A material handling system sorts materials utilizing a vision system of multiple vision devices configured with single board computers that each implement an artificial intelligence system in order to identify or classify materials, which are then sorted into separate groups based on such an identification or classification by sorting devices that are each coupled to one of the vision devices.

Provided is a method for processing electronic and electrical device component scrap, which can accurately and efficiently sort electronic and electrical device component scrap. The method for processing electronic and electrical device component scrap includes a separation step of separating non-metal objects 1b or metal objects 1a.sub.1, 1a.sub.2 from electronic and electrical device component scrap 1 containing the metal objects 1a.sub.1, 1a.sub.2 and the non-metal objects 1b using a sorter 10 comprising a metal sensor 2, a color camera 3, an air valve 4, and a conveyor 5, wherein a fixed distance is provided between the metal objects 1a.sub.1, 1a.sub.2 adjacent to each other so as to prevent the non-metal objects 1b between the metal objects 1a.sub.1, 1a.sub.2 from being erroneously detected, when detecting the metal objects 1a.sub.1, 1a.sub.2 in the electronic and electrical device component scrap 1 by the metal sensor 2.

Recycling systems can include a conveyor system, an optical device, and a processor operable to detect, identify, and count redeemable objects. The conveyor system can include a plurality of bins and be configured to move the bins from a first end of the conveyor system to a second end of the conveyor system. The optical device can be situated and configured to capture an image of a plurality of objects within a bin of the conveyor system. A processor including computer-readable instructions can be configured to detect and identify the objects within an image captured by the optical device as belonging to one or more object classes. Each object class can determine whether an object is redeemable or unredeemable. The processor can be configured to provide a count of only those objects identified as redeemable.

An apparatus for classifying materials utilizing a vision system, which may implement an artificial intelligence system in order to identify or classify each of the materials, which may then be separated from a heap in a scrap yard into separate groups, such as other heaps, based on such an identification or classification. The artificial intelligence system may utilize a neural network, and be previously trained to recognize and classify certain types of materials.

Image data is obtained that indicates an extent to which one or more objects reflect, scatter, or absorb light at each of multiple wavelength bands, where the image data was collected while a conveyor belt was moving the object(s). The image data is preprocessed by performing an analysis across frequencies and/or performing an analysis across a representation of a spatial dimension. A set of feature values is generated using the image preprocessed image data. A machine-learning model generates an output using to the feature values. A prediction of an identity of a chemical in the one or more objects or a level of one or more chemicals in the object(s) is generated using the output. Data is output indicating the prediction of the identity of the chemical in the object(s) or the level of the one or more chemicals in at least one of the one or more objects.

A recycling identification container, including a main body, including a first section to store at least one trash item therein, a second section connected to the first section to store at least one recycle item therein, and a divider disposed between at least a portion of the first section and the second section to separate the first section from the second section, a cover unit removably connected to at least a portion of a first end of the main body to cover an interior of the main body, and an identification scanner disposed on and within at least a portion of the main body to scan properties of at least one item based on a predetermined algorithm to determine whether the at least one item is at least one of the at least one recycle item and the at least one trash item.

A spent and/or decommissioned accumulator treatment plant and process, wherein a plurality of objects originating from separate waste collection of spent and/or decommissioned accumulators, nominally comprising lead-acid accumulators and accumulators and objects of a different type, are subject to an X-ray scan. If an analysis of the X-ray scan indicates that an object is not a lead-acid accumulator, and in particular is a lithium-ion battery or accumulator, it is deviated out of the treatment workflow, that comprises grinding the objects and separating lead from other materials.

The disclosure relates to a method for the analysis and/or sorting of scrap metal, more particularly of scrap aluminium, in which a quantity of scrap metal, more particularly aluminium scrap, in the form of a scrap bundle or a group of scrap bundles is provided, in which method the scrap bundle or the group of scrap bundles is irradiated by at least one neutron source, the gamma radiation emitted by the scrap bundle or by the group of scrap bundles is captured by at least one detector, and composition information relating to the composition of the scrap bundle or the group of scrap bundles is determined on the basis of the gamma radiation captured by the at least one detector. The disclosure further relates to a device for analysing and/or sorting scrap metal.

A method and system for marking and encoding recyclability includes material identification markers to enable a robot with computer vision capability to properly identify and distinguish between various materials. The material identification markers could include marks or symbols to describe a recyclable item or material. The material identification markers may be incorporated into the design of the item, printed on the item or label, or placed in any other way as this is a vision-based system. Further, the material identification markers may be visible or invisible to the human eye.

An illustrative embodiment disclosed herein is a method including receiving, by a waste diversion system and from a source, waste materials, inserting, by the waste diversion system and into the waste materials, one or more markers, generating, by the waste diversion system, finished goods including a portion of the waste materials, and detecting, by the waste diversion system, a portion of the one or more markers corresponding to the portion of the waste materials in the finished goods.