IoT-Based Indoor Air Quality Using Esp32

The Abundance of Information on the Air Quality Index (AQI) uses a lot of energy in commercial buildings. As a result, energy efficiency and consumer convenience have decreased, mainly as a result of weak supervision. We recommend using a live AQI control system that complies with User Settings energy management guidelines to automate AQI operations in real time. The devices in our system are housed in a lab and built on an IoT (Internet of Things) architecture. Thermal parameters are also received automatically from the sensor with the right sensor, and user input data is collected. to process information in real-time in a distributed cloud setting. To do this, we use the Blynk Application Programming Interface (API). by using an automation system method to monitor sensor data in real-time allowing adjustments to dynamic temperature settings and regular user input. It is based on user feedback, power management guidelines, and sensor readings. The efficacy of the AQI is measured mathematically. The purpose of this study was to determine the level of cleanliness of the air from a room. Our Tests reveal that we have managed to save a total of 0.9 kWh while continuing to maintain the thermal comfort of our users.