Smart Home Care System with Fall Detection Based on the Android Platform

In this paper, the authors propose a smart home-care system built on an Android smartphone. The database and application programming interface (API) are set up on the server side. The database collects information from various sensors and stores it, and the API acts as a bridge between the mobile phone and the database. The API prevents the leakage of private data. In the associated Android smartphone app, two functions are provided: instant monitoring based on in-home sensor data and fall detection using the three-axis accelerometer, gyroscope, and orientation sensor inbuilt into the smartphone. When the sensor data are abnormal, the remote controller is notified immediately. Moreover, the remote controller can view real-time images by using an IP camera to guarantee home safety. As for fall detection, given that falls cause severe injuries in elder people and children, the proposed app can detect a fall event, send a help message, and indicate the user’s location by using the global positioning system and Google Maps API. According to the simulation results obtained in this study, the proposed system exhibited a fall-detection sensitivity of 92.5% and specificity of 97.6%, thus proving that the system can be effectively used for home care.

[1]  M. Brian Blake,et al.  An Internet of Things for Healthcare , 2015, IEEE Internet Comput..

[2]  Richa Singh,et al.  A Survey Paper on the impact of "Internet of Things" in Healthcare , 2019, 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA).

[3]  Widyawan,et al.  Fall detection system using accelerometer and gyroscope based on smartphone , 2014, 2014 The 1st International Conference on Information Technology, Computer, and Electrical Engineering.

[5]  Yoong Choon Chang,et al.  A simple vision-based fall detection technique for indoor video surveillance , 2015, Signal Image Video Process..

[6]  Kosin Chamnongthai,et al.  Ultrasonic array sensors for monitoring of human fall detection , 2015, 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON).

[7]  Joy Bose,et al.  Inter ecosystem compatibility for the Internet of Things using a web browser , 2018, 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC).

[8]  Cuong Pham,et al.  The Internet-of-Things based Fall Detection Using Fusion Feature , 2018, 2018 10th International Conference on Knowledge and Systems Engineering (KSE).

[9]  Octavian Postolache,et al.  A Real-Time Algorithm to Detect Falls in the Elderly , 2018, 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA).

[10]  M. Kangas,et al.  Sensitivity and False Alarm Rate of a Fall Sensor in Long-Term Fall Detection in the Elderly , 2014, Gerontology.