. The EvAAL Evaluation Framework and the IPIN Competitions. Proceedings of the Geographical and Fingerprinting Data to Create Systems for Indoor Positioning and Indoor\/Outdoor Navigation."},{"key":"ref_14","unstructured":"Agostini, M., Crivello, A., Palumbo, F., and Potort\u00ec, F. (2017, January 16\u201317). An Open-source Framework for Smartphone-based Indoor Localization. Proceedings of the Artificial Intelligence for Ambient Assisted Living (AI*AAL2017), Bari, Italy."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Alarifi, A., Al-Salman, A., Alsaleh, M., Alnafessah, A., Al-Hadhrami, S., Al-Ammar, M.A., and Al-Khalifa, H.S. (2016). Ultra wideband indoor positioning technologies: Analysis and recent advances. Sensors, 16.","DOI":"10.3390\/s16050707"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2106","DOI":"10.1109\/TIM.2017.2681398","article-title":"Comparing Ubisense, BeSpoon, and DecaWave UWB location systems: Indoor performance analysis","volume":"66","author":"Ruiz","year":"2017","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Seco, F., Jim\u00e9nez, A.R., and Zampella, F. (2015, January 17\u201319). Fine-grained acoustic positioning with compensation of CDMA interference. Proceedings of the IEEE International Conference on Industrial Technology (ICIT), Seville, Spain.","DOI":"10.1109\/ICIT.2015.7125606"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/JPHOT.2016.2636021","article-title":"Single LED beacon-based 3-D indoor positioning using off-the-shelf devices","volume":"8","author":"Hou","year":"2016","journal-title":"IEEE Photonics J."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Mendoza-Silva, G.M., Richter, P., Torres-Sospedra, J., Lohan, E.S., and Huerta, J. (2018). Long-Term WiFi Fingerprinting Dataset for Research on Robust Indoor Positioning. Data, 3.","DOI":"10.3390\/data3010003"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Lohan, E.S., Torres-Sospedra, J., Lepp\u00e4koski, H., Richter, P., Peng, Z., and Huerta, J. (2017). Wi-Fi Crowdsourced Fingerprinting Dataset for Indoor Positioning. Data, 2.","DOI":"10.3390\/data2040032"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Potort\u00ec, F., Cassar\u00e0, P., and Palumbo, F. (2018, January 8\u201312). Robust Device-Free Localisation with Few Anchors. Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, Singapore.","DOI":"10.1145\/3267305.3276798"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Chesser, M., Chea, L., and Ranasinghe, D. (2018, January 5\u20137). bTracked: Highly Accurate Field Deployable Real-Time Indoor Spatial Tracking for Human Behavior Observations. Proceedings of the International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, New York, NY, USA.","DOI":"10.1145\/3286978.3287020"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"L\u00f3pez-De-Teruel, P.E., Canovas, O., Garcia Clemente, F.J., Gonzalez, R., and Carrasco, J.A. (2018, January 5\u20137). Beyond the RSSI value in BLE-based passive indoor localization: Let data speak. Proceedings of the International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, New York, NY, USA.","DOI":"10.1145\/3286978.3286986"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1540","DOI":"10.1109\/TII.2016.2579265","article-title":"Smartphone inertial sensor-based indoor localization and tracking with iBeacon corrections","volume":"12","author":"Chen","year":"2016","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Kriz, P., Maly, F., and Kozel, T. (2016). Improving indoor localization using bluetooth low energy beacons. Mob. Inf. Syst., 2016.","DOI":"10.1155\/2016\/2083094"},{"key":"ref_26","unstructured":"Bahl, P., and Padmanabhan, V.N. (2000, January 26\u201330). RADAR: An in-building RF-based user location and tracking system. Proceedings of the Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2000), Tel Aviv, Israel."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Chintalapudi, K., Padmanabha Iyer, A., and Padmanabhan, V.N. (2010, January 20\u201324). Indoor localization without the pain. Proceedings of the Sixteenth Annual International Conference On Mobile Computing and Networking, Chicago, IL, USA.","DOI":"10.1145\/1859995.1860016"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Machaj, J., Brida, P., and Pich\u00e9, R. (2011, January 21\u201323). Rank based fingerprinting algorithm for indoor positioning. