An Ultraviolet Germicidal Irradiation Autonomous Robot

Abstract

Utilization of UV light for disinfection and sterilization has increased as a result of its germicidal properties; nevertheless, due to its adverse effects on the skin and eyes, this poses a risk to individuals. The demand for autonomous UV robots originates from the requirement that UV disinfection must occur without human intervention in order to minimize health risks and take advantage of UV light as a disinfection mechanism. This study focuses on the development of a UV disinfection robot that navigates autonomously via obstacle detection and avoidance using Raspberry Pi 4 model B interfaced with UV light and YOLOv4 for high touch object detection. The UV disinfection robot uses object detection to find objects that come into touch with hands frequently and successfully cleans them with UV light. The robot uses an embedded system with a Raspberry-Pi controller, motion sensors, and detects human presence because UV radiation may be harmful to humans. Without human intervention, the autonomous UV disinfection system was effective in cleaning surfaces. Based on the findings in this study, the dosimeter showed a very faint purple tint at 10, 20, and 30 minutes that ranges from 0 to 25 mJ/cm2. Between 45 and 60 minutes, and between 25 and 50 mJ/cm2, the dosimeter exhibited a vivid purple color. These results showed that even though different bacteria require different exposure durations to become inactive, a minimum disinfection time of 10 minutes is required to conduct any type of disinfection.

Keywords

• Autonomous robot
• Convolutional network
• Germicidal irradiation
• LED
• Ultraviolet light

Bir Ultraviyole Antiseptik Işınlama Otonom Robo

Abstract

UV ışığının antiseptik özelliklerinin bir sonucu olarak dezenfeksiyon ve sterilizasyon amacıyla kullanımı artmıştır; ancak cilt ve gözler üzerindeki olumsuz etkileri nedeniyle bireyler için risk oluşturmaktadır. Otonom UV robotlarına olan talep, sağlık risklerini en aza indirmek ve bir dezenfeksiyon mekanizması olarak UV ışığından yararlanmak için UV dezenfeksiyonunun insan müdahalesi olmadan gerçekleşmesi gerekliliğinden kaynaklanmaktadır. Bu çalışma, yüksek temaslı nesne tespiti için UV ışığı ve YOLOv4 ile ara yüzlenen Raspberry Pi 4 model B'yi kullanarak engel tespiti ve kaçınma yoluyla otonom olarak hareket eden bir UV dezenfeksiyon robotunun geliştirilmesine odaklanmaktadır. UV dezenfeksiyon robotu, ellerle sık temas eden nesneleri bulmak için nesne algılamayı kullanır ve bunları UV ışığıyla başarılı bir şekilde temizler. Robot, Raspberry-Pi denetleyicisi ve hareket sensörleri içeren gömülü bir sistem kullanıyor ve UV radyasyonu insanlara zararlı olabileceğinden insan varlığını tespit ediyor. Otonom UV dezenfeksiyon sistemi, insan müdahalesi olmadan yüzeylerin temizlenmesinde etkili oldu. Bu çalışmadaki bulgulara göre dozimetre, 10, 20 ve 30. dakikada 0 ile 25 mJ/cm2 arasında değişen çok soluk bir mor renk tonu gösterdi. 45 ile 60 dakika arasında ve 25 ila 50 mJ/cm2 arasında dozimetre canlı mor renk sergiledi. Bu sonuçlar, farklı bakterilerin inaktif hale gelmeleri için farklı maruz kalma sürelerine ihtiyaç duymalarına rağmen, herhangi bir dezenfeksiyon türünün gerçekleştirilmesi için minimum 10 dakikalık bir dezenfeksiyon süresinin gerekli olduğunu gösterdi.

Keywords

• Otonom robot
• Evrişimli ağ
• Antiseptik ışınlama
• LED
• Ultraviyole ışık

References

1. [1] Guettari M, Gharbi I, Hamza S. "UVC disinfection robot". Environmental Science and Pollution Research, 28, 40394–40399, 2021. doi: 10.1007/s11356-020-11184-2
2. [2] Sanchez AG, Smart WD. “Verifiable Surface Disinfection Using Ultraviolet Light with a Mobile Manipulation Robot”. Technologies, 10, 48, 2022.
3. [3] McGinn C, Scott R, Ryan C, Donnelly N, Cullinan MF, Beckett M. “Rapid disinfection of radiology treatment rooms using an autonomous ultraviolet germicidal irradiation robot”. American Journal of Infection Control, 50(8), 947-953, 2022.
4. [4] Schahawi MD, Zingg W, Vos M, Humphreys H, Lopez-Cerero L, Fueszi A, Zahar JR, Presterl E. "Ultraviolet disinfectioonrobots to improve hospital cleaning: Real promise or just a gimmick? Antimicrobial Resistance & Infection Control, 10, 33, 2021.
5. [5] de Zoysa H, Morecroft E. "Cleaning, disinfection and sterilization of equipment". Anaesthesia & Intensive Care Medicine, 8(11), 453–456, 2007.
6. [6] Mehta I, Hsueh H, Taghipour S, Li W, Saeedi S. "UV disinfection robots: a review". Robotics and Autonomous Systems, 161, 104332, 2023.
7. [7] Dancer SJ. "Controlling hospital-acquired infection: Focus on the role of the environment and new technologies for decontamination". Clinical Microbiology Reviews, 27(4), 665 - 690, 2014.
8. [8] Vyshnavi A., Manasa AN, Hamsika SS, Shalini P. “UV Disinfection robot with automatic switching on human detection”. EAI Endorsed Transactions on Internet of Things, 6(23), 1-6, 2020.

