An Elderly Care System Based on Multiple Information Fusion

Abstract

With the development of social economy in the 21st century, and the rising of medical level, the aging of population have become a global trend. However lots of elderly people are in “empty nest” state. In order to solve the problem of high risk of daily life in this group, this paper proposed a method to integrate the information of video images, sound, infrared, pulse, and other information into the elderly care system. The whole system consists of four major components, that is, the main control board, the information acquisition boards, the server, and the client. The control board receives, processes and analyzes the data collected by the information acquisition boards, and uploads necessary information to the server, which are to be saved to the database. When something unexpected occurs to the elderly, the system will notify the relatives through the GPRS (general packet radio service) module. The system also provides an interface for the relatives to inquire the living status of the elderly through an app. The system can monitor the living status for the elderly with the characteristics of quick response, high accuracy, and low cost and can be widely applied to the elderly care at home.

Activity Detection from Electricity Consumption and Communication Usage Data for Monitoring Lonely Deaths

“…IoT Device Utility or Communication Data Activity detection [1,2,4,[11][12][13][14], [6][7][8][9] * [16][17][18][19][20][21] Anomaly detection [3,5,10], [6][7][8][9] * [22][23][24][25][26][27][28][29] * Studies that used both analysis methods.…”

“…In other words, the activation of an appliance at a certain time can be defined by Equation (2). Because the total electricity consumption (C T ) is measured and provided as raw data for a service, if the base load is obtained by the above logic, the activation of an appliance can be captured.…”

“…A similar result occurs in other positioning methods, such as triangular or primary cell (pCELL), using the signal strength with the base station. Figure 11 shows an example in which the cell list of the strongest signal strength is changed from (1,2,3) to (1,3,4) according to the user's movement from left to right within a certain small area. The positioning result was also changed from P 0 to P 1 using the triangular positioning method.…”

“…Thus, attempts have been made to provide information communication technology (ICT) based services to alleviate this problem. Most of these services monitor the condition of single persons in real-time through the internet of things (IoT) sensors or smartphone apps [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ]. Furthermore, the methods of capturing abnormal states are mainstream.…”

GBDT-Based Fall Detection with Comprehensive Data from Posture Sensor and Human Skeleton Extraction

“…The single drawback of the above methods is that Kinect camera is not cheap since a considerable computational power is needed to execute image processing algorithms. He et al [ 23 ] propose a method to integrate the information of video images, sound, infrared, pulse, and other information into the elderly care system. However, it is not very realistic to detect fall accidents with so many sensors.…”