Remote Intelligent For Oxygen Prediction Content in Prawn Culture System

Authors(3) :-V. Vinothini, M. Sankari, M. Pajany

In this work monitoring the Dissolved oxygen concentration in water tank. The problems caused by manual monitoring in prawn farming, a remote intelligent for oxygen content prediction in prawn culture system are proposed. The proposed system is on oxygen sensor in detecting the water quality and measuring the oxygen level in the water and Short Message Service (SMS) technology is delivering alert to the owner upon detection of water quality in oxygen level. The SMS can be send to the owner through Global System for Mobile Communication (GSM).Dissolved oxygen, Temperature, pH are the three water quality parameter that are critical to the prawn health. Remote 24 hour monitoring of the prawn tank to avoid the organism death caused by oxygen drops. If the oxygen level is low, the motor will be automatically ON / OFF, at the same time the message can be send to the owner. In this paper monitoring the oxygen level and SMS send to GSM by automation techniques.

Authors and Affiliations

V. Vinothini
Computer Science Department, IFET College of Engineering, India
M. Sankari
Computer Science Department, IFET College of Engineering, India
M. Pajany
Computer Science Department, IFET College of Engineering, India

Global System for Mobile Communication (GSM), automation, Oxygen sensor

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Publication Details

Published in : Volume 2 | Issue 2 | March-April 2017
Date of Publication : 2017-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 223-228
Manuscript Number : CSEIT172254
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

V. Vinothini, M. Sankari, M. Pajany, "Remote Intelligent For Oxygen Prediction Content in Prawn Culture System", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 2, pp.223-228, March-April-2017.
Journal URL : http://ijsrcseit.com/CSEIT172254

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