Year: 2025
Type: article
Abstract: The development of an embedded IOT device for real-time monitoring and control of artificial intelligence (AI)-driven ventilation systems. The device integrates sensors for air quality parameters (e.g., CO2, particulate matter, temperature, humidity) and transmits data wirelessly to a cloud platform.AI algorithms deployed on the cloud analyze the sensor data to optimize ventilation parameters, ensuring efficient energy usage and improved indoor air quality. Key Performance Indicators (KPIs) such as energy consumption, air exchange rate, and pollutant concentration are continuously monitored and displayed on a user dashboard. The embedded device facilitates closed-loop control, adjusting fan speeds and damper positions based on AI-derived insights. This system aims to enhance occupant comfort, reduce energy waste, and maintain optimal air quality in various environments like hospitals, offices, and residential buildings. The device’s modular design allows for scalability and customization to specific ventilation system requirements. The IOT infrastructure enables remote monitoring, predictive maintenance, and data-driven decision-making for efficient AI-controlled ventilation
DOI: 10.46632/jeae/4/2/20
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409647432