Optimizing indoor humidity control with AI: Case study in Abu Dhabi

Abstract

Indoor air quality is a critical factor in human health and comfort, especially in regions with extreme climatic conditions like Abu Dhabi. Traditional humidity control methods often struggle to maintain optimal indoor environments, leading to energy inefficiency and occupant discomfort. This research investigates the potential of artificial intelligence (AI) to enhance humidifier performance and optimise indoor humidity levels. By integrating sensors and AI algorithms into a humidifier (Econavi technology), we aim to create a system capable of autonomously adjusting humidity levels based on real-time data and occupant preferences. We will assess the AI model's effectiveness in achieving and maintaining desired humidity levels through experimental analysis in a controlled environment. The findings of this research contribute to the advancement of smart home technologies and provide insights into the potential of AI for improving indoor environmental quality. This study will help to understand the behaviour of AI algorithms in controlling humidity by real-time data through the sensors.