{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T21:40:25Z","timestamp":1773524425531,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2018,6,21]],"date-time":"2018-06-21T00:00:00Z","timestamp":1529539200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Scalable real-time processing of large amounts of data has become a research topic of particular importance due to the continuously rising amount of data that is generated by devices equipped with sensing components. While existing approaches allow for fault-tolerant and scalable stream processing, we present a pipeline architecture that consists of well-known open source tools to specifically integrate spatiotemporal internet of things (IoT) data streams. In a case study, we utilize the architecture to tackle the online map matching problem, a pre-processing step for trajectory mining algorithms. Given the rising amount of vehicle location data that is generated on a daily basis, existing map matching algorithms have to be implemented in a distributed manner to be executable in a stream processing framework that provides scalability. We demonstrate how to implement state-of-the-art map matching algorithms in our distributed stream processing pipeline and analyze measured latencies.<\/jats:p>","DOI":"10.3390\/ijgi7070238","type":"journal-article","created":{"date-parts":[[2018,6,22]],"date-time":"2018-06-22T02:46:21Z","timestamp":1529635581000},"page":"238","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["A Scalable Architecture for Real-Time Stream Processing of Spatiotemporal IoT Stream Data\u2014Performance Analysis on the Example of Map Matching"],"prefix":"10.3390","volume":"7","author":[{"given":"Marius","family":"Laska","sequence":"first","affiliation":[{"name":"Geodetic Institute and Chair for Computing in Civil Engineering &amp; Geo Information Systems, RWTH Aachen University, Mies-van-der-Rohe-Str. 1, 52074 Aachen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Herle","sequence":"additional","affiliation":[{"name":"Geodetic Institute and Chair for Computing in Civil Engineering &amp; Geo Information Systems, RWTH Aachen University, Mies-van-der-Rohe-Str. 1, 52074 Aachen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2296-3401","authenticated-orcid":false,"given":"Ralf","family":"Klamma","sequence":"additional","affiliation":[{"name":"Advanced Community Information Systems Group (ACIS), RWTH Aachen University, Lehrstuhl Informatik 5, Ahornstr. 55, 52074 Aachen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5700-8818","authenticated-orcid":false,"given":"J\u00f6rg","family":"Blankenbach","sequence":"additional","affiliation":[{"name":"Geodetic Institute and Chair for Computing in Civil Engineering &amp; Geo Information Systems, RWTH Aachen University, Mies-van-der-Rohe-Str. 1, 52074 Aachen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,6,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Gali\u0107, Z. 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