Monitoring and visualizing the daily activities and in-house locations using smartphone
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.
Authors: Sittichai Sukreep, Pornchai Mongkolnam, Chakarida Nukoolkit
Published in: International Joint Conference on Computer Science and Software Engineering (2015)