Mixed municipal waste in Austria still contains a large proportion of recyclable materials, which poses a problem especially in view of the specified recycling quotas and the European Union's circular economy package. Ways are being examined to encourage citizens to improve the separation quality of mixed municipal waste. Saubermacher Dienstleistungs AG relies on an innovative technology called the reusable materials scanner. This system uses multi-spectrum cameras and sensors to record the contents of a waste container during the emptying process in the refuse collection vehicle. The imaged components of the mixed municipal waste are recognized using a Convolutional Neural Network (CNN). The waste composition of a container is thus automatically evaluated and the result is communicated to the citizen via various channels in a timely manner. The repeated feedback of the separation quality directly to the waste producer aims to motivate citizens to separate waste correctly. Within a project of Saubermacher Dienstleistungs AG, the reusable materials scanner has already been used in several pilot regions over a period of several months. In the context of this work the separation behaviour of the citizens as well as the effects of the reusable materials scanner in the pilot regions during the project are examined and evaluated. At first the system of the reusable materials scanner and the associated impact mechanisms on the citizen are described in detail. The associated project management as well as the project workflow are also covered. The evaluation of the collected data provides a clear presentation of the separation behaviour of the citizens. The verifiable effects of the reusable materials scanner are evaluated and discussed with regard to the additional logistical effort. Finally, optimization potentials and further fields of application of the reusable materials scanner are shown.