A hardware based project to analyse the quality of water and classify it as fit or unfit for drinking
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Globally, at least 2 billion people use a drinking water source contaminated with faeces.
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Contaminated water can transmit diseases such diarrhoea, cholera, dysentery, typhoid, and polio.
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Contaminated drinking water is estimated to cause 485 000 diarrhoeal deaths each year.
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By 2025, half of the world’s population will be living in water-stressed areas.
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.
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To aware people to use conventional methods of treatment of drinking water.
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As the conventional methods of treatment of water are not so effective. Therefor developing sensors based cost effective methods.
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Raising awareness towards controlling water pollution.
- ML
- iot
- Raspberry pi
- Android
- Web
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First time interval -2 months – Collecting data of particular area.
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Second time interval -3 months- Estimation of data sets.