Non intrusive detection system for sleeping student at school

Ashardi Abas

QR Code Link :
Type :	article
Subject :	L Education
Main Author :	Ashardi Abas
Additional Authors :	Abu Bakar Ibrahim Norashiqin Mohd Idrus Nurul Ain Mohd Daud
Title :	Non intrusive detection system for sleeping student at school

Place of Production :	Tanjong Malim
Publisher :	Fakulti Seni, Komputeran dan Industri Kreatif
Year of Publication :	2019
Corporate Name :	Universiti Pendidikan Sultan Idris

Abstract : Universiti Pendidikan Sultan Idris

The role of poverty rate, medical diagnoses, napping and medication on sleep habits contribute to the academic performance of the children. The problem of sleeping student in class room is an underestimated problem in the Malaysia. The goal of our project was to produce a non-intrusive, portable and easy to use solution to detect whether or not a person was falling asleep while at classroom. The methods used in our system were sensors to detect whether or not the eye was open or closed and sensors to detect whether or not the head was dipped below a certain angle. This data was transmitted wirelessly where a microcontroller was used to determine whether or not to activate our alarm system. Our project was developed in C code and testing and verification were performed to validate the accuracy of the sensors and alarm decision system

References

1. Acebo Wolfson & Carskadon (1997). Relations among self-reported sleep patterns, health and injuries among adolescents. Journal of Sleep Research, 26, 149.

2. Buckhalt, El-Sheikh, & Keller (2007). In press. Children’s sleep and cognitive functioning: Race and socioeconomic status as moderators of effects. Child Development. AlphaLab, “IR Paper” ¬- http://www.alfalab.ca/irpaper.html

3. Ozdemir, Boysan, Selvi, Yildirim, & Yilmaz (2015)Psychometric Properties of the Turkish Version of the Sleep Hygiene Index in Clinical and NonClinical Samples. Comprehensive Psychiatry, 59, 135-14

4. Sedra, Adel & Kenneth Smith (2016). Microelectronic Circuits (The Oxford Series in Electrical and Computer Engineering). Oxford: Oxford University Press, 2016.

5. Yazdi, Sadeghniiat-Haghighi, Zohal, and Elmizadeh (2012) Validity and Re-liability of the Iranian Version of the Insomnia Severity Index. Malaysian Journal of Medical Sciences, 19, 31-36

6. Arora, Broglia, Thomas, & Taheri (2014) Associations between Specific

7. Technologies and Adolescent Sleep Quantity, Sleep Quality, and Parasomnias. Sleep Medicine, 15, 240-247

8. “Analog, Embedded Processing, Semiconductor Company, Texas Instruments - TI.com.” [Online]. Available: http://www.ti.com/. [Accessed: 05-Aug-2014].

9. “Raspberry Pi.” [Online]. Available: http://www.raspberrypi.org/. [Accessed: 05-Aug-2014]

10. M. Hallett, O. Bai, and C. Bonin, “Predicting Movement: When, Which and Where,” in 2007 IEEE/ICME International Conference on Complex Medical Engineering, 2007, pp. 5–7.

This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials.
You may use the digitized material for private study, scholarship, or research.

Back to previous page