The River Water Quality Monitor is an Internet of Things (IoT) project that combines Quality dashboard and Trend analysis, built with DHT sensor. The project follows a clean, modular pipeline where sensor data acquisition, connectivity, and presentation stay separated, making it easy to test, extend, and present. It showcases practical IoT techniques while producing a working, demo-ready system.
Manual monitoring and control for this task is slow, inconvenient, and cannot be done from anywhere. Without an IoT approach built on Trend analysis and DHT sensor, users cannot connect real-world devices to the internet and manage them efficiently in real time.
This project applies IoT techniques through Quality dashboard, orchestrated with DHT sensor and Trend analysis. The system is designed for connectivity and reliability, with sensing, networking, and clear evaluation. It produces consistent, reusable results and can be adapted to related connected applications with minimal changes.
DHT sensor
MQTT
ESP32 / Arduino / Raspberry Pi
MQTT / HTTP
Cloud dashboard
Sensors and actuators
ESP32 / Arduino
MQ gas sensors
PM2.5 sensor
Modular IoT pipeline around Quality dashboard and Trend analysis
Configurable sensor and control settings
Real-time data collection and monitoring
Clear alerts, logging, and error handling
Reusable components for related connected systems
Remote access and control
The project is layered: the sensing layer acquires data through Quality dashboard; the connectivity layer publishes and processes it with DHT sensor and Trend analysis; and the output layer monitors and controls via Water sensing. Shared connectivity, alerting, and dashboard modules support all layers, keeping the system robust and easy to extend.
Set up the hardware, sensors, and development environment.
Build the sensor data acquisition layer with Quality dashboard.
Implement connectivity and processing using DHT sensor and Trend analysis.
Add the dashboard and control layer via Water sensing.
Wire up end-to-end flows and add error handling and retries.
Test with real data, tune settings, and refine the system.
Package the project, document it, and prepare the demo and viva report.
Build production-style IoT applications
Apply Building weather stations and Environmental dashboards
Connect and control IoT hardware
Publish and consume sensor data
Present and defend a complete IoT project in viva
Add edge analytics for faster decisions
Add more sensors and cloud services
Add mobile app control
Deploy on scalable cloud infrastructure
The River Water Quality Monitor delivers a complete Internet of Things workflow — from sensor data acquisition and connectivity to monitoring and control. It is practical, modern, and easy to explain, making it an excellent final year project that demonstrates in-demand IoT skills.
