The recycling of waste materials plays a key role in conserving natural resources. To promote material circularity, it is necessary to consider all processes along the value chain, from raw material extraction to waste management and processing. Effective collection and sorting of end-of-life products and packaging are crucial prerequisites to achieve high recycling rates, minimize energy consumption and reduce material losses. However, a significant proportion of post-consumer waste is not properly returned to established waste management systems by citizen. To address this challenge, recent developments in AI-based object classification can support citizens in the form of a mobile app. This type of application can assist users in identifying items and suggests the most effective location-aware recycling pathways to facilitate waste separation by type. To raise these potentials, a framework is presented that combines two apps: one for citizen to optimize recycling routes and a second app for collecting data to train the machine learning models. A novel classification system was created, and data suitable for AI training were collected to ensure the effectiveness of the system. In future, this application can contribute to directing household material flows into specific recycling pathways. In this way, the application can strengthen the circular economy in Europe and support environmental protection efforts.