Smart waste disposal logistics solution using semiconductor-based electrically reduced graphene oxide odour sensors
The vision of the project is to use an interdisciplinary approach from the fields of chemistry, sensor technology, artificial intelligence and logistics to develop an intelligent IoT-capable smell sensor for the Smart Waste Bin in order to not only obtain important information about the composition of the waste but also, to optimize the recycling process in view of the EU's climate goals.
The basic idea of this application is based on an innovative approach to improve the sensor specificity by integrating graphene-based sensors and mimicking the natural combinatorial code using machine learning. By varying the recognition units and the film properties of the sensor materials in a targeted manner the sensor performance of the multivariable sensor platform is systematically investigated with regard to the specificity of a large number of singular, binary and complex gas mixtures.
The goal of the project is to test the interaction and efficiency of the 4 concepts in an IoT-capable prototype under real world conditions, and to validate the quality of the sensor outputs regarding the actual waste composition.