REAL-TIME DRINKING WATER QUALITY ASSESSMENT USING AN OPTOELECTRONIC SYSTEM
Keywords:
ATR, Optoelectronic sensor, IoT, Raspberry Pi 4B, Machine learning, Liquid quality, Optical parameters, Real-time monitoring.Abstract
This article proposes the concept of an optoelectronic liquid monitoring system based on the Attenuated Total Reflection (ATR) technology. The system integrates an ATR sensor module, an Internet of Things (IoT) device (Raspberry Pi 4B), and cloud-based Machine Learning (ML) algorithms, enabling real-time assessment of liquid quality. The proposed approach is designed to identify and predict categorical states of liquids by analyzing their optical parameters, with potential applications in industry, environmental monitoring, and food safety.
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