Smart Classroom Environment Monitoring System

Classroom conditions such as temperature, humidity, lighting and noise strongly affect student comfort and concentration, yet they are usually checked manually or not monitored continuously, so unsuitable conditions are noticed late. This paper proposes the Smart Classroom Environment Monitoring System, an IoT-based monitoring and analytics solution. An ESP32 microcontroller reads temperature, humidity, light intensity and ambient noise sensors at defined intervals, attaches date and time to each reading and sends the data to a database, where historical records are maintained. A data cleaning stage handles missing, duplicate, invalid and inconsistent readings. An interactive Power BI dashboard with KPI cards, charts, filters and trend analysis then turns the raw readings into information that helps teachers and administrators identify unusual conditions and support corrective decisions. The system is organized into four modules: environmental sensing and ESP32 data acquisition; data transmission, database and data preparation; Power BI dashboard and data analysis; and monitoring and decision support. This paper presents the architecture, methodology and planned evaluation of the proposed low-cost system.