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Student Project | Electronics & Communication Engineering | India | Volume 12 Issue 6, June 2023 | Rating: 5 / 10
Machine Learning - Based Fault Detection and Water Quality Analysis in IoT - Enabled Water Pipeline System
Yamiko Daniel Banda
Abstract: The Internet of Things technology has helped improve water pipeline monitoring and maintenance. We can establish a comprehensive network by integrating sensors and devices. Real - time information can be collected and analyzed. This will help solve the challenge of monitoring drinking water pipelines for potential breaks or cracks that could develop into leaks. Early crack detection allows utilities to fix issues before they worsen and become costly. Real - time monitoring of drinking water is vital to detect potential breaks and cracks in water pipelines. This is because small cracks can quickly develop into leaks, resulting in water loss and high maintenance costs. Therefore, early detection of cracks can help prevent leaks and conserve water resources by minimizing wastage. Identifying and repairing cracks can reduce water loss, saving costs associated with water loss, infrastructure damage, and emergency repairs. Addressing cracks promptly can also avoid potential accidents like pipeline failures or contaminated water, ensuring public safety and the safety of workers. Timely monitoring and maintenance of water pipelines is thus essential to conserve water, save costs, and ensure safety.
Keywords: Pipeline Monitoring System IoT, sensors, Water pipeline, Random Forest Algorithm, Dataset
Edition: Volume 12 Issue 6, June 2023,
Pages: 2662 - 2667