Integrating HMI display module into passive IoT optical fiber sensor network for water level monitoring and feature extraction
Sri Harsha Grandhi
Abstract
This research explores the integration of Human-Machine Interface (HMI) display modules with passive IoT optical fiber sensor networks to enhance water level monitoring systems. Utilizing Fiber Bragg Grating (FBG) sensors for their high sensitivity and reliability, this study aims to provide real-time data visualization and advanced feature extraction to aid in environmental management and flood prevention. The methodology involves deploying FBG sensors across water bodies, capturing data through an IoT gateway, and using HMI modules for user-friendly interfaces. Signal conditioning, feature extraction, and machine learning algorithms are employed to ensure data accuracy and predictive analytics. Testing and validation are conducted to ensure system robustness, with performance metrics including accuracy, reliability, response time, data integrity, and power efficiency. The integration of HMI display modules into optical fiber sensor networks presents a comprehensive solution for efficient and effective water level monitoring, improving data accessibility and decision-making capabilities.