Waste management companies are dependent on the quality and efficiency with which the bales, containers and materials are sorted. By digitizing their waste collection methods, this company aimed to improve the identification of waste and waste containers, a crucial process in managing waste and recycling services. With Sorting being a major bottleneck, they began looking up at Artificial intelligence and other Machine Learning technologies to assist them in identifying and organising waste.

Intellekt partnered with the client to use their expertise to identify and label waste and waste containers, based on computer vision that annotates images, video, or real-time video capture. Image Recognition and Image Annotation techniques allowed granular identification of pieces of waste and helped tag data for their Machine Learning (ML)models. The tags were analysed and categorized to identify appropriate disposal or recycle mechanisms, following which safe disposal or clean recycling was carried out.

Accurate annotation ensured that waste materials were identified andlabelled properly, thus helping the company build training data to train their machine learning models. By combining computer vision, machine learning, and artificial intelligence, the company was able to synchronize sorting and picking up recycledmaterials.