WQVP: An API enabled Open Data Machine Learning based Solution for Water Quality Visualization and Prediction

Authors

  • Pooja Lodhi Deptt. of CSE&IT, Jaypee Institute of Information Technology NOIDA, Uttar Pradesh India
  • Omji Mishra Deptt. of CSE&IT, Jaypee Institute of Information Technology NOIDA, Uttar Pradesh India
  • Gagandeep Kaur Deptt. of CSE&IT, Jaypee Institute of Information Technology NOIDA, Uttar Pradesh India

Keywords:

API, Clustering, Machine Learning, Open Data Initiative, Prediction, Visualization, Water Quality,

Abstract

Water is an essential component required by living bodies for their survival. In today’s world, most of the water utilization is done by human beings. Due to this, there is a lot of adverse impact on water bodies. As human consumption of water increases, their pollution also increases. In order to control pollution impact and take measures to reduce water pollution, several methods have been proposed by researchers. Water Quality Index measures are one such method being adopted and used to measure harmful constituents of water. In recent times initiatives have been taken by international and national governing bodies to provide data through Open Data Initiatives that can be publicly made available. This data fetched in real time through APIs can be used for providing data analysis to naïve natives of the place with better understanding features like visualizations. Machine learning based techniques have proved to be a great tool for providing unsupervised learning in this area. We have implemented an API enabled Open Data Machine Learning based Solution for Water Quality Visualization and Prediction for Australian Rivers.

Author Biography

Omji Mishra, Deptt. of CSE&IT, Jaypee Institute of Information Technology NOIDA, Uttar Pradesh India

Masters Student

Deptt. of CSE&IT

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Published

2018-05-30

How to Cite

Lodhi, P., Mishra, O., & Kaur, G. (2018). WQVP: An API enabled Open Data Machine Learning based Solution for Water Quality Visualization and Prediction. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(2), 61–72. Retrieved from https://jtec.utem.edu.my/jtec/article/view/3302

Issue

Vol. 10 No. 2: April - June 2018

Section

Articles

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