UV Disinfection Robots: A Review.

The novel coronavirus (COVID-19) pandemic has completely changed our lives and how we interact with the world. The pandemic has brought about a pressing need to have effective disinfection practices that can be incorporated into daily life. They are needed to limit the spread of infections through surfaces and air, particularly in public settings. Most of the current methods utilize chemical disinfectants, which can be laborious and time-consuming. Ultraviolet (UV) irradiation is a proven and powerful means of disinfection. There has been a rising interest in the implementation of UV disinfection robots by various public institutions, such as hospitals, long-term care homes, airports, and shopping malls. The use of UV-based disinfection robots could make the disinfection process faster and more efficient. The objective of this review is to equip readers with the necessary background on UV disinfection and provide relevant discussion on various aspects of UV robots.

Human Dense Avoidance Based on Coverage Control through Robots - A Patrol Algorithm Taking into Account of Visible Region

In this paper, we propose an efficient method for human dense avoidance based on a coverage control of multi-agent system. Our motivation is to contribute to an avoidance of human density in the current situation of COVID-19. We also aim to avoid crowding in social events and public spaces. Firstly, we consider a situation in which a robot autonomously patrols a region where human density occurs. As a main result, we propose a patrol algorithm in which robots distribute a cluster of humans by a coverage control if they discover them. Finally, we show an efficiency of the method based on a numerical simulation. © 2022 The Society of Instrument and Control Engineers - SICE.

Human dense avoidance based on a coverage control through robots

In this paper, we propose an efficient method for human dense avoidance based on a coverage control. Our motivation is to avoid crowding in public facilities such as stations and government offices, and human dense in the current situation of COVID‐19 from system and control theory. In this paper, humans and robots are modeled as heterogeneous and homogeneous agents, respectively, which make decisions based on their local information. We suppose a dense situation caused by the rendezvous among humans due to their own inherent dynamics. As a main result, we propose a coverage control for a distributed movement of multiple humans. We also characterize the stationary point analytically in terms of the gains that describe a strength of the interconnection of the agents, and the centers of the Voronoi regions related to the agents. Moreover, we verify the meaning of the characterization from an engineering viewpoint of the dense avoidance. Finally, we show the efficiency of the method based on a numerical simulation. [ FROM AUTHOR]

Human Dense Avoidance Based on A Coverage Control through Robots

In this paper, we propose an efficient method for human dense avoidance based on a coverage control. Our motivation is to avoid crowding in public facilities such as stations and government offices, and human dense in the current situation of COVID-19 from system and control theory. In this paper, humans and robots are modelled as heterogeneous and homogeneous agents, respectively, which make decisions based on their local information. We suppose a dense situation caused by the rendezvous among humans due to their own inherent dynamics. As a main result, we propose a coverage control for a distributed movement of multiple humans. We also characterize the stationary point analytically in terms of the the gains which describe a strength of the interconnection of the agents, and the centers of the Voronoi regions related to the agents. Moreover, we verify the meaning of the characterization from an engineering viewpoint of the dense avoidance. Finally, we show the efficiency of the method based on a numerical simulation. © 2022 The Institute of Electrical Engineers of Japan.

Next level of Hospitalisation through Smart ICU

Automation technology is developing intelligent health applications to facilitate patients by providing smart health solution. However, plethora of research is required in the autonomous robotics industry to provide smart solutions to hospitals.Hence, the proposed study aims to develop an intelligent automated infrastructure for hospitals, capable of performing several smart tasks in an Intensive Care Unit (ICU). The developed system will make food and medicine approachable by using a robotic arm on an autonomous robot. Furthermore, robotic arm can be locally controlled by the patient paramedic’s staff. The proposed intelligent robot will monitor patient’s condition by automatically monitoring the vitals conditions such as sleeping, stress, discomfort etc. This proposed system is very useful for diseases where close proximity can spread the disease, such as the covid-19 situation. Moreover, the automation will aid ICU patients by controllable bed functionality supported with patient’s EEG signals or remotely by staff. This research proposed LSTM based neural network for EEG classification and compare the results with other machine learning algorithms. The proposed LSTM network achieve 94% accuracy on self generated dataset. The achieved results are also compared with other machine learning models like SVM and Multilayer Perceptron (MLP). The intelligent navigation feature is also introduced which enables the robot to move autonomously in ICU. In addition to this, it can also establish video conference set up between the patient, staff and family members. The robot can automatically alert the staff in an emergency and assist the patient through an intelligent chatbot.

Rapid SARS-CoV-2 Inactivation in a Simulated Hospital Room Using a Mobile and Autonomous Robot Emitting Ultraviolet-C Light.

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since 2019 has made mask-wearing, physical distancing, hygiene, and disinfection complementary measures to control virus transmission. Especially for health facilities, we evaluated the efficacy of an UV-C autonomous robot to inactivate SARS-CoV-2 desiccated on potentially contaminated surfaces. ASSUM (autonomous sanitary sterilization ultraviolet machine) robot was used in an experimental box simulating a hospital intensive care unit room. Desiccated SARS-CoV-2 samples were exposed to UV-C in 2 independent runs of 5, 12, and 20 minutes. Residual virus was eluted from surfaces and viral titration was carried out in Vero E6 cells. ASSUM inactivated SARS-CoV-2 by ≥ 99.91% to ≥ 99.99% titer reduction with 12 minutes or longer of UV-C exposure and onwards and a minimum distance of 100cm between the device and the SARS-CoV-2 desiccated samples. This study demonstrates that ASSUM UV-C device is able to inactivate SARS-CoV-2 within a few minutes.