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BlueWatch: A Smarter Way to Understand Water Loss

BlueWatch is a software project that helps water management teams understand where water loss may be happening. It compares water supplied with billed consumption and uses past data to track changes in NRW levels across different zones. By highlighting areas with higher risk, BlueWatch helps teams decide where to investigate first and manage water resources more effectively. The project uses Java and Spring Boot to analyze data and deliver results through REST APIs.

CSBS Student | Java Full-Stack Developer | Spring Boot | React.js | AWS Enthusiast

BlueWatch: A Smarter Way to Understand Water Loss

Introduction

Water is essential for everyday life, but not all the water supplied to a city reaches consumers as billed water. Some may be lost through leaks, while other differences can result from measurement errors, unauthorized consumption, or billing issues. Finding the reasons behind these differences is an important challenge for water management teams.
This is where BlueWatch comes in. It is a software project that uses water usage data to help identify areas that may need attention.

Why Did We Choose This Problem?

Water loss can be difficult to track when information is spread across different records. Officials need to compare the amount of water supplied with the amount billed to understand how the distribution system is performing.
Looking at individual records may not be enough. Teams also need to know whether water loss in an area is increasing or decreasing over time. Without these insights, deciding which areas should be inspected first can become challenging.
Our goal with BlueWatch is to make this information easier to understand and use.

How Does BlueWatch Help?

BlueWatch takes water supply figures, billed consumption, and historical NRW data and turns them into useful results.
It calculates water loss and the Non-Revenue Water (NRW) percentage for each zone. It then compares current figures with historical data to show whether the NRW level has increased or decreased. Based on the current percentage and its trend, the system assigns a risk category to help highlight zones that may need further investigation.
For example, if a zone has a high NRW percentage and the value has increased compared with the previous record, BlueWatch can flag it as a higher-priority area.
This does not automatically confirm a leak, but it gives water management teams a starting point for deciding where to investigate.

What Can the System Do?

BlueWatch focuses on a few practical features:
  • Water loss calculation: Finds the difference between supplied water and billed consumption.
  • NRW analysis: Calculates the percentage of supplied water that is not billed.
  • Trend comparison: Compares current NRW values with historical figures.
  • Risk classification: Groups zones into risk levels based on the project's scoring rules.
  • API support: Returns results in JSON format so a frontend dashboard or another application can use them.
  • Future cloud access: The backend is being prepared for deployment on AWS.

Technologies We Use

We developed the backend using Java 21 and Spring Boot. These technologies help process the input data and provide results through REST APIs. Maven is used to build the application, and CSV files currently store the sample water supply and historical NRW records.
As the project develops, we plan to use Docker to package the application and AWS services such as Amazon ECR and AWS App Runner to support cloud deployment.

Who Can Use BlueWatch?

BlueWatch is designed with municipal water departments, water utility operators, and city administrators in mind. It can help these users compare water records, spot unusual patterns, and decide which zones deserve closer attention.
The main idea is to make water-related data easier to understand, even for users who do not have a technical background.

What Can We Add in the Future?

There is plenty of room to improve BlueWatch. Future versions could include a visual dashboard, map-based zone monitoring, automatic alerts, database integration, and regularly updated operational data.
Reliable field measurements could also be added to help teams investigate suspected leaks and understand whether water losses come from physical leakage or other causes.

Conclusion

Water loss is not always easy to identify, especially when teams have to work with large amounts of data. BlueWatch aims to make that task simpler by bringing important figures together and highlighting areas that may need attention.
Our project is a step toward using software and data analysis to support better water management.
BlueWatch — Clearer Data, Smarter Water Management.
Any opinions in this article are those of the individual author and may not reflect the opinions of AWS.
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