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There is nothing new about the fact that higher concentrations (up to 50 times) of valuable materials can be found in e-waste, compared to mined ores. Moreover, the constant accumulation of excessive amounts of waste equipment has a negative impact on the environment. The components found in electronic equipment may contain hazardous materials or materials that could be recycled and reintroduced into production processes, thus reducing the carbon footprint created by waste electrical and electronics equipment (WEEE). Sustainable e-waste recycling requires high-value, integrated recovery systems. By implementing a two-stage experimental sorting stand, this paper proposes an efficient and fast sorting method that can be industrially scaled up to reduce the time, energy and costs needed to sort electronic waste (e-waste). The sorting equipment is in fact an ensemble of sensors consisting of cameras, color sensors, proximity sensors, metal detectors and a hyperspectral camera. The first stage of the system sorts the components based on the materials’ spectral signature by using hyperspectral image (HSI) processing and, with the help of a robotic arm, removes the marked components from the conveyor belt. The second stage of the sorting stand uses a contour vision camera to detect specific shapes of the components to be sorted with the help of pneumatic actuators. The experimental sorting stand is able to distinguish up to five types of components with an efficiency of 89%.

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