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An Experimental Investigation into the Performance Characteristics of TiO2/Ethylene Glycol Nanofluid Flowing in a Horizontal Counterflow Heat Exchanger Read chapter Read first chapter

2022 | OriginalPaper | Chapter

33. Vision-Based Real-Time Hand Wash Accuracy Prediction

Authors : C. Kavinkumar, S. Tony Geefus, Prashant R. Nair

Published in: Intelligent Manufacturing and Energy Sustainability

Publisher: Springer Singapore

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Abstract

Hands are the primary means of germ transmission, which results in the transmission of deadly diseases. Hand hygiene is thus an important measure to prevent the spread of harmful diseases. The World Health Organization (WHO) has recommended seven steps for proper handwashing hygiene. However, not everyone adheres to the WHO’s handwashing guidelines of seven steps. A proper hand wash is an important factor in protecting people’s health during the corona virus disease (COVID-19) pandemic, especially for healthcare workers who are exposed to bacteria, influenza, and other infectious diseases. There are technologies available like ultraviolet (UV) images to check a person’s hand hygiene. However, there is no real-time system to monitor how efficiently a person makes his or her hand wash. A real-time monitoring system is needed to check people’s hand wash hygiene in public places and hospitals, reducing the risk of spreading communicable diseases. In this paper, we have discussed predicting the accuracy of handwashing actions performed by humans using a deep learning model with transfer learning (VGG16).

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Metadata
Title
Vision-Based Real-Time Hand Wash Accuracy Prediction
Authors
C. Kavinkumar
S. Tony Geefus
Prashant R. Nair
Copyright Year
2022
Publisher
Springer Singapore
Book
Intelligent Manufacturing and Energy Sustainability

Print ISBN: 978-981-16-6481-6

Electronic ISBN: 978-981-16-6482-3

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-981-16-6482-3_33

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