Розробка системи моніторингу та управління на основі екологічних ключових показників ефективності для освітніх SMART-лабораторій

The object of research is a set of processes for monitoring and intelligent control of energy consumption and the state of the SMART laboratory environment, aimed at improving its environmental safety. The research problem is aimed at implementing integrated automated systems based on: monitoring, forecasting and adaptive control in real time of SMART laboratories. The research used methods for synthesis and analysis of energy consumption monitoring systems, microclimate control, CO2 concentration forecasting and algorithms for adaptive control of educational environment resources. Basic and extended key performance indicators (KPIs) have been formed for the SMART laboratory monitoring subsystem, which take into account the state of the microclimate and comfort, energy, environmental and operational indicators, and are the basis of modern eco-maps of the premises. The adaptive control subsystem uses adaptive control logic based on a predictive model. The developed open software and hardware architecture based on Node-RED integrates automation and environmental audit tools into a single analytical platform adapted to different types of educational locations. The adaptive automatic control system for SMART laboratories based on integrated predictive ML models contributes to a controlled reduction in energy consumption by more than 40%, in particular by reducing the average power from 4.1 kW to 2.4 kW. While traditional operating modes of laboratory equipment without adaptation are characterized by a high level of carbon intensity. According to the results of the LCA analysis, the total carbon footprint at the operational stage decreased from 1.85 to 0.47 kg CO2/hour. The use of the proposed monitoring and control system for SMART laboratories forms a modern technical and software solution that meets the criteria of sustainable development.