| Summary: | In recent years, pupils' health has been taken into consideration more than ever, and the raising of correcting posture in humans or specifically pupils posture was extremely noticeable. The purpose of this project is to propose a system using a wireless sensor network integrating a body tilt sensor, an infrared proximity sensor, a particle dust sensor, and a camera to detect children's drowsiness states using a neural-network-based facial landmark detection. The monitoring of children's posture operates based on their body movements and the distance of their eyes to the table, when the sensor detects an accepted limitation exceeding the parameter, the device will alert so that the pupils can recorrect their sitting posture. We also created a website for remote tracking and saving data on children's posture. The accuracy and the effectiveness of the system has been verified by various experiments and give promising results. We expect that this system can be effective and easily operate so that people can utilize it to upgrade their quality of life. © 2023 Lavoisier. All rights reserved.
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