Applying SARIMA time series to forecast sleeping activity for wellness model of elderly monitoring in smart home

N. K. Survadevara*, S. C. Mukhopadhyay, R. K. Rayudu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

14 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2012 6th International Conference on Sensing Technology, ICST 2012
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages157-162
Number of pages6
ISBN (Electronic)9781467322485
ISBN (Print)9781467322461
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 6th International Conference on Sensing Technology, ICST 2012 - Kolkata, India
Duration: 18 Dec 201221 Dec 2012

Other

Other2012 6th International Conference on Sensing Technology, ICST 2012
CountryIndia
CityKolkata
Period18/12/1221/12/12

    Fingerprint

Cite this

Survadevara, N. K., Mukhopadhyay, S. C., & Rayudu, R. K. (2012). Applying SARIMA time series to forecast sleeping activity for wellness model of elderly monitoring in smart home. In 2012 6th International Conference on Sensing Technology, ICST 2012 (pp. 157-162). [6461661] Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICSensT.2012.6461661