Description:According to one embodiment of the present invention, as shown in Figure 1, Effective water management is critical for ensuring sustainability and operational efficiency, particularly in industrial settings where water wastage or leaks can lead to significant losses and environmental concerns. This project introduces a comprehensive system for detecting water leakage and monitoring water quality using advanced technologies such as optical fibre sensors and IoTenabled devices. By combining real-time monitoring with advanced data analytics, the system aims to address the challenges of industrial water management, providing an innovative solution
that is both accurate and cost-effective. At the core of the system are optical fibre sensors, strategically placed along pipelines and
tanks to detect any signs of leakage. These sensors operate on the principle of light signal modulation, where changes in the transmission of light within the fibre indicate the presence of leaks or structural issues. When water leakage occurs, it disrupts the integrity of the optical fibre,
causing variations in the light signal. These variations are detected and processed by an ESP32 microcontroller, which serves as the central hub for data collection and processing. This noninvasive approach ensures that the system can operate without interfering with the normal
functioning of the pipeline or water tanks, making it suitable for a wide range of industrial applications.In addition to detecting leaks, the system integrates sensors to monitor the quality and quantity
of water. Tank 2 (Inlet Tank) is equipped with sensors to measure water levels and pH, ensuring that the incoming water meets industrial requirements. Monitoring water levels helps identify
potential supply issues, while pH sensors ensure the chemical composition of the water remains
within safe and operational limits. Similarly, Tank 3 (Outlet Tank) is outfitted with sensors to measure Total Dissolved Solids (TDS) and other quality parameters, ensuring that the water
exiting the system is compliant with industrial and environmental standards. The combination of these features allows the system to provide a holistic approach to water management, addressing both leakage and quality concerns. A key feature of the project is its integration with IoT technology, enabling seamless data
processing and transmission. The ESP32 microcontroller collects data from the optical fiber sensors and the additional quality-monitoring sensors, processes the information, and transmits
it to a cloud platform for storage and further analysis. This cloud integration allows for the aggregation of large datasets, enabling long-term tracking and predictive analytics. Users can
access this data remotely, providing real-time insights and enabling informed decision-making.
For example, by analyzing historical trends, users can predict maintenance needs, identify
patterns in water usage, and develop strategies to minimize wastage.
To ensure accessibility and ease of use, the system includes an LCD display that provides
real-time information at the control unit. This display shows key metrics such as leakage status,
water levels, pH readings, and TDS values, giving operators an immediate overview of the
system’s performance. Additionally, the system generates alerts for anomalies, such as sudden
drops in water levels or deviations in quality parameters. These alerts are sent to a user-friendly
interface, which may include notifications on mobile or desktop platforms, ensuring that
operators are promptly informed of any issues that require attention.
The system operates through a well-defined workflow. Initially, the optical fibre sensors
detect any leaks by monitoring changes in light transmission. This data is sent to the ESP32,
which processes the information and integrates it with additional sensor readings from the tanks.
The processed data is then transmitted to the cloud platform for storage and analysis.
Simultaneously, the data is displayed on the LCD screen, allowing for real-time monitoring.
Alerts are generated in case of anomalies, enabling immediate action. By combining real-time
detection, quality monitoring, and cloud-based analytics, the system offers a robust solution for
industrial water management.
This project provides several key advantages. The use of optical fiber sensors ensures high
accuracy in detecting leaks while minimizing the risk of interference with the water system.
Real-time monitoring capabilities enable prompt identification and resolution of issues, reducing
water loss and operational downtime. The inclusion of quality monitoring parameters, such as pH and TDS levels, ensures that the water meets industrial standards, enhancing overall system reliability. Additionally, the integration of IoT technology and cloud analytics allows for remote access and advanced data insights, making the system highly scalable and adaptable to various industrial contexts. , C , Claims:1. A method for detecting water leakage and monitoring water quality using optical fibre and
IoT, comprising:
optical fibre sensors for detecting water leakage and flow;
an IoT module for real-time data acquisition and transmission;
a microcontroller for data processing and control;
a feature extraction algorithm for water flow and quality analysis;
a classification algorithm to identify and localize water leakage.
2. Optical fibre sensors for detecting water leakage and flow as claimed in claim 1, wherein
the sensors are integrated into Tank 2 (Inlet Tank) to detect changes in water flow and level.
The leakage data is collected and processed in real time by the ESP32 microcontroller and
transmitted to a cloud server for further analysis.
3. An IoT module for real-time data acquisition and transmission as claimed in claim 1,
wherein the system continuously monitors Tank 2 and Tank 3 (Outlet Tank) for parameters
such as water flow rate, TDS (Total Dissolved Solids), and pH level. Data is uploaded to a
cloud platform every 30 seconds for remote access and real-time monitoring.
4. A microcontroller for data processing and control as claimed in claim 1, wherein the ESP32
microcontroller integrates optical fibre sensor data with additional sensors for TDS and pH
measurements, applying normalization techniques to reduce noise and improve detection
accuracy.
5. A feature extraction algorithm for water flow and quality analysis as claimed in claim 1,
wherein the system preprocesses sensor data using filtering methods to enhance the accuracy
of leakage detection. The algorithm identifies key parameters to determine potential leakage
zones.
6. A classification algorithm to identify and localize water leakage as claimed in claim 1,
wherein the system achieves high accuracy in detecting water leakage by optimizing
computational efficiency. The system ensures real-time alerts and actionable insights
displayed on an LCD screen and accessible via a user interface, making it suitable for industrial water management applications