An Efficient Machine Learning Software Architecture for Internet of Things

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dc.contributor.advisorLitoiu, Marin
dc.contributor.authorChaudhary, Mahima
dc.date.accessioned2021-07-06T12:50:20Z
dc.date.available2021-07-06T12:50:20Z
dc.date.copyright2021-04
dc.date.issued2021-07-06
dc.date.updated2021-07-06T12:50:19Z
dc.degree.disciplineElectrical and Computer Engineering
dc.degree.levelMaster's
dc.degree.nameMASc - Master of Applied Science
dc.description.abstractInternet of Things (IoT) software is becoming a critical infrastructure for many domains. In IoT, sensors monitor their environment and transfer readings to cloud, where Machine Learning (ML) provides insights to decision-makers. In the healthcare domain, the IoT software designers have to consider privacy, real-time performance and cost in addition to ML accuracy. We propose an architecture that decomposes the ML lifecycle into components for deployment on a two-tier cloud, edge-core. It enables IoT time-series data to be consumed by ML models on edge-core infrastructure, with pipeline elements deployed on any tier, dynamically. The architecture feasibility and ML accuracy are validated with three brain-computer interfaces (BCI) based use-cases. The contributions are two-fold: first, we propose a novel ML-IoT pipeline software architecture that encompasses essential components from data ingestion to runtime use of ML models; second, we assess the software on cognitive applications and achieve promising results in comparison to literature.
dc.identifier.urihttp://hdl.handle.net/10315/38477
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectNeurosciences
dc.subject.keywordsmachine learning
dc.subject.keywordsbrain-computer interface
dc.subject.keywordswearable devices
dc.subject.keywordsinternet of things
dc.subject.keywordssoftware architecture
dc.titleAn Efficient Machine Learning Software Architecture for Internet of Things
dc.typeElectronic Thesis or Dissertation

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