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Guimaraes, Portugal.","DOI":"10.1109\/IPIN.2011.6071929"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Marques, N., Meneses, F., and Moreira, A. (2012, January 13\u201315). Combining similarity functions and majority rules for multi-building, multi-floor, WiFi positioning. Proceedings of the IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sydney, Australia.","DOI":"10.1109\/IPIN.2012.6418937"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Lemic, F., Behboodi, A., Handziski, V., and Wolisz, A. (2014, January 27\u201330). Experimental decomposition of the performance of fingerprinting-based localization algorithms. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Busan, Korea.","DOI":"10.1109\/IPIN.2014.7275503"},{"key":"ref_31","unstructured":"Van Haute, T., De Poorter, E., Rossey, J., Moerman, I., Handziski, V., Behboodi, A., Lemic, F., Wolisz, A., Wirstr\u00f6m, N., and Voigt, T. (2013, January 7). The evarilos benchmarking handbook: Evaluation of rf-based indoor localization solutions. Proceedings of the 2nd International Workshop on Measurement-Based Experimental Research, Methodology and Tools, Dublin, Ireland."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Lemic, F., B\u00fcsch, J., Chwalisz, M., Handziski, V., and Wolisz, A. (2014, January 20\u201321). Infrastructure for benchmarking rf-based indoor localization under controlled interference. Proceedings of the Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS), Corpus Christ, TX, USA.","DOI":"10.1109\/UPINLBS.2014.7033707"},{"key":"ref_33","unstructured":"Berclaz, J., Shahrokni, A., Fleuret, F., Ferryman, J., and Fua, P. (2009, January 20\u201325). Evaluation of probabilistic occupancy map people detection for surveillance systems. Proceedings of the IEEE International Workshop on Performance Evaluation of Tracking and Surveillance, Miami, FL, USA."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Ghai, S.K., Thanayankizil, L.V., Seetharam, D.P., and Chakraborty, D. (2012, January 19\u201323). Occupancy detection in commercial buildings using opportunistic context sources. Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), Lugano, Switzerland.","DOI":"10.1109\/PerComW.2012.6197536"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Erickson, V.L., and Cerpa, A.E. (2010, January 2). Occupancy based demand response HVAC control strategy. Proceedings of the 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building, Zurich, Switzerland.","DOI":"10.1145\/1878431.1878434"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Filippoupolitis, A., Oliff, W., and Loukas, G. (2016, January 14\u201316). Bluetooth low energy based occupancy detection for emergency management. Proceedings of the International Conference on Ubiquitous Computing and Communications and 2016 International Symposium on Cyberspace and Security (IUCC-CSS), Granada, Spain.","DOI":"10.1109\/IUCC-CSS.2016.013"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.enbuild.2018.03.084","article-title":"Building occupancy estimation and detection: A review","volume":"169","author":"Chen","year":"2018","journal-title":"Energy Build."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.enbuild.2015.11.071","article-title":"Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models","volume":"112","author":"Candanedo","year":"2016","journal-title":"Energy Build."},{"key":"ref_39","unstructured":"Yang, Z., Li, N., Becerik-Gerber, B., and Orosz, M. (2012, January 26\u201330). A multi-sensor based occupancy estimation model for supporting demand driven HVAC operations. Proceedings of the 2012 Symposium on Simulation for Architecture and Urban Design, Orlando, FL, USA."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1504\/IJSNET.2018.092136","article-title":"Detecting occupancy and social interaction via energy and environmental monitoring","volume":"27","author":"Crivello","year":"2018","journal-title":"Int. J. Sens. Netw."