AUTONOMOUS IOT-BASED CLASSROOM MICROCLIMATE MONITORING SYSTEM USING AN OPEN DIY ARCHITECTURE
DOI:
https://doi.org/10.32782/mathematical-modelling/2025-8-1-24Keywords:
Internet of Things (IoT), indoor monitoring, automation system, local automation methods, data mining, optimization, decision-makingAbstract
The article presents the architectural model of an autonomous system for monitoring microclimate parameters in educational environments, implemented using Internet of Things (IoT) technologies based on an open Do It Yourself (DIY) architecture. The proposed solution is aimed at creating a flexible, scalable, and cost-effective system that enables local collection, processing, and real-time visualization of environmental indicators without relying on external cloud services. The system follows a three-tier architecture: the edge level includes ESP32 microcontrollers with connected sensors for temperature, humidity, and CO₂; the server level is implemented using PostgreSQL extended with TimescaleDB and a RESTful API for data storage, verification, and processing; and the client level includes a web interface developed using React and Chart.js, providing interactive access to data visualization in accordance with standard thresholds (ISO 7730, DBN V.2.5-67:2013). The relevance of this research is driven by the need to implement affordable, open, and secure tools for environmental monitoring in the context of limited funding for educational institutions. Commercial IoT systems often exhibit significant drawbacks such as high cost, closed architecture, dependence on cloud infrastructure, and limited support for non-standard sensor configurations. The proposed solution addresses these limitations by offering complete autonomy, local data management, a high level of confidentiality, and adaptability to the specific requirements of individual classrooms. The system also includes a mechanism for automatic alerts in cases of regulatory parameter violations, allowing timely identification of potential risks to health and educational performance. In addition to its practical value, the proposed development has strong educational potential, serving as a platform for teaching students in the fields of microelectronics, programming, data analysis, and IoT security. The results confirm the feasibility of using open hardware and software solutions in education and highlight the prospects for scaling the system to other types of spaces, such as offices, laboratories, or public facilities.
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