Our project aims to digitize the waste industry by combining a novel digital SMELL sensor with an Internet-of-Things (IoT) based platform. From an industrial and societal point of view incorrect waste-separation or contaminations in household-, bio-, paper- or industrial waste dramatically increase recycling costs and decrease efficiency due to mandatory post-separation steps thus hindering a responsible and respectful use of natural resources. While a number of commercial sensors try to monitor the content of waste bins using ultra-sound (fill-level), microphones (rough classification) or optical sensors (requires high computational resources) none of these systems can truly determine the composition of the waste or detect visually hidden components (e.g. typically waste is disposed in plastic bags). Our solution to this challenge is to develop a SMELL sensor consisting of a 12-channel array of individually functionalizable and tunable sensors. The sensing materials are conducting polymers with broad overlapping specificities. Exposure to different odors changes the electronic properties of the different types of conducting polymers in the chemiresistor configuration, thus generating a unique pattern, which resembles the combinatorial code of our own olfaction system. Similarly, to the pattern recognition work performed by our brain, we use advanced machine learning algorithms to analyze the resulting patterns, thus obtaining a “smell picture” of the waste. Complementary to the information obtained from the SMELL sensor, SLOC’s IoT-platform provides information about fill-level, position, acoustic sensors, lid-openings, temperature and humidity. The combined data is then transferred via newest communication technology (5G) to a secure cloud sever for further processing and automatic dispatch of the correct waste trucks using optimized routes. Our concept of merging innovative SMELL sensors with an IoT-platform is more than the sum of its parts and will contribute to the vision of a Smart City using a Waste Management 4.0 solution.