IDEAS home Printed from https://ideas.repec.org/a/epw/ejece0/v6y2022i1id19383.html

Robot-Assisted Ultraviolet Disinfector with Dispenser for Healthcare Related Services

Author

Listed:
  • Shatrughna Prasad Yadav

    (Guru Nanak Institute of Technology, India)

  • Sai Kumar

    (Guru Nanak Institute of Technology, India)

  • Boddu Devika

    (Guru Nanak Institute of Technology, India)

  • Kolluri Rahul

    (Guru Nanak Institute of Technology, India)

Abstract

Recently healthcare sector has attracted service robots to prevent the spread of infection. During COVID-19 pandemic, service robots have been able to reduce direct contact of front-line healthcare workers by separating them from direct exposure to infection. Robots have been used for delivery systems, disinfection of the exposed area, remote monitoring of patients, etc. In the present work, we have designed a disinfection robot that radiates ultraviolet C rays for UV sterilization of hospitals that kills 95.0% of bacteria within 20 second of exposure from a distance of 0.5 meter. UVC disinfection is more effective than disinfection by hydrogen peroxide, and with other chemical-based disinfectants like chlorine, chloramine, etc. Our designed robot can also be used as a dispenser in hospital delivery system for transporting medicine, laboratory samples, etc. Its use will not only increase logistics efficiency but will also avoid spread of Hospital Acquired Infections (HAIs), healthcare associated infections, eliminate human error, and allow health workers to engage themselves in their higher priority works.

Suggested Citation

  • Shatrughna Prasad Yadav & Sai Kumar & Boddu Devika & Kolluri Rahul, 2022. "Robot-Assisted Ultraviolet Disinfector with Dispenser for Healthcare Related Services," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 6(1), pages 1-5, January.
    • Handle: RePEc:epw:ejece0:v:6:y:2022:i:1:id:19383
    DOI: 10.24018/ejece.2022.6.1.383
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejece/article/view/19383
    File Function: Abstract page
    Download Restriction: no
    File URL: https://eu-opensci.org/index.php/ejece/article/download/19383/11226
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.24018/ejece.2022.6.1.383?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:epw:ejece0:v:6:y:2022:i:1:id:19383. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejece .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.