IDEAS home Printed from https://ideas.repec.org/a/jbh/ijsrcs/v7y2021i4idhcseit217469.html

Medicine Delivery Bot Using Time Series and Object Detection

Author

Listed:
  • Kartikeya Bajpai
  • Prachi Jain

Abstract

Nowadays, delivery is mainly done by humans which includes a lot of manual work. The existing way is good but lacks faster deliveries. In the present context the deliveries are not possible 24*7 by humans, especially in the case of medicines, customers often require immediate deliveries for maintaining their course of medication. Since, in many other fields AI has contributed to decreasing a lot of manual work and time. In this research paper, we have proposed the idea of a delivery bot which uses deep learning algorithms to detect traffic lights and classify the color of the traffic light. On the basis of which the lapse time will be calculated in between the two traffic lights and hence maps the route for delivery with the help of geocoding accordingly which helps in more secure and faster deliveries.

Suggested Citation

  • Kartikeya Bajpai & Prachi Jain, 2021. "Medicine Delivery Bot Using Time Series and Object Detection," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 7(4), pages 286-290, August.
  • Handle: RePEc:jbh:ijsrcs:v7:y2021:i4:id:hcseit217469
    DOI: 10.32628/CSEIT217469
    Note: Article URL: https://ijsrcseit.com/CSEIT217469
    as

    Download full text from publisher

    File URL: https://ijsrcseit.com/CSEIT217469
    File Function: Article URL
    Download Restriction: no

    File URL: https://ijsrcseit.com/paper/CSEIT217469.pdf
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32628/CSEIT217469?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:jbh:ijsrcs:v7:y2021:i4:id:hcseit217469. 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: Pankaj Sharma (USA) (email available below). General contact details of provider: https://ijsrcseit.com/home .

    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.