Pilot Demonstration of Smart Water Leak Detection Project in Buraydah, Saudi Arabia

 

Title  Pilot Demonstration of Smart Water Leak Detection Project in Buraydah, Saudi Arabia

Period   September 22 – September 26, 2024

 

 

Introduction

The pilot project in Buraydah, the capital of the Al-Qassim region in north-central Saudi Arabia, aimed to improve water management and reduce non-revenue water (NRW) by implementing WI.Plat’s advanced water leak detection technology. In collaboration with International Aramoon Co. Ltd. (IAC), we aim not only to identify and address leak points but also to train local workers to effectively use our systems. This project builds upon WI.Plat’s success in previous international projects and represents a significant step toward sustainable water management in the Middle East.

 

NRW Status

The challenge of non-revenue water (NRW) in Buraydah is significant, with many leaks detected throughout the existing infrastructure. These leaks not only contribute to substantial water loss but also hinder effective resource management in the region. Currently, International Aramoon Co. Ltd. (IAC) relies heavily on expert technicians for leak detection. IAC is actively seeking innovative and high-tech solutions to enhance their leak detection and management capabilities.

 

The adoption of WI.Plat’s advanced technology represents a critical step toward addressing these challenges, enabling IAC to implement more effective strategies for minimizing NRW and improving overall water distribution efficiency. The collaboration aims to foster a proactive approach in identifying and mitigating leaks, ensuring a sustainable water supply for the community.

 

Local Partner

International Aramoon Co. Ltd. (IAC) is specialized in No-Dig Leak Detection and Test and Repair for Water and Sewer Network. Accordingly, it is considered to be first local specialized Trenchless Technology contractor in the Kingdom of Saudi Arabia and the GCC Region.

 

Key Activities

Here are the key onsite activities performed during the project.

 

• GIS Data Collection and Analysis: The first phase of the project involved a comprehensive assessment of the study area, which includes 3,822 water meters, 150 valves, 22 hydrants, and 76 kilometers of pipelines. This extensive data collection was crucial not only for understanding the existing infrastructure but also for creating a robust Geographic Information System (GIS) framework. By mapping these elements in GIS, we gained valuable insights into the spatial distribution of the water network, enabling us prioritize areas for investigation.

 

 

• System Introduction and Training for Local Engineers: WI.Plat’s NELOW system and Sonic GL-F devices were introduced to local engineers from Aramoon during a series of comprehensive training sessions. These sessions were designed not only to familiarize the engineers with the advanced technology but also to provide them with hands-on experience in its application. By the end of the training, the engineers were well-equipped with the knowledge and skills necessary to effectively utilize the NELOW system and Sonic GL-F devices, empowering them to contribute to the project’s success.

 

• Leak Inspection: Following the training, WI.Plat and Aramoon engineers conducted leak inspections within a designated District Metered Area (DMA). The investigation process involved the collection of 203 sound recordings using Sonic GL-F devices. Twenty of these recordings were identified as potential leak sources, and chosen for further overnight monitoring using the GL-F loggers.

 

• Leak Validation: From the initial assessment, twenty recordings were flagged as potential leak sources. For these identified areas, a detailed inspection was conducted using multiple Sonic GL devices, strategically placed near suspected leak points. Data was collected at regular intervals—every 10 minutes—during nighttime when ambient noise levels are low, ensuring greater accuracy in detecting leak signals. NELOW system’s advanced correlation feature analyzes this data to identify continuous leak signals and estimate their exact locations, enabling targeted and efficient interventions.

 

• Leak Detection: Nine critical points were identified for additional investigation. WI.Plat’s engineers, alongside the local team, performed precise leak pinpointing, validating existing leaks previously suspected by the local staff. Additional points were confirmed by Aramoon’s local expert, further demonstrating the effectiveness of WI.Plat’s solutions.

 

 

 

• Pressure Logging and M2 Remote Sensor Communication Test: WI.Plat introduced pressure loggers to simulate both standard water pressure and water hammer effects. Additionally, the M2 modem communication tests were successful, demonstrating compatibility with local networks, including STC, Zain KSA, and Mobily.

 

• AI Customizing: WI.Plat will leverage the collected data from this project to customize an AI model, enhancing its accuracy for future initiatives in Saudi Arabia. The unique sound profiles captured are specific to the region, influenced by the local network infrastructure and water pressure conditions. By tailoring the AI model to these distinct characteristics, we aim to improve leak detection capabilities, ensuring more effective management of water resources in future projects.

Outcomes

The project yielded significant results:

• Potential Leak Points Identified: 9 potential leak sites, at least 1 confirmed.
• Sound Data Collected: 203 points, with 20 identified as suspicious for further analysis
• Local Worker Training: Local workers were successfully trained to use WI.Plat’s advanced leak detection devices, such as the Sonic GL-F and pressure loggers. This training enabled the local team to conduct investigations and pinpoint leaks independently.
• Modem Communication Test Success: Confirmed effective communication between M2 devices and local Saudi networks.

 

The project also allowed us to identify areas for improvements:

• Enhanced Ground Penetration with Metallic Stick: In environments such as sandy soil, where the detection of leak sounds at the surface proves challenging, equipping the Sonic GL with a metallic stick enables deeper insertion into the ground, thereby allowing the sensor to capture clearer sound signals close to buried pipelines, which ensures that leaks are not overlooked due to unfavorable conditions.
• Protective Cover for Noise Reduction: By outfitting the Sonic GL with a protective cover, which effectively shields the device from environmental disturbances like wind and ambient noise, we can ensure that only relevant leak sounds are recorded, thus improving data quality and minimizing the risk of false positives resulting from external interference.
• Efficient Data Collection from Outdoor Meters: The positioning of the water meters outdoors facilitated straightforward data collection during the project. With minimal obstructions and easy access, local teams were able to gather data efficiently.
• Consistent Water Pressure for Leak Detection: The relatively constant water pressure during the project period provided a stable environment for leak detection efforts. This consistency enabled our team to conduct thorough checks throughout the day, enhancing the reliability of the findings.
• Low Ambient Noise Levels: The project benefited from low ambient noise levels, which greatly aided in the pinpointing of potential leaks. With fewer competing sounds in the environment, the Sonic GL could operate more effectively, allowing for clearer detection of leak signals.

 

The Buraydah pilot project highlighted the potential of intelligent water management solutions in Saudi Arabia. WI.Plat’s NELOW system demonstrated its ability to detect leaks efficiently and foster collaboration between local teams and international expertise. The project lays the groundwork for future water management initiatives in the Middle East, promising improved water conservation and resource management. The integration of advanced technology and local know-how offers a sustainable path forward in tackling NRW and enhancing the overall efficiency of the water distribution network.