Integrated Management of Electronic and Electric Waste (EEW) with the Application of Artificial Intelligence (AI)

Abstract

Electric and electronic waste (EEW) is a growing concern around the world. With technological advances, industries have moved towards greater automation, which has increased the use of electrical and electronic equipment. Electrical and electronic products have become common in the daily life of the average consumer, frequently used in manufacturing and other industries. The continuous updating of increasingly performing and reliable technologies has led to a decrease in the life cycle of the product, which pushes to always buy the most innovative electronic product, discarding obsolete products. All these developments have in turn led to an exponential increase in the production of electronic waste. The implementation of artificial intelligence (AI) allows automated machines – collection bins, vehicles, conveyor belts, storage – to identify common electronic waste based on learning about transfer from images and other specifications that will accelerate the collection and recovery of electronic waste. Complex identification systems based on convolutional neural networks are used to classify electronic waste with high accuracy.