{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T19:01:31Z","timestamp":1772823691028,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T00:00:00Z","timestamp":1588550400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The creation of an automatic crowd estimation system capable of providing reliable, real-time estimates of human crowd sizes would be an invaluable tool for organizers of large-scale events, particularly so in the context of safety management. We describe a set of experiments in which we installed a passive Radio Frequency (RF) sensor network in different environments containing thousands of human individuals and discuss the accuracy with which the resulting measurements can be used to estimate the sizes of these crowds. Depending on the selected training approach, a median crowd estimation error of 184 people could be obtained for a large scale environment which contained 3227 people at its peak. Additionally, we look into the potential benefits of dividing one of our experimental environments into multiple subregions and open up a potentially interesting new topic of research regarding the estimation of crowd flows. Finally, we investigate the combination of our measurements with another sources of crowd-related data: sales data from drink stands within the environment. In doing so, we aim to integrate the concept of an automatic RF-based crowd estimation system into the broader domain of crowd analysis.<\/jats:p>","DOI":"10.3390\/s20092624","type":"journal-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T14:00:43Z","timestamp":1588600843000},"page":"2624","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Large-Scale Crowd Analysis through the Use of Passive Radio Sensing Networks"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6447-6935","authenticated-orcid":false,"given":"Stijn","family":"Denis","sequence":"first","affiliation":[{"name":"IDLab\u2013Faculty of Applied Engineering, University of Antwerp\u2013imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2698-8128","authenticated-orcid":false,"given":"Ben","family":"Bellekens","sequence":"additional","affiliation":[{"name":"IDLab\u2013Faculty of Applied Engineering, University of Antwerp\u2013imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9280-4142","authenticated-orcid":false,"given":"Abdil","family":"Kaya","sequence":"additional","affiliation":[{"name":"IDLab\u2013Faculty of Applied Engineering, University of Antwerp\u2013imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0064-5020","authenticated-orcid":false,"given":"Rafael","family":"Berkvens","sequence":"additional","affiliation":[{"name":"IDLab\u2013Faculty of Applied Engineering, University of Antwerp\u2013imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1152-6617","authenticated-orcid":false,"given":"Maarten","family":"Weyn","sequence":"additional","affiliation":[{"name":"IDLab\u2013Faculty of Applied Engineering, University of Antwerp\u2013imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1016\/j.ssci.2016.09.006","article-title":"On current crowd management practices and the need for increased situation awareness, prediction, and intervention","volume":"91","author":"Martella","year":"2017","journal-title":"Saf. Sci."},{"key":"ref_2","unstructured":"Still, G.K. (2000). Crowd Dynamics. [Ph.D. Thesis, University of Warwick]."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Still, G.K. (2014). Introduction to Crowd Science, CRC Press.","DOI":"10.1201\/b17097"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0925-7535(96)81011-3","article-title":"Crowd psychology and engineering","volume":"21","author":"Sime","year":"1995","journal-title":"Saf. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Schadschneider, A., Klingsch, W., Kl\u00fcpfel, H., Kretz, T., Rogsch, C., and Seyfried, A. (2008). Evacuation dynamics: Empirical results, modeling and applications. arXiv.","DOI":"10.1007\/978-0-387-30440-3_187"},{"key":"ref_6","unstructured":"(2020, March 31). Homepage of Prof. Dr. G. Keith Still. Available online: https:\/\/www.gkstill.com\/CV\/Projects\/ControlRoom.html."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.engappai.2015.01.007","article-title":"Recent survey on crowd density estimation and counting for visual surveillance","volume":"41","author":"Saleh","year":"2015","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.patrec.2017.07.007","article-title":"A survey of recent advances in cnn-based single image crowd counting and density estimation","volume":"107","author":"Sindagi","year":"2018","journal-title":"Pattern Recognit. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1177\/0894439317726510","article-title":"Automated solutions for crowd size estimation","volume":"36","author":"Aziz","year":"2018","journal-title":"Soc. Sci. Comput. Rev."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1515\/popets-2017-0054","article-title":"A study of MAC address randomization in mobile devices and when it fails","volume":"2017","author":"Martin","year":"2017","journal-title":"Proc. Privacy Enhancing Technol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Youssef, M., Mah, M., and Agrawala, A. (2007, January 9\u201314). Challenges: Device-free passive localization for wireless environments. Proceedings of the 13th Annual ACM International Conference on Mobile Computing and Networking, Montreal, QC, Canada.","DOI":"10.1145\/1287853.1287880"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"7302","DOI":"10.1109\/TVT.2017.2664938","article-title":"ARTI: An adaptive radio tomographic imaging system","volume":"66","author":"Kaltiokallio","year":"2017","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1109\/MCOM.2017.8067691","article-title":"Behavior Recognition Based on Wi-Fi CSI: Part 1","volume":"55","author":"Guo","year":"2017","journal-title":"IEEE Commun. Mag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1109\/MCOM.2018.8360859","article-title":"Behavior Recognition Based on Wi-Fi CSI: Part 2","volume":"56","author":"Guo","year":"2018","journal-title":"IEEE Commun. Mag."