Automated Facemask Detection and Monitoring of Body Temperature using IoT Enabled Smart Door

Yerrababu Moukthika Reddy, Mounika Nadampalli, Asisa Kumar Panigrahy, Kunduri Surya Divyasree, A. Jahnavi, N. Vignesh
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引用次数: 3

Abstract

Living with the novel Coronavirus is becoming the new normal as nations around the globe resume. However, in order to stop the virus from spreading, we must isolate Covid-infected persons from the rest of the population.Fever is the most common symptom of coronavirus infection, according to the CDC [1], with up to 83 percent of symptomatic patients presenting indications of fever. Early symptom detection and good hygiene standards are therefore critical, particularly in situations where people come into random contact with one another. As a result, temperature checks and masks are now required in schools, colleges, offices, and other public spaces. However, manually monitoring each individual and measuring their respective body temperatures is a cumbersome task. Currently, most of the temperature checkups are done manually which can be inefficient, impractical, and riskybecause sometimes people checking manually may be reluctant to check every person’s temperature or sometimes allow people even if they violate the guidelines. Moreover, the person assigned to manually check will be at high risk as he is exposed to a lot of people. To solve these issues, we propose a project that reduces the growth of COVID-19 by monitoring the presence of a facial mask and measuring their temperature. The Face Mask Detection can be done using the TensorFlow software library, Mobilenet V2 architecture and OpenCV.A non-contact IR temperature sensor is used to monitor the individual’s body temperature. To avoid false positives, the system will be strengthened by training it with a variety of cases. Once the system detects a mask, it measures the body temperature of the person. If the temperature is within the normal range, sanitization is done,and the person is permitted entry through an IOT enabled smart door. However, if the system fails to detect a mask or the person’s temperature falls out of the predefined range, a buzzer rings and the door remains closed. Our model is intended to be effective in preventing the spread of this infectious disease.
使用物联网智能门的自动口罩检测和体温监测
随着全球各国疫情恢复,与新型冠状病毒共存正成为一种新常态。然而,为了阻止病毒传播,我们必须将covid - 19感染者与其他人隔离开来。根据美国疾病控制与预防中心[1]的数据,发烧是冠状病毒感染最常见的症状,高达83%的有症状患者出现发烧症状。因此,早期发现症状和良好的卫生标准至关重要,特别是在人们彼此随机接触的情况下。因此,现在学校、学院、办公室和其他公共场所都需要进行体温检查并佩戴口罩。然而,手动监测每个人并测量他们各自的体温是一项繁琐的任务。目前,大多数体温检查都是手工完成的,这可能是低效的,不切实际的,而且有风险,因为有时手工检查的人可能不愿意检查每个人的体温,或者有时允许人们检查,即使他们违反了指导方针。此外,被指派手动检查的人将面临很高的风险,因为他与很多人接触。为了解决这些问题,我们提出了一个项目,通过监测口罩的存在并测量其温度来减少COVID-19的生长。人脸掩码检测可以使用TensorFlow软件库、Mobilenet V2架构和OpenCV来完成。非接触式红外温度传感器用于监测个人的体温。为了避免误报,该系统将通过各种案例进行训练来加强。一旦系统检测到口罩,它就会测量人的体温。如果温度在正常范围内,则完成消毒,并允许该人通过启用物联网的智能门进入。然而,如果系统没有检测到口罩,或者人的体温超出了预定的范围,蜂鸣器就会响起,门就会保持关闭状态。我们的模型旨在有效地防止这种传染病的传播。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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