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Fall Detection System based Internet of Things
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 Title & Authors
Fall Detection System based Internet of Things
Jeong, Pil-Seong; Cho, Yang-Hyun;
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 Abstract
Falling can happen to anyone, anywhere at anytime and especially it is one of the risk factor that can lead causes of death of persons aged 65 and over. Recently, the study of fall detection mechanisms as a smart healthcare service based on the IoT(Internet of Things) are being actively investigated. In this paper, we implement a fall detection system using arduino as a smart sensor communicates with a smart device. When transmitting the information of the acceleration on a sensor smart sensor with a BLE(Bluetooth Low Energy), the smart device processing and analyzing this information. and determines a fall situation. A fall detection system based on the Internet of Things which using smart sensor and smart device, has the advantage of being able to overcome the mobility and portability constraints.
 Keywords
Fall Detection;Arduino;Internet of Things;Accelerometer;Sensor;
 Language
Korean
 Cited by
 References
1.
Donghui Sin, Jaeyeol Jeong, Seonghyeon Kang, "Internet of Things Trend and Vision", Review of Korean Society for Internet Information, Vol.14, No.12, pp.32-46, 2013.

2.
Organization for Economi Co-operation and Development, "Dependent Population", OECE FACTBOOK, pp.16-17. 2010.

3.
Lin, C. W., Z. H. Ling, Y. C. Chang, C. J. Kuo, "Compressed-domain Fall Incident Detection for Intelligent Homecare", The Journal of VLSI Signal Processing, Vol.49, No.3, pp.393-408, 2007. crossref(new window)

4.
Zhang, T., J. Wang, L. Xu, P. Liu, "Fall Detection by Wearable Sensor and One-Class SVM Algorithm", Lecture Notes in Control and Information Sciences, pp.858-863, 2006.

5.
Zhang, T., J. Wang, P. Liu, J. Hou, "Fall Detection by Embedding in Accelerometer in Cellphone and Using KDF Algorithm", IJCSNS International Journal of Computer Science and Network Security, Vol.6, No.10, pp.277-284, 2006.

6.
Lindermann, U., A. Hock, M. Stuber, W. Keck, C. Beeker, "Evaluation of a fall detector based on accelerometers: A pilot study", Medical Biological Engineering and Computing, Vol.43, No.5, pp.548-551, 2005. crossref(new window)

7.
Bourke, A. K., G. M. Lyons, "A threshold-based fall-detection algorithm using a bi-axial gyroscope sensor", Medical Engineering and Physics, Vol.30, pp.84-90, 2008. crossref(new window)

8.
Lee, G. E., J. W. Lee, "Comparison Study of Web Application Development Environments in Smartphone", Journal of KOCON, Vol.10, No.12, pp.155-163, 2010.

9.
Pil-Seong Jeong, Yang-Hyun Cho, "Fall Detection System using Smartphone for Mobile Healthcare", Journal of the Korea society of IT services, Vol.12, No.4, pp.435-447, 2013. crossref(new window)

10.
Blueinno, http://cafe.naver.com/arduinoplusble