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/JSTSP.2013.2287473","article-title":"Breathfinding: A Wireless Network That Monitors and Locates Breathing in a Home","volume":"8","author":"Patwari","year":"2014","journal-title":"J. Sel. Top. Signal Process."},{"key":"ref_16","unstructured":"Abdelnasser, H., Harras, K.A., and Youssef, M. (May, January 26). WiGest demo: A ubiquitous WiFi-based gesture recognition system. Proceedings of the Computer Communications Workshops (INFOCOM WKSHPS), Hong Kong, China."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1109\/JIOT.2016.2624800","article-title":"Device-free RF human body fall detection and localization in industrial workplaces","volume":"4","author":"Kianoush","year":"2016","journal-title":"IEEE Internet Things J."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3837","DOI":"10.1109\/JSEN.2013.2259692","article-title":"Estimating crowd density in an RF-based dynamic environment","volume":"13","author":"Yuan","year":"2013","journal-title":"IEEE Sens. J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1109\/JSAC.2015.2430272","article-title":"Occupancy estimation using only WiFi power measurements","volume":"33","author":"Depatla","year":"2015","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"8351017","DOI":"10.1155\/2016\/8351017","article-title":"A statistical approach in designing an rf-based human crowd density estimation system","volume":"12","author":"Fadhlullah","year":"2016","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Xi, W., Zhao, J., Li, X.Y., Zhao, K., Tang, S., Liu, X., and Jiang, Z. (May, January 27). Electronic frog eye: Counting crowd using WiFi. Proceedings of the IEEE INFOCOM 2014\u2014IEEE Conference on Computer Communications, Toronto, ON, Canada.","DOI":"10.1109\/INFOCOM.2014.6847958"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1109\/JIOT.2016.2563399","article-title":"Radios as Sensors","volume":"4","author":"Cianca","year":"2017","journal-title":"IEEE Internet Things J."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Kianoush, S., Savazzi, S., Rampa, V., and Nicoli, M. (2019). People Counting by Dense WiFi MIMO Networks: Channel Features and Machine Learning Algorithms. Sensors, 19.","DOI":"10.3390\/s19163450"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Denis, S., Berkvens, R., Bellekens, B., and Weyn, M. (2018, January 9\u201312). Large Scale Crowd Density Estimation Using a sub-GHz Wireless Sensor Network. Proceedings of the 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Bologna, Italy.","DOI":"10.1109\/PIMRC.2018.8580840"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Weyn, M., Ergeerts, G., Berkvens, R., Wojciechowski, B., and Tabakov, Y. (2015, January 28\u201330). DASH7 alliance protocol 1.0: Low-power, mid-range sensor and actuator communication. Proceedings of the 2015 IEEE Conference on Standards for Communications and Networking (CSCN), Tokyo, Japan.","DOI":"10.1109\/CSCN.2015.7390420"},{"key":"ref_26","unstructured":"(2020, March 31). Grafana Website. Available online: https:\/\/grafana.com\/."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kaltiokallio, O., Bocca, M., and Patwari, N. (2012, January 8\u201311). Enhancing the accuracy of radio tomographic imaging using channel diversity. Proceedings of the 2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2012), Las Vegas, NV, USA.","DOI":"10.1109\/MASS.2012.6502524"},{"key":"ref_28","first-page":"1159","article-title":"A fade level-based spatial model for radio tomographic imaging","volume":"13","author":"Kaltiokallio","year":"2013","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Bocca, M., Luong, A., Patwari, N., and Schmid, T. (July, January 30). Dial it in: Rotating RF sensors to enhance radio tomography. Proceedings of the 2014 Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), Singapore.","DOI":"10.1109\/SAHCN.2014.6990400"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Xu, C., Firner, B., Moore, R.S., Zhang, Y., Trappe, W., Howard, R., Zhang, F., and An, N. (2013, January 8\u201311). SCPL: Indoor device-free multi-subject counting and localization using radio signal strength. Proceedings of the 12th International Conference on Information Processing in Sensor Networks, Philadelphia, PA, USA.","DOI":"10.1145\/2461381.2461394"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Denis, S., Berkvens, R., and Weyn, M. (2019). A Survey on Detection, Tracking and Identification in Radio Frequency-Based Device-Free Localization. Sensors, 19.","DOI":"10.3390\/s19235329"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/9\/2624\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:52:29Z","timestamp":1760363549000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/9\/2624"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,4]]},"references-count":31,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["s20092624"],"URL":"https:\/\/doi.org\/10.3390\/s20092624","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,4]]}}}