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Sunday, 31 May 2026
AI Smart Water Quality Monitoring and Prediction System
AI Smart Water Quality Monitoring and Prediction System
AI-Powered ESP32 + Agentic IoT + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak Cloud Dashboard
AI Smart Water Quality Monitoring and Prediction System
AI-Powered ESP32 + Agentic IoT + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak Cloud Dashboard
1. Project Overview
The AI Smart Water Quality Monitoring and Prediction System continuously monitors water quality parameters using sensors connected to an ESP32. The collected data is uploaded to cloud platforms and analyzed using AI models to predict water contamination trends and power consumption.
The system provides:
✅ Real-time Water Quality Monitoring
✅ Cloud Data Storage
✅ AI-Based Water Quality Prediction
✅ Automated n8n Workflow Processing
✅ Google Sheets Data Logging
✅ ThingSpeak Dashboard Visualization
✅ Telegram Notifications
✅ Telegram Voice Alerts
✅ AI Agent Analytics
✅ Remote Monitoring Through Web Dashboard
2. Objectives
The system monitors:
Water Temperature
pH Level
Turbidity
TDS (Total Dissolved Solids)
Water Quality Index (WQI)
The AI Agent predicts:
Water contamination risk
Future water quality trend
Sensor anomaly detection
Power consumption forecast
3. System Architecture
Sensors
│
▼
ESP32 Controller
│
WiFi Internet
│
▼
ThingSpeak Cloud
│
├────────► Dashboard
│
▼
n8n Workflow
│
├────────► Google Sheets
│
├────────► AI Agent Analysis
│
└────────► Telegram Bot
│
├── Text Alert
└── Voice Alert
4. Required Components
Component Quantity
ESP32 Dev Board 1
pH Sensor Module 1
Turbidity Sensor 1
TDS Sensor 1
DS18B20 Temperature Sensor 1
Breadboard 1
Jumper Wires As required
4.7kΩ Resistor 1
Power Supply 1
WiFi Network 1
Computer/Laptop 1
5. Sensor Description
pH Sensor
Measures acidity or alkalinity.
Range:
0 - 14
Ideal Drinking Water:
6.5 - 8.5
Turbidity Sensor
Measures water clarity.
Unit:
NTU
Lower value = Cleaner water
TDS Sensor
Measures dissolved solids.
Unit:
PPM
Drinking Water:
50 - 300 PPM
DS18B20
Measures water temperature.
Range:
-55°C to 125°C
6. Circuit Connections
pH Sensor
VCC → 5V
GND → GND
OUT → GPIO34
Turbidity Sensor
VCC → 5V
GND → GND
OUT → GPIO35
TDS Sensor
VCC → 5V
GND → GND
OUT → GPIO32
DS18B20
VCC → 3.3V
GND → GND
DATA → GPIO4
4.7kΩ between DATA and VCC
7. Circuit Schematic
ESP32
GPIO34 ← pH Sensor
GPIO35 ← Turbidity
GPIO32 ← TDS Sensor
GPIO4 ← DS18B20
WiFi
│
▼
ThingSpeak
│
▼
n8n
┌────────┼─────────┐
▼ ▼ ▼
Google Telegram AI Agent
Sheets Bot
8. Flowchart
Start
│
Initialize Sensors
│
Connect WiFi
│
Read Sensor Values
│
Calculate Water Quality
│
Send Data To ThingSpeak
│
Trigger n8n Workflow
│
Store In Google Sheet
│
AI Agent Analysis
│
Generate Alerts
│
Telegram Notification
│
Telegram Voice Alert
│
Repeat Every Minute
9. ESP32 Source Code
#include
#include
const char* ssid = "YOUR_WIFI";
const char* password = "YOUR_PASSWORD";
String apiKey = "YOUR_THINGSPEAK_API_KEY";
#define PH_PIN 34
#define TURB_PIN 35
#define TDS_PIN 32
void setup()
{
Serial.begin(115200);
WiFi.begin(ssid,password);
while(WiFi.status()!=WL_CONNECTED)
{
delay(500);
}
}
void loop()
{
float phValue =
analogRead(PH_PIN) * 14.0 / 4095.0;
float turbidity =
analogRead(TURB_PIN);
float tds =
analogRead(TDS_PIN);
if(WiFi.status()==WL_CONNECTED)
{
HTTPClient http;
String url =
"http://api.thingspeak.com/update?api_key="
+ apiKey +
"&field1=" + String(phValue) +
"&field2=" + String(turbidity) +
"&field3=" + String(tds);
http.begin(url);
http.GET();
http.end();
}
delay(60000);
}
10. ThingSpeak Setup
Step 1
Create account:
ThingSpeak
Step 2
Create New Channel
Fields:
Field1 = pH
Field2 = Turbidity
Field3 = TDS
Field4 = Temperature
Field5 = Water Quality Index
Step 3
Copy Write API Key
Step 4
Paste into ESP32 Code
11. Google Sheets Integration
Create Sheet:
Timestamp
Temperature
pH
TDS
Turbidity
WQI
Status
Prediction
12. n8n Workflow Design
Install:
n8n Official Website
Workflow:
Webhook Trigger
│
▼
Read ThingSpeak Data
│
▼
AI Analysis
│
├── Google Sheets
│
├── Telegram Message
│
│
└── Voice Alert
13. n8n Workflow JSON Structure
{
"nodes": [
{
"name": "Webhook"
},
{
"name": "AI Agent"
},
{
"name": "Google Sheets"
},
{
"name": "Telegram"
}
]
}
14. Telegram Bot Setup
Step 1
Open Telegram.
