KOICA CTS-1 Pilot Project - AI Leak Detection for NRW Management at PDAM Tirta Bumi Wibawa Sukabumi

Transforming Water Loss Management in Indonesia with AI and IoT

Client: Perumdam Tirta Bumi Wibawa, Kota Sukabumi
Project Partners: Korea International Cooperation Agency (KOICA), WI.Plat Co., Ltd., SUPRA International Indonesia
Location: Kota Sukabumi, Indonesia
Project Timeline: 2021–2022

Executive Summary

In 2021, the city of Sukabumi became the first location in Indonesia to trial an AI-driven, IoT-based leak detection system under the KOICA Creative Technology Solution (CTS) program. The initiative was designed to address the city’s high level of Non-Revenue Water (NRW) by combining advanced acoustic monitoring, real-time flow and pressure data, and artificial intelligence analytics.

Jointly implemented by WI.Plat Co., Ltd., a South Korean technology company established by K-Water, and SUPRA International Indonesia, the project focused on two District Metered Areas (DMAs) covering approximately 4,000 household connections. Using NELOW’s AI platform and M1 IoT sensors, the system provided engineers with accurate and rapid leakage identification, enabling PDAM Sukabumi to take targeted actions without large-scale or costly equipment deployment.

By the end of the pilot, leak detection accuracy exceeded 80 percent and provided a foundation for sustainable NRW management in Sukabumi. The project was well received by the local government and positioned as a benchmark for other cities in Indonesia seeking to modernize their water loss control strategies.

Project Context

Perumdam Tirta Bumi Wibawa operates about 20,000 service connections across Sukabumi and faces persistent challenges in managing water losses. Traditional detection methods often require extensive manpower, large equipment investments, and lengthy search times.

With funding from KOICA, the project introduced a fully digital and data-driven approach that integrated IoT devices, cloud-based analytics, and AI. This allowed the team to identify leakage points with high precision and minimal operational disruption, while also building local technical capabilities for ongoing system monitoring.

Challenges

• High levels of NRW in target DMAs affecting revenue and reliability.


• Limited budget for conventional detection tools and manpower.


• Complex underground infrastructure with varying ages and materials.


• Need to improve the capacity of local technical teams in digital diagnostics

Approach and Methodology

The project applied a structured sequence of activities to ensure efficiency and measurable outcomes:

1. Deployment of IoT Acoustic and Pressure Sensors at strategic points in two DMAs, providing continuous data streams to the NELOW platform.


2. AI-Based Data Analysis using machine learning algorithms to process acoustic, flow, and pressure readings, identifying likely leakage points.


3. Targeted Field Verification by SUPRA engineers and PDAM staff using portable acoustic devices and manual inspections.


4. Performance Monitoring with a focus on reducing Minimum Night Flow by at least 30 percent in each DMA.


5. Stakeholder Coordination involving KOICA, PDAM management, and the city government to align objectives and reporting.

Key Results

• Achieved over 80 percent accuracy in detecting real leakage points.


• Reduced NRW levels within the pilot DMAs.


• Shortened detection cycle time and minimized unnecessary excavation.


• Enhanced technical capacity of PDAM teams in AI-supported leak detection.


• Strong positive response from municipal leaders and utility management.

Strategic Impact

The Sukabumi pilot demonstrated that integrating artificial intelligence, IoT-based monitoring, and targeted field verification can transform the way utilities manage water losses. The project proved that high detection accuracy can be achieved without excessive capital investment, allowing resources to be focused on targeted repairs that deliver measurable results.

It also showed that technology transfer and capacity building can be achieved in parallel, ensuring that the local utility can sustain the improvements beyond the pilot phase. The success of the initiative has encouraged discussions on scaling similar programs to other Indonesian cities facing critical NRW challenges.

The project established a replicable model for modern water loss management in developing urban contexts by bridging advanced engineering tools with practical field application. It strengthened the link between data, decision-making, and operational execution, positioning PDAM Sukabumi as an early adopter of digital utility practices in Indonesia’s water sector.