Citation :

Shiny Pradheepa, Madhumitha.S, 2026. "An AI-Based Ventilation KPI Using Embedded IoT Devices" ESP International Journal of Advancements in Science & Technology (ESP-IJAST)  Volume 4, Issue 1: 69-72.

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. These streamlined models are designed specifically for embedded deployment, continuously monitoring critical KPIs related to air quality index, ventilation efficiency and response time to ensure smart order situational adaptive ventilation. The solution has scalability, low power consumption and stable functioning under various conditions-all because these models are combined with small IoT devices (they don't differ in size and price from ordinary calculators or digital watches). By processing raw sensor data into actionable insights, this helps to improve ventilation performance and contributes toward green, smart infrastructure in the archetype of Smart Cities.

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Keywords :

AI-Based Ventilation, IOT Devices, KPI, Real Time Monitoring, Gas Sensor, Embedded Device.