Design and Functional Evaluation of an Embedded Multiparametric Platform for Fermentation Monitoring

The continuous monitoring of physicochemical variables can provide temporally resolved information during fermentation processes while reducing dependence on discrete manual measurements. This work presents the design, implementation, and functional proof-of-concept evaluation of an embedded multiparametric platform for continuous monitoring in laboratory-scale fermentation environments. The platform integrates sensing, embedded data acquisition, local processing, chronological data organization, and automatic storage within a distributed architecture. Temperature, pH, dissolved oxygen (DO), and oxidation-reduction potential (ORP) were monitored using commercially available sensing devices integrated into a stainless-steel fermentation reactor with an approximate nominal capacity of 25 L and a working volume of 20 L. An Arduino Uno was used for sensor interfacing and data acquisition, while a Raspberry Pi 4 performed local processing, chronological organization, and automatic storage of the acquired information. The experimental evaluation comprised preliminary operation under controlled conditions followed by a Cabernet Sauvignon wine fermentation used as a real-process operating scenario to assess the integrated functionality of the platform under enological conditions. During the reported experiments, the sensing, acquisition, communication, processing, and data-management subsystems operated jointly and generated continuous, chronologically structured multiparametric records. The monitored channels exhibited distinct temporal patterns with comparatively gradual variations in temperature and pH and shorter-duration fluctuations in ORP and DO. The experimental protocol was designed to evaluate integrated system operation rather than the metrological performance of the individual sensing channels. Consequently, the recorded values should be interpreted as proof-of-concept monitoring data and not as validated analytical determinations of enological parameters. In particular, the absolute pH values recorded during the initial stage and the short-duration variations observed in ORP and DO cannot be unambiguously interpreted without synchronized measurements against reference instrumentation. The results demonstrate the feasibility of integrating multiple physicochemical sensing channels with embedded acquisition, processing, and automatic data-management capabilities within a common experimental platform. The proposed system therefore constitutes a laboratory-scale technological proof-of-concept and provides a basis for future work involving quantitative sensor characterization, repeatability and drift assessment, and validation against reference instrumentation before analytical or industrial-scale application.