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https://github.com/bunnysunny24/bluepulse

A Smart Water Management System
https://github.com/bunnysunny24/bluepulse

data data-processing data-visualization firebase iot machine-learning mysql-database reactjs

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A Smart Water Management System

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README

          

# Noobventures
# Bhavashesh Dachpalli
# Raunak Jalan
# Sri Vatsa

# You can check the implementation fro iot in https://youtu.be/9BgTsOEIfLc

#### **Problem Statement 2: Water Conservation and Management**
#### **Overview:**
Water scarcity is a growing concern worldwide. Efficient water management systems can significantly reduce water wastage and ensure sustainable usage. The objective is to create a **smart IoT-based system** for monitoring and controlling water usage in buildings using **real-time data, predictive analytics, and automation**.

#### **Tech Stack:**
- **IoT Components:** ESP32, YF-S201 Hall Effect Water Flow Sensor, Water Pressure Sensor, Leakage Detection Sensor, LCD with I2C, 10K Potentiometer.
- **Machine Learning & Data Processing:** Python (Pandas, NumPy, Joblib, Scikit-learn, Matplotlib, Seaborn).
- **Database:** MySQL for storing sensor data and water usage history.
- **Web Application:** React.js for an interactive dashboard displaying real-time analytics.
- **Cloud Infrastructure:** AWS/GCP/Azure for data storage and real-time processing.

#### **Task:**
Develop a **smart water management system** that includes:
✔ **IoT sensors** to monitor water flow, detect leaks, and measure usage in real-time.
✔ **Machine Learning-powered predictive analytics** to forecast water demand and identify wastage patterns.
✔ **A React-based web application** to display water usage statistics, alerts, and conservation tips.
✔ **Integration with existing building management systems** for automated water control and alerts.

#### **Resources:**
- **IoT Hardware:** ESP32, Water Flow & Pressure Sensors, LCD Display.
- **Machine Learning Frameworks:** Pandas, NumPy, Scikit-learn for analysis.
- **Database Management:** MySQL for structured data storage.
- **Frontend Development:** React.js for the user dashboard.
- **Cloud Storage & Processing:** AWS/GCP/Azure for handling real-time data.

USE bluepulse;
SHOW TABLES;
SELECT * FROM pipeline1 LIMIT 10;
python new_modell.py
uvicorn iot_fast_api:app --host 0.0.0.0 --port 8000 --reload
uvicorn main:app --reload
curl -X POST "http://localhost:8000/add-pipeline-data" -H "Content-Type: application/json" -d '{"timestamp": "2025-02-09T11:00:00", "flow_inlet": 100, "flow_outlet": 90}'
npm install"
npm start