1. Status and challenges of water loss in ASEAN

1.1 Overall situation of non-revenue water (NRW)

According to the World Economic Forum – Adaptation through Water 2025, many urban water-supply systems in ASEAN face NRW levels of 22% to 38%, which is 4–8 times higher than Singapore’s 5%. The main causes are aging pipelines and a lack of monitoring technology, so a large share of produced water is lost before reaching users. This not only wastes resources but also raises operating costs for companies and financial pressure for governments.

• In Thailand, a 2025 study on major river basins shows Water Use Efficiency dropped by about 21%, while water stress rose from 9.68% to 13.8% (MDPI, 2025). This clearly reflects sub-optimal performance in water extraction and management.
• In Vietnam, the water sector is working hard to reduce losses. According to FiinGroup (2024), the average NRW at water companies is around 17.5%, with a target to lower it close to 15% by 2025. With urban treatment capacity of about 12 million m³/day (Water Summit 2025), even small loss rates mean millions of cubic meters of clean water are lost every day.

These numbers show that water loss is not only a technical problem; it is also a serious economic and environmental issue. However, despite many efforts, ASEAN cities still face a series of challenges in controlling and reducing NRW.

1.2 Major challenges in urban water management

Even with many NRW-reduction programs, large challenges remain:

• Dependence on fixed sensors, high cost: Traditional systems require installing flow meters, pressure gauges, and vibration sensors across the network. This drives very high CAPEX and OPEX, while detection coverage remains limited.
• Limited analysis accuracy: 1D simulations are fast but have high error; 3D models are accurate but too slow for real-time use. As a result, many leaks are not detected in time.
• Manual processes slow response and repairs: Many utilities spend days or even weeks from anomaly detection to locating, digging, and repairing. This causes long-term water loss, affects residents and businesses, and raises recovery costs.
• Poor data integration & long-term management: Operations, leak events, repairs, and maintenance data are often separated across different systems, making trend analysis and long-term network optimization difficult. This weakens asset management effectiveness.
• Environmental & ESG impact: Lost water also means wasted pumping and treatment energy, increasing greenhouse gas emissions. This can hinder ASEAN cities from reaching Net Zero targets in water infrastructure.

These challenges show that traditional methods are no longer sufficient. A more breakthrough technology is needed.

2. UGV (Unmanned Ground Vehicles) & AI for Water Leakage Detection: Accurate, AI-based leak detection

2.1 What is UGV & AI for Water Leakage Detection?

UGV & AI for Water Leakage Detection is a smart leak-detection and management solution built on Digital Twin and AI. The system monitors pipeline networks in real time, automatically identifies potential leak locations, and generates optimal repair plans—without requiring fixed sensors.

2.2 Operation process of the technology

The end-to-end leak-management workflow runs through four complete steps:

• Step 1: Identify suspect areas and pipelines

The system uses a pipeline-flow analysis engine to detect abnormal flow patterns, then defines zones and pipe segments at risk of leakage.

• Step 2: Collect data on suspect pipelines

A mobile leak-detection device is deployed on-site to capture real-world data and verify the suspected locations.

• Step 3: Pinpoint exact leak points

Collected data is processed by an AI-based precision analytics system, combining acoustic signals with GIS information to locate exact leak points on the network.

• Step 4: Auto-generate maintenance plans

Based on the analysis, the system automatically creates maintenance work plans and proposes optimal repair scenarios to fix leaks quickly while minimizing service disruption.

2.3 Key differentiators

This leak-detection solution stands out from traditional methods in several ways:

• No fixed sensors required: The system detects leaks using mobile devices, cutting initial CAPEX and enabling flexible, wide-area monitoring.
• Faster and more accurate detection: Proprietary AI algorithms combined with 2D flow analysis increase accuracy by up to 30% versus current systems, shorten detection time by 3×, and reduce recovery time by 50%.
• End-to-end automation: After detection, AI automatically proposes recovery scenarios and optimizes valve control, making the process faster, more accurate, and far less dependent on manual work.
• Integrated management: Designed to connect directly with SCADA and smart-city platforms for long-term pipeline-network optimization.
• Meets ESG and Net Zero goals: The technology can reduce leakage rates to 5%, saving up to 300 million m³ of water per year. Lower water loss means lower pumping/treatment energy and lower CO₂ emissions, helping utilities and local governments reach carbon-neutral goals.

3. Real results from the Ulsan pilot

A clear proof point is the 2024 pilot at Ulsan Waterworks (Korea), where UGV and AI + Digital Twin leak detection were applied. Results showed:

• Leak-detection accuracy increased by 30% versus the existing system.
• Detection time shortened by 3×, enabling much faster incident handling.
• Recovery time decreased, significantly cutting service disruption for residents.

The success in Ulsan proves real-world effectiveness—not only technically but also in improving the reliability of water-supply systems under real operating conditions.

4. Digital Twin & AI vs. traditional methods

5. Outlook and future applications

5.1 Market context and rising demand in ASEAN

The water-supply market in ASEAN is facing a growing need for technology upgrades. Real figures show that water loss is not only a technical issue but also a massive market opportunity for smart monitoring and management solutions.

• According to the World Economic Forum (2025), many cities in the region report NRW levels between 22% and 38%. This indicates that ASEAN is one of the markets with the most urgent demand for water-leakage detection and reduction technologies.
• In Vietnam, a bulletin from StateOfGreen, citing Denmark–Vietnam cooperation research, states that the country has a plan to cut NRW to 15% by 2025.

These numbers show that the region has entered a stage where concrete action is required. This makes leak-detection technology a top investment priority.

5.2 ESG policies and Net Zero goals

Governments and businesses in the region are linking water management with ESG and Net Zero strategies. As a result, reducing NRW can become a key target in the green transition process.

• Many ASEAN countries have announced Net Zero commitments for 2050-2065, in which cutting water loss is considered a direct way to reduce CO₂ emissions. With fast leak detection and shorter recovery time, UGV & AI for Water Leakage Detection can fully support countries in moving closer to these Net Zero goals.
• The trend of AI + IoT + Digital Twin is becoming the standard in smart-city projects, showing that this new technology is not only in line with global trends but also directly fits regional policy roadmaps.

5.3 Partnership opportunities and cross-industry value

Beyond technical benefits, this technology also opens opportunities for cross-industry cooperation and new business models for many partners both inside and outside the water sector.

• The technology can integrate with SCADA, sensors, and Smart City platforms to create a comprehensive water-management ecosystem. This not only optimizes water operations but also supports wider urban management.
• Small or local water companies can join through a SaaS model or co-investment, lowering initial capital barriers while still gaining access to advanced technology.
• Its scalability into oil, gas, and energy also creates opportunities to work with heavy-industry companies, where pipeline leaks pose very high risks.

5.4 R&D potential and next steps

In the future, this technology has many directions for development to optimize efficiency and expand its applications.

• It can be integrated with pressure management and DMA zoning to prevent leaks caused by high pressure, enabling more sustainable network control.
• Research on robots or smart valves that can automatically isolate or repair leaks as soon as they are detected will improve safety and reduce recovery time.
• The use of predictive leakage applications based on AI and historical data will allow early forecasting of failures, shifting from “reactive” response to “proactive” prevention.

If you are a business, water utility, or industrial partner seeking an advanced solution for sustainable infrastructure management, contact us today. Mekonglink is ready to discuss long-term business partnerships, pilot projects (PoC), and real deployments across ASEAN.

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