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