Skip to content

A hardware based project to analyse the quality of water and classify it as fit or unfit for drinking

Notifications You must be signed in to change notification settings

gdscnitp/drinking-water-treatment

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

10 Commits
 
 

Repository files navigation

drinking-water-treatment

A hardware based project to analyse the quality of water and classify it as fit or unfit for drinking

Problems Addressed:

  • Globally, at least 2 billion people use a drinking water source contaminated with faeces.

  • Contaminated water can transmit diseases such diarrhoea, cholera, dysentery, typhoid, and polio.

  • Contaminated drinking water is estimated to cause 485 000 diarrhoeal deaths each year.

  • By 2025, half of the world’s population will be living in water-stressed areas.

Overview:

The project is based on the data science that estimate the drinking water parameter data collected from particular area according to IS 10500 : 2012 (Drinking Water Specification). The result that get from estimation will use to categorize the particular zone Red, Yellow and Green.

  • Green Zone :- Safe zone
  • Yellow Zone :- warning
  • Red Zone :- Alarming Situation.

Goals:

  • To aware people to use conventional methods of treatment of drinking water.

  • As the conventional methods of treatment of water are not so effective. Therefor developing sensors based cost effective methods.

  • Raising awareness towards controlling water pollution.

Tech Stacks Required:

  • ML
  • iot
  • Raspberry pi
  • Android
  • Web

Roadmap Overview:

  • First time interval -2 months – Collecting data of particular area.

  • Second time interval -3 months- Estimation of data sets.

Approximate count of contributors required: 15-20

About

A hardware based project to analyse the quality of water and classify it as fit or unfit for drinking

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 3

  •  
  •  
  •