The system enables using digitalized product features during the traditional, offline purchase process. It will build the AR- based digital twin of a retail store. The research results will open the new ways of product selection, presentation and promotion which were previously booked solely for e-commerce.

From consumer’s point of view, Reetail:AR provides the enhanced product information and immersive AR experiences, as well as the functional, filter-based (e.g eco, paraben-free) purchase recommendations, while using a mid-range smartphone.

The project’s R&D work activities are:

• DATMO-based methods for simultaneous, real-time detection and tracking of multiple FMCG products in the conditions of a retail store and using the limited computational resources of a smartphone
• real-time, FMCG product image search methods, based on the products’ physical shape and labels
• multi-criteria-based product recommendation method dedicated for offline shopping, using consumer behaviour and context data as an input
• methods for improving the performance of the above mentioned components, which are able to overcome the smartphone’s computational power limitations
• the user layer (incl. tool for B2B product management and SDKs for developing the consumer apps) which integrates the system components and ensures their performance.