Citation:

Mrs. Shiny Pradheepa, Madhumitha.S, 2026. "An AI-Based Ventilation KPI Using Embedded IoT Devices", ESP Journal of Engineering & Technology Advancements  6(1): 150-155.

Abstract:

An AI-based Key Performance Indicator (KPI) framework is developed for monitoring and controlling ventilation quality using embedded devices.The system integrates real-time data from MQ-02 and MQ-135 gas sensors, processed through machine learning algorithms to generate predictive outputs that guide ventilation control decisions. The trained models, optimized for embedded deployment, track essential KPIs such as air quality index, ventilation efficiency, and response time, enabling smart, adaptive ventilation management. By embedding these models into compact, low-cost IoT devices, the solution ensures scalability, low power consumption, and reliable operation in diverse environments. This approach transforms raw sensor data into actionable insights, enhancing ventilation performance while supporting sustainable and intelligent infrastructure within the broader vision of Smart Cities.

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Keywords:

AI-based Ventitilation, IOTdevices, KPI, Real time monitoring, Gas sensor, Embedded device.