GeoLBS Indoor Positioning System With Privacy Protection

With the development of radio technology, it is possible to utilize Wi-Fi fingerprint as feature to identify user’s location. Due to the fluations of Wi-Fi signal, this paper introduced inertial positioning to enhance the indoor positioning system performance. Besides, location based service could divulge user’s privacy, and aiming for protecting user’s information, this paper designed location anynimizer to blur user’s real location.In this paper, it did comprehensive study on Wi-Fi fingerprint positioning and inertial positioning, and also it analyze the features of RSSI signal propagation and all environment factors which could affect indoor positioning accuracy. In addition, inertial positioning has the issue of error accumulation and other measuring problems. Based on those researches, by integrating Wi-Fi fingerprint positioning and inertial positioning, it implemented the GeoLBS system that provided high accuracy and high reliable indoor positioning solution. As for LBS privacy protection problem, the paper separately demonstrated the location anonymization and id concealing technique. It developed a middleware which provided location anonymization, and through adjust its parameter it could balance privacy leaking risk and system consumption. For theoretical analysis and algorithm solution designed above, the paper degiend and implemented GeoLBS platform which included indoor positioning function and LBS privacy protection function. GeoLBS platform was based on B/S architecture, and its server side was upon Django Framework, and cloud service used Baidu Map. Through B/S architecture, it avoids high computing consumption on mobile terminal, and it strenghened the system extensibility. As testing result shows, fused indoor positioning system could increase positioning accuracy and stability, and also anonymizer could prevent cloud service collecting user’s data concerning its privacy.