Examining the effect of aquaculture using sensor‐based technology with machine learning algorithm-Reference-Cited by-同舟云学术

Examining the effect of aquaculture using sensor‐based technology with machine learning algorithm

Published:2020-08-17 Issue:11 Volume:51 Page:4748-4758
ISSN:1355-557X
Container-title:Aquaculture Research
language:en
Short-container-title:Aquac Res

Author:

Manoharan Hariprasath¹^ORCID,Teekaraman Yuvaraja²,Kshirsagar Pravin R.³,Sundaramurthy Shanmugam⁴,Manoharan Abirami⁵

Affiliation:

1. Department of Electronics and Communication Engineering Audisankara College of Engineering and Technology Gudur, Andhra Pradesh India

2. Faculty of Energy and Power Engineering South Ural State University Chelyabinsk Russia

3. Department of Electronics and Communication Engineering AVN Institute of Engineering and Technology Hyderabad India

4. Department of Computer Science and Engineering Kongunadu College of Engineering and Technology Thottiam, Trichy India

5. Department of Electrical and Electronics Engineering Government College of Engineering Srirangam, Trichy India

Publisher

Wiley

Subject

Aquatic Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/are.14821

Reference19 articles.

1. Remote wireless automation and monitoring of large farm using wireless sensors networks and internet;Abdul‐rahaim L. A.;International Journal of Computer Science & Engineering Technology (IJCSET),2015

2. Analysing the water quality parameters from traditional to modern methods in aquaculture;Amrita C. M.;International Journal of Science, Environment and Technology,2018

3. Design and Deployment of Aqua Monitoring System Using Wireless Sensor Networks and IAR-Kick

4. Design of water quality monitoring system for aquaculture ponds based on NB-IoT

5. Prediction of water quality and smart water quality monitoring system in IoT environment;Karthick T.;International Journal of Pure and Applied Mathematics,2018

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