SPACE: Semantic-enhanced Placing AlloCation for smart Environments

The project proposes an integrated framework which uses augmented reality and knowledge representation theory and languages to allocate objects in a space in the best possible way with automatic recombination when modifications are introduced. No limits are given to objects' shape and type and to space dimension. The application performs a sub-optimum allocation by taking into account stereoscopic features of both objects and environment but also intrinsic characteristics of them such as operating temperature, material, frangibility, light/darkness incompatibility, climacteric issues, priority usage, power requirements and so on. A simple interaction is required to the user: geometric information is automatically retrieved by targeting both container and objects to be contained via a smartphone camera suited by Tango. Instead, relevant additional information can be annotated through a visual interface via drag and drop gestures. Alternatively, the QR code on the object or RFID protocol standard (in case of equipped smartphones) can be used to associate annotations remotely stored. Space optimization is performed, but also integrity and compatibility checks concur to determine the optimal object to space relation. Noteworthy is the capability to fill to the best possible extend very small spaces as well as huge areas (luggage, trunks, containers, rooms, warehouses). Finally, suggested allocation is shown to the user diplaying objects into the real world exploting motion tracking, area learning and depth perception features of Project Tango