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2021 | OriginalPaper | Chapter

Human Detector Smart Sensor for Autonomous Disinfection Mobile Robot

Authors : Hugo Mendonça, José Lima, Paulo Costa, António Paulo Moreira, Filipe Santos

Published in: Optimization, Learning Algorithms and Applications

Publisher: Springer International Publishing

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Abstract

The COVID-19 virus outbreak led to the need of developing smart disinfection systems, not only to protect the people that usually frequent public spaces but also to protect those who have to subject themselves to the contaminated areas. In this paper it is developed a human detector smart sensor for autonomous disinfection mobile robot that use Ultra Violet C type light for the disinfection task and stops the disinfection system when a human is detected around the robot in all directions. UVC light is dangerous for humans and thus the need for a human detection system that will protect them by disabling the disinfection process, as soon as a person is detected. This system uses a Raspberry Pi Camera with a Single Shot Detector (SSD) Mobilenet neural network to identify and detect persons. It also has a FLIR 3.5 Thermal camera that measures temperatures that are used to detect humans when within a certain range of temperatures. The normal human skin temperature is the reference value for the range definition. The results show that the fusion of both sensors data improves the system performance, compared to when the sensors are used individually. One of the tests performed proves that the system is able to distinguish a person in a picture from a real person by fusing the thermal camera and the visible light camera data. The detection results validate the proposed system.

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Title: Human Detector Smart Sensor for Autonomous Disinfection Mobile Robot
Authors: Hugo Mendonça
José Lima
Paulo Costa
António Paulo Moreira
Filipe Santos
Publisher: Springer International Publishing
Book: Optimization, Learning Algorithms and Applications
Print ISBN: 978-3-030-91884-2

Electronic ISBN: 978-3-030-91885-9

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-91885-9_13

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