Yerrababu Moukthika Reddy, Mounika Nadampalli, Asisa Kumar Panigrahy, Kunduri Surya Divyasree, A. Jahnavi, N. Vignesh
{"title":"Automated Facemask Detection and Monitoring of Body Temperature using IoT Enabled Smart Door","authors":"Yerrababu Moukthika Reddy, Mounika Nadampalli, Asisa Kumar Panigrahy, Kunduri Surya Divyasree, A. Jahnavi, N. Vignesh","doi":"10.1109/AISP53593.2022.9760551","DOIUrl":null,"url":null,"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.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"1 1","pages":"1-8"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AISP53593.2022.9760551","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.