IDEAS home Printed from https://ideas.repec.org/a/etm/ijsrst/v13y2026i2id1459.html

LiFi Based Real Time Under Water Board Casting from Optimal Data Rates and Low Power Consumptions

Author

Listed:
  • K. Bhaskar
  • S. S. Jayapriya
  • P. Varshith
  • A. Sathvik
  • P. Yaswanthi
  • Prabhakar Kumar

Abstract

This project presents a Li-Fi–based underwater communication prototype designed to efficiently transmit water-quality data using low power and optical signaling. The system consists of separate Transmitter (TX) and Receiver (RX) modules. The TX module, placed underwater, uses sensors such as the HC-SR04 ultrasonic sensor for water level, pH sensor, DS18B20 temperature sensor, and turbidity sensor to monitor environmental conditions, while a buzzer provides alerts during abnormal readings. The collected data is encoded and sent through a Li-Fi LED transmitter. At the surface, the RX module uses an LDR-based Li-Fi receiver to decode the optical signal, display the information on an LCD, and indicate the status using green (normal) and red (abnormal) LEDs. Additional sensors like DHT11, MQ135, and LDR enhance monitoring at the receiver side. A push button allows the data to be uploaded to the ThingSpeak cloud using NodeMCU. The proto- type demonstrates the effectiveness of Li-Fi as a low-power, interference-free solution for underwater communication, making it suitable for various water-quality monitoring applications.one important feature for scuba divers,whenever they found a danger,they can send ‘help!’ signal to receiver and activates the buzzer.

Suggested Citation

  • K. Bhaskar & S. S. Jayapriya & P. Varshith & A. Sathvik & P. Yaswanthi & Prabhakar Kumar, 2026. "LiFi Based Real Time Under Water Board Casting from Optimal Data Rates and Low Power Consumptions," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 13(2), pages 347-353, April.
  • Handle: RePEc:etm:ijsrst:v13:y2026:i2:id:1459
    DOI: 10.32628/IJSRST261334
    as

    Download full text from publisher

    File URL: https://ijsrst.com/home/article/view/IJSRST261334
    File Function: Abstract page
    Download Restriction: no

    File URL: https://ijsrst.com/home/article/download/IJSRST261334/IJSRST261334
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32628/IJSRST261334?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:etm:ijsrst:v13:y2026:i2:id:1459. 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 (email available below). General contact details of provider: https://ijsrst.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.