An automated IoT-based audio announcement system for smart classrooms: integrating administrative broadcasts with lecture audio
Abstract Background Traditional classroom announcement systems rely on manual intervention, often disrupting lectures and causing communication inefficiencies. While smart classroom research has focused on energy management, attendance tracking, and environmental monitoring, the challenge of real-time audio coordination between public address systems and classroom lectures remains largely unaddressed. Results This study proposes an automated Internet of Things (IoT)-based audio announcement system that integrates administrative broadcasts with classroom audio infrastructure. The system utilizes an ESP32 microcontroller, a MAX98357A I2S amplifier module, and a relay-based switching mechanism to automate audio routing. A web-based platform enables authorized users to upload or record announcements, which are converted into MP3 format and stored in a centralized MySQL database. The ESP32 continuously polls the server and automatically triggers audio playback when new announcements are detected. Experimental evaluation over 150 test cycles across a two-week period demonstrates a mean end-to-end latency of 3.12 s (SD = 0.41 s), a mean relay switching time of 0.23 s, a 100% announcement delivery success rate, and zero instances of audio overlap or playback failure. Conclusions The proposed system demonstrates reliable and consistent communication performance in a single-classroom deployment and offers a modular architecture compatible with existing infrastructure. Future work will address multi-room synchronization, offline buffering, and formal scalability evaluation.
Authors
- Dip Nandi (ORCID: https://orcid.org/0000-0002-9019-9740)
- Mijanur Rahaman
Institutions
- American International University-Bangladesh (BD)
Publication Details
- Journal
- Journal of Electrical Systems and Information Technology
- Published
- 2026-09-15
- DOI
- https://doi.org/10.1186/s43067-026-00397-z
- Primary Topic
- Music and Audio Processing
- Type
- article
- Field-Weighted Citation Impact
- 0.00