Abstract

This paper presents the development and experimental validation of a low-cost IoT-enabled turbidity monitoring platform intended for laboratory-scale bioprocess applications. The proposed system was designed as a modular turbidity acquisition subsystem that can be integrated into broader bioreactor automation platforms. The hardware architecture is based on an ESP8266 microcontroller, a TS-300B optical turbidity sensor, a resistive voltage divider for analog signal conditioning, an OLED display for local visualization, and a Google Sheets-based cloud logging solution. A blank-based relative Turbidity Index was defined in order to compensate for optical configuration and environmental variations. The embedded firmware implements multi-sample averaging, blank calibration, serial command control, local display updates, CSV logging, and optional cloud transmission through HTTP requests. The calibration procedure was performed using serial dilutions of a yeast suspension, and the obtained data were fitted using a nonlinear power-law model and a log-log representation. An additional comparison with OD600 reference measurements showed a monotonic relationship between the proposed Turbidity Index and conventional optical-density measurements. The system was further validated through a yeast-based monitoring experiment performed under consistent optical conditions. The results showed the capability of the platform to acquire, process, visualize, and store turbidity-related data over an extended interval. The proposed platform provides a practical, affordable, and reproducible solution for turbidity monitoring and IoT-based data acquisition in small-scale bioprocess applications.

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