{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T20:11:02Z","timestamp":1770754262919,"version":"3.50.0"},"reference-count":72,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,3,7]],"date-time":"2021-03-07T00:00:00Z","timestamp":1615075200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003758","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa e ao Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico do Maranh\u00e3o","doi-asserted-by":"publisher","award":["not defined"],"award-info":[{"award-number":["not defined"]}],"id":[{"id":"10.13039\/501100003758","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The Internet of Things (IoT) has emerged from the proliferation of mobile devices and objects connected, resulting in the acquisition of periodic event flows from different devices and sensors. However, such sensors and devices can be faulty or affected by failures, have poor calibration, and produce inaccurate data and uncertain event flows in IoT applications. A prominent technique for analyzing event flows is Complex Event Processing (CEP). Uncertainty in CEP is usually observed in primitive events (i.e., sensor readings) and rules that derive complex events (i.e., high-level situations). In this paper, we investigate the identification and treatment of uncertainty in CEP-based IoT applications. We propose the DST-CEP, an approach that uses the Dempster\u2013Shafer Theory to treat uncertainties. By using this theory, our solution can combine unreliable sensor data in conflicting situations and detect correct results. DST-CEP has an architectural model for treating uncertainty in events and its propagation to processing rules. We describe a case study using the proposed approach in a multi-sensor fire outbreak detection system. We submit our solution to experiments with a real sensor dataset, and evaluate it using well-known performance metrics. The solution achieves promising results regarding Accuracy, Precision, Recall, F-measure, and ROC Curve, even when combining conflicting sensor readings. DST-CEP demonstrated to be suitable and flexible to deal with uncertainty.<\/jats:p>","DOI":"10.3390\/s21051863","type":"journal-article","created":{"date-parts":[[2021,3,7]],"date-time":"2021-03-07T21:52:15Z","timestamp":1615153935000},"page":"1863","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Dempster\u2013Shafer Theory for Modeling and Treating Uncertainty in IoT Applications Based on Complex Event Processing"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2259-4009","authenticated-orcid":false,"given":"Eduardo Devidson Costa","family":"Bezerra","sequence":"first","affiliation":[{"name":"Laboratory of Intelligent Distributed Systems (LSDi), Federal University of Maranh\u00e3o, 65080-805 S\u00e3o Lu\u00eds, Maranh\u00e3o, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0840-3870","authenticated-orcid":false,"given":"Ariel Soares","family":"Teles","sequence":"additional","affiliation":[{"name":"Laboratory of Intelligent Distributed Systems (LSDi), Federal University of Maranh\u00e3o, 65080-805 S\u00e3o Lu\u00eds, Maranh\u00e3o, Brazil"},{"name":"Federal Institute of Maranh\u00e3o, 65570-000 Araioses, Maranh\u00e3o, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7996-7334","authenticated-orcid":false,"given":"Luciano Reis","family":"Coutinho","sequence":"additional","affiliation":[{"name":"Laboratory of Intelligent Distributed Systems (LSDi), Federal University of Maranh\u00e3o, 65080-805 S\u00e3o Lu\u00eds, Maranh\u00e3o, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8339-3679","authenticated-orcid":false,"given":"Francisco Jos\u00e9","family":"da Silva e Silva","sequence":"additional","affiliation":[{"name":"Laboratory of Intelligent Distributed Systems (LSDi), Federal University of Maranh\u00e3o, 65080-805 S\u00e3o Lu\u00eds, Maranh\u00e3o, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.fss.2017.10.005","article-title":"A fuzzy expert system architecture for data and event stream processing","volume":"343","author":"Poli","year":"2018","journal-title":"Fuzzy Sets Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1497","DOI":"10.1016\/j.adhoc.2012.02.016","article-title":"Internet of Things: Vision, Applications and Research Challenges","volume":"10","author":"Miorandi","year":"2012","journal-title":"Ad Hoc Netw."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1645","DOI":"10.1016\/j.future.2013.01.010","article-title":"Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions","volume":"29","author":"Gubbi","year":"2013","journal-title":"Future Gener. 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