Main Article Content
The trend of the age proportion of the Thai population is completely stepping into an aging society. One of the main problems is that the elderly being left alone spend their lives to do daily activities difficultly due to physical changes. For example, falls in the elderly are the most common accidents. Therefore the objectives of this research are (1) to develop an alarm and monitoring system for the elderly when the elderly have an accident or injury, and (2) to develop a WiFi network inside residences to bridge data communication between wireless sensing devices and the Raspberry Pi board used as a main controller. The wireless sensing devices used to detect abnormal and emergency situations included a fall detector with an accelerometer, a motion detector with a camera and a distance sensor, and an emergency push button. When emergency situations were detected according to the pre-defined conditions, i.e., falling or pressing an emergency push button, or no motion within some time intervals, the Raspberry Pi board sent an SMS to a caregiver automatically. The experimental results showed that the intended objectives were achieved when the alarm and monitoring system was tested in both simulation scenarios and real-world situations.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Article Accepting Policy
The editorial board of Thai-Nichi Institute of Technology is pleased to receive articles from lecturers and experts in the fields of business administration, languages, engineering and technology written in Thai or English. The academic work submitted for publication must not be published in any other publication before and must not be under consideration of other journal submissions. Therefore, those interested in participating in the dissemination of work and knowledge can submit their article to the editorial board for further submission to the screening committee to consider publishing in the journal. The articles that can be published include solely research articles. Interested persons can prepare their articles by reviewing recommendations for article authors.
Copyright infringement is solely the responsibility of the author(s) of the article. Articles that have been published must be screened and reviewed for quality from qualified experts approved by the editorial board.
The text that appears within each article published in this research journal is a personal opinion of each author, nothing related to Thai-Nichi Institute of Technology, and other faculty members in the institution in any way. Responsibilities and accuracy for the content of each article are owned by each author. If there is any mistake, each author will be responsible for his/her own article(s).
The editorial board reserves the right not to bring any content, views or comments of articles in the Journal of Thai-Nichi Institute of Technology to publish before receiving permission from the authorized author(s) in writing. The published work is the copyright of the Journal of Thai-Nichi Institute of Technology.
 Y.S. Delahoz and M.A. Labrador, “Survey on fall detection and fall prevention using wearable and external sensors,” Sensors, vol. 14, no. 10, pp. 19806–19842, 2014.
 S. Eamsamai, R. Mhuansit and C. Thongmag, “An elderly care model among caregiving volunteers at Phukrang municipality, Amphur Praputthabat, Saraburi province,” (In Thai). Nursing Journal of the Ministry of Public Health, vol. 22, no. 3, pp. 77-87, 2012.
 T. Yu, A. Stamm and R. Hartanto, “Design and implementation of a Bluetooth low energy-based local area network for fall detection,” in Proc. 12th Conference of the International Sports Engineering Association, Queensland, Australia, March 26-29, 2018.
 Y. Lee, H. Yeh, K. Kim and O. Choi, “A real-time fall detection system based on the acceleration sensor of smartphone,” International Journal of Engineering Business Management, vol. 10, pp. 1–8, 2018.
 C. Ko, F. Leu and I. Lin, “A wandering path tracking and fall detection system for people with dementia,” in Proc. 9th International Conference on Broadband and Wireless Computing, Communication and Applications, Guangdong, China, November 8-10, 2014.
 Y. Xiang, Y. Tang, B. Ma, H. Yan, J. Jiang and X. Tia, “Remote safety monitoring for elderly persons based on omni-vision analysis,” PLoS ONE, vol. 10, no. 5, e0124068, 2015.
 L.H. Juang and M.N. Wu, “Fall down detection under smart home system,” Journal of Medical Systems, vol. 39, no. 10, pp. 1–12, 2015.
 W. Zhuang, X. Sun, Y Zhi, Y. Han and H. Mao. “A novel wearable smart button system for fall detection,” in Proc. the 1st International Conference on Materials Science, Energy Technology, Power Engineering (MEP 2017), Hangzhou, China, April 15-16, 2017, pp. 020075-1 - 020075-6.
 V. Muenruekam, V. Sudkratok, S. Surarochprajak and T. Thongkrau, “Automatic accident alert system using multi-layer perceptron,” (In Thai).TNI Journal of Engineering and Technology, vol. 5, no. 2, pp. 49 – 53, 2017.