This demonstration presents a set of services for streamlined experimental evaluation and benchmarking of RF-based indoor localization algorithms using previously collected raw measurements. The platform consists of an online service for storing and managing raw indoor localization data collected in a set of extensive experiments. The platform also integrates a cloud based service for calculation of a standardized set of metrics for characterizing the performance of indoor localization algorithms. To simplify the access to the above services, we also offer a set of Software Development Kits (SDKs) for their use from Python and MATLAB. Experimenters are able to “link” the platform to their indoor localization algorithms, use previously collected data to evaluate the performance of their algorithms and calculate a set of metrics for characterizing their performance.


Raw Data Storage Service

Raw Data Visualization Tool

Metrics Calculation Service

Experiments Results Storage Service

EWSN'15 Demo Paper

Infrastructure Used for Data Collection


Python SDK