Smart Ironing Appliance using Real-Time Fabric Classification and Automatic Temperature Control

Ironing is a common household task that requires careful temperature control to prevent damage to different fabric types. Traditional irons rely on manual temperature adjustment, leading to errors and potential fabric damage. This paper implements an innovative solution to automating iron temperature control using a machine learning-based fabric type classifier. The classifier response is used to adjust the temperature of the iron automatically. By integrating computer vision technology and machine learning techniques with the hardware control system, the proposed solution aims to enhance the ironing experience, reduce fabric damage, and improve energy efficiency with a simple, easy-to-use, cost-effective end product.