An ATR-Based Optoelectronic System for Real-Time Liquid Quality Monitoring Using Machine Learning and IoT

In this paper, an overview of a generic concept of a liquid-quality monitoring system based on the Attenuated Total Reflection (ATR) technology is provided. The system consists of the combination of an ATR sensor, a Raspberry Pi 4B as the IoT device, and machine-learning programs that run on the cloud to assess liquid properties in real time. The system is able to observe the optical behavior of the liquid and determine the state of the liquid and approximate changes that might occur. This may be practical in industrial procedures, in environmental surveillance activities and different food-safety uses.

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