AI-Based Control Strategies for Dynamic Ventilation Systems to Improve Indoor Air Quality in Smart Buildings

Rene K. Torres; Adedeji F. Samuel

Authors

Rene K. Torres Author
Adedeji F. Samuel Author

Keywords:

Indoor air quality, dynamic ventilation systems, artificial intelligence, smart buildings, machine learning, IoT, predictive modelling

Abstract

Indoor air quality (IAQ) is a critical component of occupant health, comfort, and productivity in smart buildings. Dynamic ventilation systems integrated with artificial intelligence (AI) provide adaptive, real-time solutions for maintaining optimal IAQ while conserving energy. This paper explores AI-based control strategies for ventilation systems, emphasizing machine learning algorithms, predictive modeling, and IoT-enabled frameworks. It evaluates the existing body of research and presents simulation results showcasing AI's potential to revolutionize ventilation system efficiency. A comparative analysis with traditional approaches highlights the tangible benefits of AI in maintaining superior IAQ standards.

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