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Indoor User Movement Detection


Location-based Services have seen a crucial push in the last couple of years. The majority of these services are in the field of outdoor LBS as outdoor positioning of devices has been easily available (Cell-ID, WiFi, GPS). In indoor environments, positioning systems are typically highly expensive and need specialized hardware in order to detect the users' movement pattern.

The objective of this project is to enable the detection of user movements by analyzing the periodically emitted Wi-Fi signals of smartphones. The analysis will include the generation of user movement paths and the visualization of them.


  • Get familiar with WiFi signal behavior and Indoor Location Analytics
  • Implement a client application which collects, pre-aggregates and forwards the WiFi-Signal data
  • Implement a server application for processing the collected data
  • Design an algorithm for detecting the movement behavior of users  between multiple recording nodes
  • Build a visualization of the detected user paths


  • Interest in Indoor Location-based Services, Data Analytics
  • Good experience in programming, Unix, scripting, databases
  • Beneficial: NoSQL Databases (MongoDB, Redis, Neo4j, etc.)
  • Beneficial: Experience in data analysis (Big Data / Data Mining)



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TU Berlin - Service-centric Networking - TEL 19
Ernst-Reuter-Platz 7
10587 Berlin, Germany
Phone: +49 30 8353 58811
Fax: +49 30 8353 58409