Search:
BotFather
Step 2
/newbot
Step 3
Create Bot Name.
Step 4
Copy API Token.
15. Telegram Integration in n8n
Add:
Telegram Node
Insert:
Bot Token
Chat ID
Alert Message:
⚠ Water Quality Alert
pH: {{$json.ph}}
TDS: {{$json.tds}}
Turbidity: {{$json.turbidity}}
Risk Level:
{{$json.risk}}
16. Voice Notification Automation
n8n Process:
AI Alert
│
Generate Text
│
Google TTS
│
MP3 Voice
│
Telegram Send Audio
Voice Example:
Warning.
Water contamination level is increasing.
Immediate inspection recommended.
17. AI Agent Analytics
The AI Agent evaluates:
Water Quality Index
Excellent
Good
Moderate
Poor
Unsafe
Contamination Detection
Checks:
High Turbidity
High TDS
Abnormal pH
Sensor Health Monitoring
Detects:
Sensor Failure
Missing Data
Noise Data
18. AI Water Quality Prediction Logic
Example Rule Engine:
IF pH < 6.5
AND Turbidity > 500
THEN
Risk = HIGH
Prediction Model Inputs:
Temperature
pH
TDS
Turbidity
Historical Data
Outputs:
Water Quality Score
Future Risk
Alert Probability
Machine Learning Options:
Linear Regression
Random Forest
XGBoost
LSTM Time Series
19. AI Power Consumption Prediction
Inputs:
ESP32 Runtime
WiFi Usage
Sensor Operating Time
Cloud Upload Frequency
Formula:
Power = Voltage × Current
P=VI
Example:
Voltage = 5V
Current = 0.18A
Power = 0.9 Watts
AI predicts:
Daily Energy Usage
Monthly Energy Usage
Battery Life
20. Dashboard Features
ThingSpeak Dashboard Displays:
Live pH Graph
TDS Graph
Turbidity Graph
Temperature Graph
Water Quality Trend
Prediction Trend
Alert Status
21. Future Enhancements
AI Enhancements
Deep Learning Prediction
Auto Calibration
Edge AI on ESP32
TinyML Deployment
Cloud Enhancements
Multi-location Monitoring
Mobile App
Firebase Integration
AWS IoT Integration
Industrial Enhancements
Water Treatment Plant Monitoring
Smart City Water Management
River Pollution Detection
Industrial Wastewater Monitoring
22. Deployment Guide
Small Scale
Schools
Colleges
Homes
Laboratories
Medium Scale
Apartment Complexes
Water Tanks
Hospitals
Large Scale
Municipal Water Systems
Smart Cities
Industrial Plants
Final Outcome
Complete AI-Powered Water Quality Monitoring Platform
✅ ESP32 IoT Monitoring
✅ Real-Time Water Quality Sensing
✅ AI Agent Analytics
✅ n8n Workflow Automation
✅ Google Sheets Database
✅ Telegram Text Alerts
✅ Telegram Voice Alerts
✅ ThingSpeak Cloud Dashboard
✅ Water Quality Prediction
✅ Power Consumption Prediction
✅ Cloud-Based Monitoring
✅ Scalable Smart Water Management Solution
This project is suitable for final-year engineering projects, IoT research, smart city applications, environmental monitoring systems, and Industry 4.0 deployments.
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