SVM Classifier in IoT-Connected Doorway Thermal Scanning for Preventive Health Check Surveillance

• Published in: 2024 1st International Conference on Innovative Sustainable Technologies for Energy, Mechatronics, and Smart Systems (ISTEMS) pp. 1 - 6
• Main Authors: Srinivasan, S., Veda, Parthiban, Asha, P., Srinivasan, C., Murugan, S., Sujatha, S.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 26.04.2024
• Subjects: Abnormal Temperature Detection; Body Temperature Monitoring; COVID-19; Early Warning System; Health Anomalies; Machine learning; Public Health; Support vector machines; Temperature distribution; Temperature measurement; Temperature sensors; Thermal analysis
• DOI: 10.1109/ISTEMS60181.2024.10560231

Doorway thermal scanning with an Internet of Things (IoT) connection may determine whether a person is healthy or sick by analyzing their core body temperature using the SVM classifier machine learning (ML) algorithm. One indication of COVID-19 is a high body temperature, and this device is made to identify those with it. Taking a thermal image of the subject allows the system to determine if they are healthy or sick using the SVM classifier. With this approach, it can stop the transmission of the COVID-19 virus in public spaces like airports, hospitals, and malls. Using an IoT -connected entryway thermal scanner, it suggests a means to identify and categorize people's health state according to their core temperature. A SVM classifier, a machine learning tool for feature-based data classification, is used in the approach. Fever is a frequent indication of many illnesses, including COVID-19. This technique can reliably detect cases of fever and notify the appropriate authorities to take precautions. The pros and cons of deploying IoT devices for public health monitoring are discussed. According to the World Health Organization (WHO), thermal scanning is not a reliable way to identify COVID-19 and should not be relied upon completely.