Automatic Detection and Alert of Fall in a Restroom by Infrared Sensor

Main Article Content

Kornkanok Saranan
Nuntiya Chaiyabut


This paper presents the automatic detection and alert of fall in a restroom which is developed by internet of things (IoT) concept. The system consists of sensors, microcontroller, transmitter, and receiver device. The data are measured by infrared distance sensors and sent to the microcontroller. In this paper, Arduino Uno is used for processing the fall. Then the results of processing are transmitted to the cloud by Node MCU. The receiver device is a mobile phone. The alert signal is sent to Line application on a mobile phone when a fall in a restroom appears. Moreover, we develop the application for the Android operating system on mobile devices. This application is designed to facilitate the request for help as specified by the user. The test result of the automatic detection and alert system is the system can alert through the Line application on mobile devices for every ten seconds after the fall event occurs with 98 percent accuracy.  

Article Details

How to Cite
Saranan, K. ., & Chaiyabut, N. (2020). Automatic Detection and Alert of Fall in a Restroom by Infrared Sensor. Naresuan University Engineering Journal, 15(1), 44–52. Retrieved from
Research Paper


NHESO. (2009). Report of the Thai public health survey by physical examination (2008 - 2009).

Ministry of public health. (2019, 20 December). Data on the number and rate of death from falls in the elderly ICD10 (W00 – W19).

Kido, S., Miyasaka, T., Tanaka, T., Shimizu, T., & Saga, T. (2009, January 29). Fall detection in toilet rooms using thermal imaging sensors [Paper presentation]. 2009 IEEE/SICE International Symposium on System Integration (SII), Tokyo, Japan.

Shirogane, S., Takahashi, H., Murata, K., Kido, S., Miyasaka, T., Saga, T., Sakurai, S., Hamaguchi, T., & Tanaka, T. (2019). Use of Thermal Sensors for Fall Detection in a Simulated Toilet Environment. International Journal of New Technology and Research (IJNTR), 5(11), 21–25.

Chotikawanich, T. (2012). An Embedded System for Fall Detection While Showering by a Privacy Camera [Master's Thesis]. Prince of Songkla University.

de Miguel, K., Brunete, A., Hernando, M., & Gambao, E. (2017). Home Camera-Based Fall Detection System for the Elderly. Sensors (Basel), Multidisciplinary Digital Publishing Institute (MDPI), 17(12), 1 – 31.

Thawornwong, N., Akarasatthung, A., & Makasorn, P. (2011). Designing of Falls Detection for Elderly by Using Tilt Sensor. Naresuan University Journal, Special Issue, 43–46.

Kanjananoppawong, J., & Puttha, K. (2013). Fall Behavior Detection System using 3-Axis Accelerometer by FiO Std Board [Bachelor's Thesis]. Nakhon Ratchasima. Suranaree university of technology.

Sompang, P., & Jaruwittayakowit, T. (2017, November 1-2). 2D Fall Detection with Bluetooth Accelerometer Sensor. 9th National Conference on Information Technology, NCIT.

Mattern, F., & Floerkemeier, C. (2010). From Internet of Computers to the Internet of Thinks. Springer-Verlag Berlin.

Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014). Context-Aware Computing for The Internet of Things: A Survey. IEEE Communications Surveys & Tutorials, 6(1), 414–454.

Casini, M. (2014). Internet of things for Energy efficiency of buildings. International Scientific Journal Architecture and Engineering, 29, 1–5.

Nilrak, P., Yatdon, W., & Chaiyabut, N. (2018). Alert System of Solar Panels Operation. Engineering Journal Chiang Mai University, 25(2), 124 – 134.

Sparkfun. (2019, January 29). Sharp GP2Y0A02.

Wangsuphachart, S. (2018, October 29). Research Design & Research Methodology.

Dounghaklang, P., Sreesompan, P., & Batchinger, R. (2017). Real-world Applications Development with MIT App Inventor. Apheit journals, 6(1), 80–91.

National Electronics and Computer Technology Center. (2009, October 29). survey results of size nationwide.

Kitisomprayoonkul, W. (2018, October 29). Falling and prevention.