Safety protection using artificial intelligence internet of things for preschool education

IF 0.9 Q4 TELECOMMUNICATIONS Internet Technology Letters Pub Date : 2024-05-05 DOI:10.1002/itl2.537
Yun Tan, Shuangyuan Mo
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Abstract

With the rapid development of social economy and information technology, safety protection in daily life has become more and more important. Although the awareness of safety has increased, the children's safety is still not paid enough attention. Children still may suffer accidental injuries, especially in developing countries. Children spend most of time at school in a day. Thus, it has become an emergent challenge to guarantee children's safety at school. In order handle this issue, this paper designs an Artificial Intelligence Internet of Things (AIoT) safety protection system for preschool education. The AIoT safety protection system consists of three parts: camera, Raspberry Pi, and monitoring computer. The camera captures the images of classroom scene during preschool education. The Raspberry Pi analyzes the images from camera to determine the unsafe behaviors of children, in which a YOLOv8 model is deployed. The monitoring computer receives the alarms from Raspberry Pi. The camera, Raspberry Pi, and monitoring computer are connected using wireless sensor network. The experiments show the behavior recognition model can correctly identify most of dangerous behaviors of children in classroom. The simulation result demonstrates the AIoT safety protection system can find the dangerous behaviors in time.
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利用人工智能物联网为学前教育提供安全保护
随着社会经济和信息技术的飞速发展,日常生活中的安全保护变得越来越重要。虽然人们的安全意识有所提高,但对儿童的安全仍然不够重视。儿童仍有可能遭受意外伤害,尤其是在发展中国家。儿童每天大部分时间都在学校度过。因此,如何保障儿童在学校的安全已成为一项紧迫的挑战。针对这一问题,本文设计了一种学前教育人工智能物联网(AIoT)安全保护系统。人工智能物联网安全保护系统由三部分组成:摄像头、树莓派(Raspberry Pi)和监控计算机。摄像头捕捉学前教育过程中教室场景的图像。树莓派(Raspberry Pi)通过分析摄像头的图像来判断儿童的不安全行为,并在其中部署 YOLOv8 模型。监控计算机接收来自 Raspberry Pi 的警报。摄像头、Raspberry Pi 和监控计算机通过无线传感器网络连接。实验表明,行为识别模型可以正确识别教室里孩子们的大部分危险行为。仿真结果表明,AIoT 安全保护系统能够及时发现危险行为。
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