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"16377","DOI":"10.1109\/ACCESS.2018.2809612","article-title":"Visible Light Based Occupancy Inference Using Ensemble Learning","volume":"6","author":"Hao","year":"2018","journal-title":"IEEE Access"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Li, D., Balaji, B., Jiang, Y., and Singh, K. (2012, January 6). A wi-fi based occupancy sensing approach to smart energy in commercial office buildings. Proceedings of the Fourth ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, Toronto, ON, Canada.","DOI":"10.1145\/2422531.2422568"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Barsocchi, P., Crivello, A., Girolami, M., Mavilia, F., and Palumbo, F. (2017, January 18\u201321). Occupancy detection by multi-power bluetooth low energy beaconing. Proceedings of the International Conference Indoor Positioning and Indoor Navigation (IPIN), Sapporo, Japan.","DOI":"10.1109\/IPIN.2017.8115946"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Cho, E., Myers, S.A., and Leskovec, J. (2011, January 21\u201324). Friendship and mobility: User movement in location-based social networks. Proceedings of the 17th ACM SIGKDD International Conference On Knowledge Discovery and Data Mining, San Diego, CA, USA.","DOI":"10.1145\/2020408.2020579"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Sofia, R., Firdose, S., Lopes, L.A., Moreira, W., and Mendes, P. (2016, January 14\u201316). NSense: A people-centric, non-intrusive opportunistic sensing tool for contextualizing nearness. Proceedings of the IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom), Munich, Germany.","DOI":"10.1109\/HealthCom.2016.7749490"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Mtibaa, A., May, M., Diot, C., and Ammar, M. (2010, January 14\u201319). Peoplerank: Social opportunistic forwarding. Proceedings of the IEEE INFOCOM, San Diego, CA, USA.","DOI":"10.1109\/INFCOM.2010.5462261"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Pietil\u00e4inen, A.K., Oliver, E., LeBrun, J., Varghese, G., and Diot, C. (2009, January 17). MobiClique: Middleware for mobile social networking. Proceedings of the 2nd ACM Workshop on Online Social Networks, Barcelona, Spain.","DOI":"10.1145\/1592665.1592678"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1109\/TMC.2007.1060","article-title":"Impact of human mobility on opportunistic forwarding algorithms","volume":"6","author":"Chaintreau","year":"2007","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_49","unstructured":"and Petro, C. (2018, December 16). CRAWDAD Dataset Hope\/amd (v. 2008-08-07). Available online: https:\/\/crawdad.org\/hope\/amd\/20080807."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Varvello, M., Picconi, F., Diot, C., and Biersack, E. (2008, January 9\u201312). Is there life in Second Life?. Proceedings of the 2008 ACM CoNEXT Conference, Madrid, Spain.","DOI":"10.1145\/1544012.1544013"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Fathi, A., Hodgins, J.K., and Rehg, J.M. (2012, January 16\u201321). Social interactions: A first-person perspective. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, USA.","DOI":"10.1109\/CVPR.2012.6247805"},{"key":"ref_52","unstructured":"Coppola, C., Cosar, S., Faria, D., and Bellotto, N. (September, January 28). Automatic Detection of Human Interactions from RGB-D Data for Social Activity Classification. Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), Lisbon, Portugal."},{"key":"ref_53","unstructured":"Mohammadi, M., Al-Fuqaha, A., Guizani, M., and Oh, J.S. (2017). Semi-supervised Deep Reinforcement Learning in Support of IoT and Smart City Services. IEEE Internet Things J., 1\u201312."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Lazik, P., Rajagopal, N., Shih, O., Sinopoli, B., and Rowe, A. (2014, January 3\u20136). ALPS: A bluetooth and ultrasound platform for mapping and localization. Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems, Memphis, TN, USA.","DOI":"10.1145\/2809695.2809727"},{"key":"ref_55","unstructured":"Sikeridis, D., Papapanagiotou, I., and Devetsikiotis, M. (arXiv, 2018). BLEBeacon: A Real-Subject Trial Dataset from Mobile Bluetooth Low Energy Beacons, arXiv."},{"key":"ref_56","unstructured":"Barsocchi, P. (2006). Channel Models for Terrestrial Wireless Communications: A Survey, CNR-ISTI. CNR-ISTI Technical Report."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/12\/4462\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:34:25Z","timestamp":1760196865000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/12\/4462"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12,17]]},"references-count":56,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2018,12]]}},"alternative-id":["s18124462"],"URL":"https:\/\/doi.org\/10.3390\/s18124462","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,12,17]]}}}