9. [9] UVO3. “The History of Water Treatment”. https://www.uvo3.co.uk/the-history-of-uv-disinfection-uvo3/ (18.12.2022).
10. [10] HEPACART. “Far-UV VS. Near-UV”. https://www.hepacart.com/blog/far-uv-vs.-near-uv (31.05.2017)
11. [11] World Health Organization, “Radiation: Ultraviolet (UV) radiation”. https://www.who.int/news-room/questions-and-answers/item/radiation-ultraviolet (uv)#:~:text=The%20UV%20region%20covers%20the,(100%2D280%20nm) (26.09.2023).
12. [12] Brandt K.S. “Why UV light is one of the most effective ways to sanitize your home”. https://www.insider.com/does-uv-light-kill-germs (18.12.2022).
13. [13] Mehta I, Hsueh HY, Taghipour S, Li W, Saeedi S. “UV disinfection robots: A Review”. Robotics and Autonomous Systems, 161, 104332, 2023.
14. [14] Ackerman E. “Autonomous robots are helping kill coronavirus in Hospitals”. IEEE Spectrum. https://spectrum.ieee.org/autonomous-robots-are-helping-kill-coronavirus-in-hospitals (08.01.2023).
15. [15] Anderson, M. “UV light might keep the world safe from the coronavirus-and whatever comes next”. IEEE Spectrum. https://spectrum.ieee.org/uv-light-might-keep-the-world-safe-from-the-coronavirusand-whatever-comes-next (09.01.2023).
16. [16] Building Momentum. “UV-C robot 2.0: After a design sprint and the completion of a first prototype, building momentum's UV-C robot is stronger and more powerful than ever”. https://web.facebook.com/watch/?v=636986286901250 (08.01.2023).
17. [17] Shen Y. Guo D, Long F, Mateos LA, Ding H, Xiu Z, Hellman RB, King A, Chen S, Zhang C, Tan H. “Robots under covid-19 pandemic: A comprehensive survey”. IEEE Access, 9, 1590–1615, 2021.
18. [18] McGinn C, Scott R, Donnelly N, Roberts KL, Bogue M, Kiernan C, Beckett M. “Exploring the applicability of robot-assisted UV disinfection in Radiology”. Frontiers in Robotics and AI, 7, 1-12, 2021
19. [19] Ackerman E. “Akara Robotics turns Turtlebot into autonomous UV disinfecting robot”. IEEE Spectrum. https://spectrum.ieee.org/akara-robotics-turtlebot-autonomous-uv-disinfecting-robot (27.04.2020).
20. [20] Simmons SE, Carrion R, Alfson KJ, Staples HM, Jinadatha C, Jarvis WR, Sampathkumar P, Chemaly RF, Khawaja F, Povroz-nik M, Jackson S, Kaye KS, Rodriguez RM, Stibich MA. “Deactivation of SARS-COV-2 with pulsed-xenon ultraviolet light: Implications for environmental covid-19 control”. Infection Control & Hospital Epidemiology, 42(2), 127–130, 2020.
21. [21] Hyun KS. “KIST’s Efforts to Overcome COVID-19”. Korean Institute of Science and Technology. https://www.kist.re.kr/_attach/kist/old/9/2021112511482543_0.pdf (08.01.2023).
22. [22] Moore SK “Flight of the GERMFALCON: How a potential coronavirus-killing airplane sterilizer was born”. IEEE Spectrum. IEEE Spectrum. https://spectrum.ieee.org/germfalcon-coronavirus-airplane-ultraviolet-sterilizer-news (Accessed: 08.01.2023).
23. [23] Chanprakon P, Sae-Oung T, Treebupachatsakul T, Hannanta-Anan P, Piyawattanametha W. “An ultra-violet sterilization robot for disinfection”. Proceeding - 5th International Conference on Engineering, Applied Sciences and Technology, 2019.
24. [24] Perminov S, Mikhailovskiy N, Sedunin A, Okunevich I, Kalinov I, Kurenkov M, Tsetserukou D. “UltraBot: Autonomous Mobile Robot for Indoor UVC Disinfection”. IEEE 17th International Conference on Automation Science and Engineering (CASE), 2147-2152, 2021.
25. [25] Bochkovskiy A, Wang C, Liao HM. “YOLOv4: Optimal speed and accuracy of object detection”. ArXiv, abs/2004.10934, 1-17, 2020.
26. [26] Li Y, Wang H, Dang LM, Nguyen TN, Han D, Lee A, Jang I, Moon H. “A deep learning-based hybrid framework for object detection and recognition in autonomous driving”. IEEE Access, 8, 194228–194239, 2020.
27. [27] Liu H, Fan K, Ouyang Q, Li N. “Real-time small drones detection based on pruned yolov4”. Sensors, 21(10), 3374, 2021.
28. [28] He K, Zhang X, Ren S, Sun J. “Spatial pyramid pooling in deep convolutional networks for visual recognition”. IEEE transactions on pattern analysis and machine intelligence, 37(9), 1904–1916, 2015.
29. [29] Liu S, Qi L, Qin H, Shi J, Jia J. “Path aggregation network for instance segmentation”. IEEE conference on computer vision and pattern recognition, 8759–8768, 2018.
30. [30] Pounder L. “Raspberry Pi Gpio Pinout: What each pin does on PI 4, earlier models, Tom’s Hardware”. https://www.tomshardware.com/reviews/raspberry-pi-gpio-pinout,6122.html#:~:text=The%20operating%20voltage%20of%20the,(see%20resistor%20color%20codes) (12.04.2023).
31. [31] UV Light Technology. “UVC dose required to kill microorganisms”. Available at: https://uv-light.co.uk/uv-dosage-required-to-kill-microorganisms/ (24.06.2023).