IOT Based Water Quality Monitoring System using ESP32

Abstract

The rapid growth of the human population, combined with environmental degradation and climate changes, is turning clean water into an increasingly scarce resource. As a result, monitoring water quality, especially for drinking purposes, has become crucial. Traditional methods of laboratory testing are time-consuming, costly, and fail to provide real-time results. Moreover, systems based on Wireless Sensor Networks (WSN) technology often face challenges in areas like data security, energy management, and communication coverage. Critical sectors, such as flood warning systems, irrigation networks, power generation, and research, rely heavily on accurate flood-level data. Historically, water levels have been measured manually, but this approach is prone to inaccuracies due to difficulties in accessing the measurement sites and human error. To address this, data can be transmitted to a central server via a web interface for database management. Access to this data is secured by passwords, ensuring that only authorized users can view it. Additionally, customers are billed based on their water consumption, which is monitored through a flow sensor connected to an ESP32, providing measurements in liters per minute or other volumetric units.

Introduction

1. Introduction

Access to clean water is vital for health, sustainability, and economic development. According to the WHO, contaminated water causes over 5 million deaths annually, underscoring the need for better monitoring and management technologies. This study introduces a real-time IoT-based system that monitors water quality using sensors and wireless connectivity to address these challenges.

2. System Overview

The system uses an ESP32 microcontroller and various sensors to monitor:

• pH (acidity/alkalinity)

• Turbidity (clarity)

• TDS (Total Dissolved Solids)

• Temperature (via DHT11)

The data is processed, converted into real-world units, and sent to a cloud platform (e.g., ThingSpeak) or displayed on an LCD. If thresholds are breached, alerts (via SMS/email) are sent to notify users.

3. Flowchart Summary

The system operates in the following sequence:

1. Startup & Initialization: ESP32 powers on and connects to Wi-Fi.

2. Sensor Activation: All sensors are initialized.

3. Data Acquisition: Readings are taken from pH, turbidity, TDS, and temperature sensors.

4. Data Processing: Sensor outputs are calibrated and converted to readable formats.

5. Cloud Upload & Display: Processed data is uploaded to the cloud and optionally shown on a local display.

6. Monitoring & Alerts: If any values exceed safe thresholds, alerts are triggered.

7. Delay: A waiting period is set before the cycle restarts.

4. Hardware Components

• ESP32 & ESP8266: Microcontrollers with built-in Wi-Fi, enabling IoT integration.

• LCD with I2C: Displays live sensor readings.

• pH, Turbidity, TDS Sensors: Monitor various water quality parameters.

• DHT11: Measures environmental or water temperature.

• GSM Module: Sends SMS alerts using mobile networks.

5. Working Methodology

• Sensor Integration: Real-time monitoring with advanced sensors.

• Data Transmission: Sent wirelessly to IoT platforms like Blynk.

• Smart Filtration: Automated water filtration system ensures high water quality.

• Feedback Loop: TDS sensors at output points monitor post-filtration quality.

• Remote Access: Users can track water quality and receive alerts on their smartphones.

6. Results and Hardware Output

• The prototype successfully displays real-time water quality data on an LCD and transmits the same to a mobile application.

• Alerts (e.g., filter damage) are automatically sent via SMS and email.

• The system supports automated water management and quality assurance.

7. Key Benefits

• Real-time monitoring

• Remote access via mobile app

• Automated alerts

• Smart filtration

• Improved public health and sustainability

This IoT-based water quality system offers a low-cost, scalable, and effective solution for ensuring safe water access and promoting sustainable water resource management.

Conclusion

In conclusion, integrating the IoT-based Blynk app, pump, and filtration system with TDS, pH, and turbidity sensors connected to an ESP32 provides a reliable approach to ensuring access to clean and safe water. By continuously monitoring key water parameters and leveraging IoT technology, this system enables proactive management and intervention to maintain water quality standards. The real-time data display offered by the Blynk app enhances transparency, allowing users to make informed decisions regarding water usage and management. The pump facilitates efficient water distribution, while the filtration system ensures improved water quality before consumption. Additionally, a feedback loop provided by the TDS sensor at the point of use enables continuous monitoring and optimization. Overall, this integrated solution effectively addresses water quality concerns, promotes sustainability, and helps protect both the environment and public health. Advancements in research and development in this field will further enhance our ability to monitor and manage water resources efficiently, even in the face of evolving environmental and societal challenges.

References

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Copyright

Copyright © 2025 M. Mahendiran, C. Kabilan, R. Santhosh, E. Yathav, Mr. S. Sugumar, Dr. R. Manikandan, Dr. P. Selvakumar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.