Title :
Applying SARIMA time series to forecast sleeping activity for wellness model of elderly monitoring in smart home
Author :
Survadevara, N.K. ; Mukhopadhyay, S.C. ; Rayudu, Ramesh K.
Author_Institution :
Massey Univ., Palmerston North, New Zealand
Abstract :
In this paper, we have reported a mechanism to forecast the sensing durations of various object usages in a smart home environment. Prognosis will assist in determining the quantitative well-being of an elderly and notify the daily activity behavior as regular or irregular. Prediction process involved in wellness model is the seasonal auto regression integration moving average routines based on the recorded sensing active status of everyday objects used by an elderly living alone.
Keywords :
assisted living; autoregressive moving average processes; biomedical communication; geriatrics; home computing; sleep; time series; SARIMA time series; daily activity behavior; elderly monitoring; sensing durations; sleeping activity forecasting; smart home environment; wellness model; Forecasting; Monitoring; Predictive models; Senior citizens; Sensors; Smart homes; Time series analysis; ADL; ARIMA Time Series; Activity Recognition; Wellnes; Wireless Sensor Networks;
Conference_Titel :
Sensing Technology (ICST), 2012 Sixth International Conference on
Conference_Location :
Kolkata
Print_ISBN :
978-1-4673-2246-1
DOI :
10.1109/ICSensT.2012.6461661
