indoorPositioning | make indoor positioning by using Raspberry Pi

indoorPositioning is a C# library typically used in Manufacturing, Utilities, Machinery, Process, Networking applications. indoorPositioning has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Estimating the location of a Bluetooth capable device in an indoor environment has many practical purposes. Either for a smart warehouse with autonomous robots carrying the goods around, or for a classic multi-storey office with employees moving from one place to another, or for a vacation compound where crowded groups of tourists can go to swimming pools, restaurants, and other activity locations with a wearable computer (e.g. a smart bracelet, or a necklace), instantaneous information about where these people are at a certain time period, and where they are moving to, will definitely help organizational planning. Tracking employees on how much time they spend outside their workspace would be an important performance metric especially in production lines. In the case of tracking tourists, the hotels can adjust their security, and other services according to the movement of their guests. For the smart warehouse, location estimation has to be so precise that a robot should never place things in wrong shelves, nor it should look for items that do not exist at the current location of the robot. Indoor positioning can be performed using a set of stationary Bluetooth access points. Location estimation inside a building is harder than doing it with GPS. One of the major approaches in indoor positioning is to use a fingerprinting database, trained with multiple signal level measurements at specific locations, covering the entire area, with respect to each available access point. The other major approach is to use triangulation, which is based on coordinated location estimation using at least three access points, and signal arrival times. The arrival time can be calculated at the stationary access points, or the mobile device itself. This method can be roughly considered as an indoor alternative to the GPS solution. In this project, we are going to implement a hybrid solution of fingerprinting and triangulation.