Deep-Learning-Based Image Recognition to Help Create Greener Commercial Energy Systems

A unique deep learning-based image recognition technique for the extensible implementation of on-demand defrosting control has been presented in a recent study published in the journal Applied Energy. Study: Deep learning-based image recognition method for on-demand defrosting control to save energy in commercial energy systems. To increase recognition accuracy, the researchers utilized a convolutional neural network (CNN) model to extract intricate and difficult features for frosty state detection. Commercial energy systems significantly contribute to global energy consumption and are essential for providing operation power and assuring comfort. The most common issue with heat exchangers in commercial energy systems is frost formation.