{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T10:13:22Z","timestamp":1783937602015,"version":"3.55.0"},"reference-count":57,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2020,10,15]],"date-time":"2020-10-15T00:00:00Z","timestamp":1602720000000},"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>Queue systems are practically used in various institutions and commercial enterprises constituting a challenge for the intelligent environments in smart cities. The management of the flow of customers guarantees the elimination or reduction of the queues as well as the economic benefits which follow the clients\u2019 satisfaction of a better quality of service. An intelligent queue management system has been proposed which is designed as the pro-active and context-aware ecosystem based on multiple low-level sensors and devices constituting the IoT (Internet of Things) network. The designed context-driven system is characterised by user friendliness, as well as the client behaviour recognition and understanding which generate actions that support clients, establishing wealthy environments. A prototype version of the system has been proposed which has been validated by formal analysis and simulation. This prototype can be used as a necessary experience and as a reference point when building a target system and meeting requirements typical for context-aware and pro-active systems based on IoT networks which process massive data streams.<\/jats:p>","DOI":"10.3390\/s20205837","type":"journal-article","created":{"date-parts":[[2020,10,15]],"date-time":"2020-10-15T09:02:03Z","timestamp":1602752523000},"page":"5837","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Sensor-Enabled Context-Aware and Pro-Active Queue Management Systems in Intelligent Environments"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9061-561X","authenticated-orcid":false,"given":"Rados\u0142aw","family":"Klimek","sequence":"first","affiliation":[{"name":"Department of Applied Computer Science, AGH University of Science and Technology, Al. 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