Novel evolutionary-EAC instance-learning-based algorithm for fast data stream mining in assisted living with extreme connectivity

In modern healthcare, sensing technologies such as IoT empower the quality of assisted living service by knowing what a resident is doing in real-time. Using extreme connectivity and cloud computing in a smart home, where a collection of sensors is installed, the sensors sample continuously from the...

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Veröffentlicht in:	Computing Jg. 103; H. 7; S. 1519 - 1543
Hauptverfasser:	Hu, Shimin, Fong, Simon, Song, Wei, Cho, Kyungeun, Millham, Richard C., Fiaidhi, Jinan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Vienna Springer Vienna 01.07.2021 Springer Nature B.V
Schlagworte:	Approximation Artificial Intelligence Asthma Cloud computing Computer Appl. in Administrative Data Processing Computer Communication Networks Computer Science Connectivity Data processing Data transmission Evolutionary algorithms Human activity recognition Information Systems Applications (incl.Internet) Machine learning Moving object recognition Multivariate analysis Optimization Real time Regular Paper Sensors Smart buildings Smart houses Software Engineering Subgroups Subspaces Extreme connectivity 68W50 IoT data analysis Regression Assisted living Human activity recognition Forecasting
ISSN:	0010-485X, 1436-5057
Online-Zugang:	Volltext
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