Computer Vision for Glass Waste: Technologies and Sensors

TL;DR

This review explores technologies and computer vision sensors used specifically for managing and recycling glass waste.

Contribution

The paper provides a focused review on technologies for glass waste, including real-world implementations and patents.

Findings

Glass waste is often grouped with other materials, requiring specialized technologies for separation.

Computer vision sensors play a key role in identifying and sorting glass waste.

Real-world projects and patents show practical applications of these technologies.

Abstract

Several reviews have been published addressing the challenges of waste collection and recycling across various sectors, including municipal, industrial, construction, and agricultural domains. These studies often emphasize the role of existing technologies in addressing recycling-related issues. Among the diverse range of waste materials, glass remains a significant component, frequently grouped with other multi-class waste types (such as plastic, cardboard, and metal) for segregation and classification processes. The primary aim of this review is to examine the technologies specifically involved in the collection and separation stages of waste in which glass represents a major or exclusive fraction. The second objective is to present the main technologies and computer vision sensors currently used in managing glass waste. This study not only references laboratory developments or experiments on standard datasets, but also includes projects, patents, and real-world implementations that are already delivering measurable results. The review discusses the technological possibilities, gaps, and challenges faced in this specialized field of research.

Figures