Smart monitoring : uncovering anomalies in massive streaming time series data

dc.contributor.authorTalagala, P
dc.date.accessioned2025-01-03T03:26:46Z
dc.date.available2025-01-03T03:26:46Z
dc.date.issued2024
dc.description.abstractAnomaly detection has become a critical component of monitoring systems across various applications in the modern age of digital information and interconnected systems. From detecting infrastructure defects in civil engineering to identifying chemical hazards in environmental engineering, the ability to monitor and detect anomalies in streaming data has a significant impact on safety, efficiency, and operational continuity. With rapid advancements in data collection technology, it has become increasingly common for organizations to rely on sensors to monitor these systems.en_US
dc.identifier.doihttps://doi.org/10.31705/BPRM.v4(2).2024.2en_US
dc.identifier.issn2815-0082en_US
dc.identifier.issue2en_US
dc.identifier.journalBolgoda Plains Research Magazineen_US
dc.identifier.pgnospp. 12-16en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/23079
dc.identifier.volume4en_US
dc.identifier.year2024en_US
dc.language.isoenen_US
dc.publisherFaculty of Graduate Studiesen_US
dc.titleSmart monitoring : uncovering anomalies in massive streaming time series dataen_US
dc.typeArticle-Full-texten_US

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