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2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2018772

ABSTRACT

In this work, a cost-effective disinfection system for Coronavirus Disease of 2019 (COVID-19) is proposed to be used inside public transport. The disinfection system is twofold, firstly containing a tower unit where UV-C (Ultraviolet type-C) lamps are positioned in parallel, in such a way that, 360-degree space is covered, and secondly a power unit that incorporates robotics and electrical parts. The UVC unit is a separate and movable tower that can be placed anywhere inside a vehicle horizontally or vertically. UV lamps in the tower have a 254 nm wavelength with a total power of 180 Watt. The system can provide a dose of it 16.9 mj/cm2 within 26.83 seconds if the distance of the targeted surface inside a vehicle from the UVC light source is 1.5 meters. Various distances from the UV source to the targeted surface inside the vehicle are chosen and calculated the required corresponding times to achieve the required dose to inactivate all viral concentrations. The developed disinfection system not only minimizes the growth of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by performing robotic features ensuring human detection auto turn off but also utilizes minimum labor work which is vital in the current Covid-19 pandemic. © 2022 IEEE.

2.
6th International Conference on Inventive Systems and Control, ICISC 2022 ; 436:775-788, 2022.
Article in English | Scopus | ID: covidwho-2014003

ABSTRACT

This study is divided into risk factor analysis (RFA) and proposed system architecture (PSA). The light gradient boosting machine (LightGBM) algorithm in the RFA will work with the PSA to predict the risk factors. The results, efficacy, and performance will be validated via a ROC-AUC curve. Therefore, a system usability scale (SUS) procedure will be implemented to increase the performance. If the SUS score reaches 85–99 and 100 thresholds, it will be classified as appropriate for use and robust. The prediction score thresholds will be 0–100. If the score is below 25, it will be classified as normal, 26–50 as moderate, 51–70 risk, and 71–100 as severe. Due to a shortage of experienced staff and intelligent technology, it is becoming progressively difficult to reduce COVID-19 fatality rates. In this research, a lightweight mobile application has been suggested from which the significant patterns and factors can be recognised. Furthermore, it will assist both doctors and patients become aware of COVID-19 risk factors and take the required steps to mitigate them. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

3.
2021 International Conference on Electronics, Communications and Information Technology, ICECIT 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1685081

ABSTRACT

In this study, a low-cost Ultraviolet disinfection system is proposed to be used inside ambulances for minimizing the cross-infection of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) during patient transfer. The disinfection system consists of a tower unit that contains the Ultraviolet type C (UVC) light fixture and a control box where the power unit is placed. The UVC tower unit is portable, lightweight, and can be easily placed anywhere inside an ambulance. Two ultraviolet (UV) lamps used in the tower part have 254 nm wavelength with a total power of 180 Watt. The disinfection system can provide a dose of 16.9mj/cm2 within 1.06 seconds and 26.83 seconds if the distance of the targeted surface inside the ambulance from UV sources are 0.3 meters and 1.5 meters respectively. We have chosen various distances from UV source to targeted surface inside an ambulance and calculated the required corresponding times to reach the required dose to inactivate all viral concentrations. The designed disinfection system not only reduces the spread of SARS-CoV-2 by the semi-autonomous way inside ambulances but also requires the least labor efforts which are crucial in the current Covid-19 pandemic. © 2021 IEEE.

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