The paper describes an end-to-end system for optimal Bluetooth beacon deployment in an indoor environment. The system allows accurate indoor positioning in realistic scenarios with signal attenuation from various objects, e.g. walls or furniture. It also satisfies a number of common practical requirements: 1) it computes beacon placement that achieves maximal coverage for a target area within an allocated beacon budget; 2) it allows specifying areas of higher importance whose signal coverage needs to be prioritized, in case of insufficient beacon budget; 3) it allows optimal local-only beacon adjustment in case of layout changes, without the need of re-positioning all previously placed beacons.There are three main components in the proposed system: floorplan representation converter, beacon signal coverage simulator, and beacon placement optimization model. The floorplan representation converter conflates and transforms multi-source inputs into floorplan representations that are used by the signal coverage simulator and the optimization model. The simulator provides realistic radio coverage simulation for the target environment. In the beacon placement optimization model we propose a novel multi-objective loss function, the solution to which is computed through an evolutionary algorithm. We demonstrate the generated optimal placement on synthetic as well as real office building floorplans. The system is compared to random and grid-based beacon placements.

The paper describes Streetside Building Search-Retrieve System (SBSRS) - a system for recognizing buildings from steetside images. SBSRS powers several distinct applications: 1) it improves map-search by enriching its streetview service with semantic information, such as location, business name, open hours, etc.; 2) it enables search by image and location - a novel form of visual image search where both visual and location signals are used to identify the most relevant result to a query image of a building.