Monitoring and visualizing the daily activities and in-house locations using smartphone

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Publication Details

Author listSukreep S., Mongkolnam P., Nukoolkit C.

PublisherHindawi

Publication year2015

Start page291

End page296

Number of pages6

ISBN9781479919659

ISSN0146-9428

eISSN1745-4557

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84945980352&doi=10.1109%2fJCSSE.2015.7219812&partnerID=40&md5=c3c76dd333360e925636b397ab331b59

LanguagesEnglish-Great Britain (EN-GB)


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Abstract

Fall is a leading cause of accidental injury deaths and a key cause of significant health problems, especially for elderly people who live alone. To assist those people for seeking help when falling and keeping records of key daily movements, we propose a simple yet effective system to monitor the daily activities and in-house locations using smartphone. We also test the system for the optimum arrangement of our Wi-Fi access points. First, the data mining classification is applied through the threshold model to detect the common activities like sitting, standing, lying down, walking, running, walking up/downstairs, falling, and in-house locations. Then the system gives out a warning when unhealthy activities or falls are detected, using an alarm sound and short messages sent to those who are in contact or caretakers. In addition, it provides various forms of visualization such as a health risk level summary, daily activity summary, and in-house location summary. ฉ 2015 IEEE.


Keywords

Daily ActivitiesHealth RisksIn-house Locations


Last updated on 2023-28-09 at 07:35