Idea - FICS

Water-Quality Analysis

Team and Contact Details

Student Name School Degree Year Email
Hassan Kumail

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

Idea Name: Water-Quality Analysis
Slogan: Water is life!
Supervisor Name: Dr. Rafia Mumtaz
Supervisor Designation: Assistant Professor|Head of Information Technology
Supervisor School: School of Electrical Engineering and Computer Sciences
Supervisor Department: Department of Computing
Contact number: 05190852161
Email ID:
    A time-series analysis and prediction of water quality will be performed using machine learning techniques. Water quality parameters will be obtained from Remote Sensing, Geoinformation System and IoT
What is the unmet need in society that your idea will fulfill ?
    The increasing population, stressed resources, pollution, and the lack of technology-based solution for effective resource management raises the question of the quality of water available for near future generations. In this regard, the temporal analysis of water quality holds paramount importance.
Who needs it ? How many would benefit ?
   The periodic time series analysis of water quality will help us in identifying key problems and finding effective solutions for improved quality in the near future for local citizens. The government should be alarmed in such a drastic situation of decreasing water quality.
How will the solution works
    A Machine Learning model would be made based on water quality parameters’ (WQPs) data gathered from Geographical Information Systems, Remote Sensing, and IoT devices. WQPs like Turbidity, Dissolved Oxygen, Chlorophyll-a concentration will be used. After deriving the WQPs, a single-valued Water Quality Index will be calculated. Time-series analysis will be performed, and predictions will be made that would provide the government or other regulatory authorities with important insights.
Who are your competitors ? How is your solution different
    Many researchers had the same idea, but we would be the first to apply it on such a varied dataset. With data being pooled from three different sources and being used, we aim to create a robust model that would give accurate results for other water bodies with similar conditions.
Status: new
Entry Date & Time: 2020-12-24 (1844)