COVID门铃——预防COVID-19的智能门铃解决方案

Abhishek Gudipalli, Vaibhav Kejriwal, Vaishnavi Patel, Riddhi M. Gupta, Utkarsh Dixit
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摘要

本文介绍了一种有效缓解COVID-19因接触任何表面而在局部传播的新策略。我们的项目旨在成为普通民众抗击疫情的关键安全盾牌。超声波传感器集成在自动门铃系统中,用手来按门铃。系统中还包括一个温度传感器Mlx90614,它记录站在门前的人的温度。该设备还包括一个摄像头模块,可以捕捉站在前门入口处的人的图像。捕获的图像通过ML模型进行处理,该模型以超过30 fps的速度运行,以检测该人是否戴着面具。站在外面的人的图像和温度通过配置的iOS应用程序发送给主人。如果外面的人戴着口罩,可以通过应用程序本身打开门,允许站在外面的人进入,从而将边缘设备与应用程序相结合,以获得更好的用户体验。该系统有助于减少物理接触,所获得的结果与现有的解决方案相当,并且具有一些优势。
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COVID bell – A smart doorbell solution for prevention of COVID-19
Abstract The article introduces a novel strategy for efficiently mitigating COVID-19 distribution at the local level due to contact with any surfaces. Our project aims to be a critical safety shield for the general people in the fight against the epidemic. An ultrasonic sensor is integrated with the automated doorbell system to ring the doorbell with a hand motion. A temperature sensor Mlx90614 is also included in the system, which records the temperature of the person standing in front of the door. The device also includes a camera module that captures the image of the person standing at the front entrance. The captured image is processed through an ML model which runs at over 30 fps to detect whether or not the person is wearing a mask. The image and the temperature of the person standing outside are sent to the owner through the configured iOS application. If the person outside is wearing a mask, one can open the door through the app itself and permit the entry of the person standing outside thereby integrating the edge device with an app for a better user experience. The system helps in reducing physical contact, and the results obtained are at par with the already existing solutions and provide a few advantages over them.
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