Discovering Human Activities from Binary Data in Smart Homes
With the rapid development in sensing technology, data mining, and machine learning fields for human health monitoring, it became possible to enable monitoring of personal motion and vital signs in a manner that minimizes the disruption of an individual’s daily routine and assist individuals with di...
Main Authors: | Mohamed Eldib, Wilfried Philips, Hamid Aghajan |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-04-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/9/2513 |
Similar Items
-
Riding the IoT Wave With VFuzz: Discovering Security Flaws in Smart Homes
by: Carlos Kayembe Nkuba, et al.
Published: (2022-01-01) -
Design and Evaluation of a Solo-Resident Smart Home Testbed for Mobility Pattern Monitoring and Behavioural Assessment
by: Mohsen Shirali, et al.
Published: (2020-12-01) -
Data mining and knowledge discovery in chemical processes: Effect of alternative processing techniques
by: Luis A. Briceno-Mena, et al.
Published: (2022-01-01) -
Future Activities Prediction Framework in Smart Homes Environment
by: Mai Mohamed, et al.
Published: (2022-01-01) -
Periodic Behavioral Routine Discovery Based on Implicit Spatial Correlations for Smart Home
by: Chun-Chih Lo, et al.
Published: (2023-01-01)