Smart Space - An Indoor Positioning Framework

Smart Space - An Indoor Positioning Framework Droidcon 09 Berlin, 4.11.2009 Stephan Linzner, Daniel Kersting, Dr. Christian Hoene Universität Tübingen Research Group on Interactive Communication Systems (ICS)

Agenda 1. Location Matters! 2. Indoor Localisation Techniques 3. SmartSpace Framework (SSF) 4. Opportunities 2 von 24

Location Matters! Location changes everything. This one input our coordinates has the potential to change all the outputs. Where we shop, who we talk to, what we read, what we search for, where we go they all change once we merge location and the Web. Mathew Honan, WIRED magazine, 19.1.2009 3 von 24

BUT Location for outdoor environments is provided by the Global Positioning System (GPS) 4 von 24

BUT Location for outdoor environments is provided by the Global Positioning System (GPS). there is no solution for indoors yet! http://www.waagner-biro.at/ 4 von 24

AND New generation of mobile devices with multiple sensors WLAN, GSM/CDMA, IMUs and Camera 880 million global smartphone users by 2013 (Morgan Stanley) Omnipresent RFinfrastructure in urban areas WLAN: 319 million chipsets sold in 2008, with 862 million installed base (Morgan Stanley) GSM/CDMA 5 von 24

AND New generation of mobile devices with multiple sensors WLAN, GSM/CDMA, IMUs and Camera 880 million global smartphone users by 2013 (Morgan Stanley) Omnipresent RFinfrastructure in urban areas WLAN: 319 million chipsets sold in 2008, with 862 million installed base (Morgan Stanley) GSM/CDMA allows Fine grained sensor profiling of any environment 5 von 24

AND New generation of mobile devices with multiple sensors WLAN, GSM/CDMA, IMUs and Camera 880 million global smartphone users by 2013 (Morgan Stanley) Omnipresent RFinfrastructure in urban areas WLAN: 319 million chipsets sold in 2008, with 862 million installed base (Morgan Stanley) GSM/CDMA allows Fine grained sensor profiling of any environment enables Indoor Localisation 5 von 24

Agenda 1. Location Matters! 2. Indoor Localisation Techniques 3. SmartSpace Framework (SSF) 4. Opportunities 6 von 24

Indoor Localisation Techniques Location Fingerprinting (LFPT) Signal Strength Measurements WLAN RSSI GSM RSS Inertial Measuring Units (IMUs) Accelerometer Gyroscope Electric compass Marker based localisation QR-Codes Display http://www.wikipedia.de/ http://www.phonewreck.com/ 7 von 24

LFPT WLAN Radio Propagation 8 von 24

LFPT WLAN Radio Propagation 9 von 24

LFPT - WLAN signal stability over time 10 von 24

LFPT - WLAN signal stability over time Awake 10 von 24

LFPT - WLAN signal stability over time Sleeping 10 von 24

LFPT = collect environmental sensor data GSM - 80 dbm, - 65 dbm - 45 dbm, - 57 dbm WLAN IMU Orientation Sensor Fusion Radio-Map 11 von 24

LFPT Sensor Fusion Synchronize sensors Measurement count Time Normalize data Variance Deviance Algorithms Fusionate data Kalman filters Particle filters Orientation Sensor Data GSM RSS WIFI RSS Location Fingerprint 12 von 24

LFPT How-to Testbed at University of Tübingen with 4 rooms + corridor: 1. Trainings-Phase Grid of Training-Points Record LFPTs Write to Radio-Map? 2. Realtime-Phase Record LFPT Alignment with Radio-Map Estimate position 13 von 24

LFPT How-to Testbed at University of Tübingen with 4 rooms + corridor: TP 1 TP 2 1. Trainings-Phase Grid of Training-Points Record LFPTs Write to Radio-Map TP 3 TP 4 2. Realtime-Phase Record LFPT Alignment with Radio-Map Estimate position TP 5 TP 7 TP 6 TP 8 13 von 24

LFPT How-to Testbed at University of Tübingen with 4 rooms + corridor: 1. Trainings-Phase Grid of Training-Points Record LFPTs Write to Radio-Map TP3 2. Realtime-Phase Record LFPT Alignment with Radio-Map Estimate position 13 von 24

IMU Localisation Dead Reckoning Current Position Estimate position based upon previous determined position Calculate Distance step length * total steps IMU Sensor Data Accelerometer, Orientation Step Detection Detect step patterns Filter Data Kalman Filter 14 von 24

IMU Localisation Step Detection 15 von 24

IMU Localisation Step Detection Swing Phase Stance Phase 15 von 24

IMU Localisation Step Detection Step Pattern 15 von 24

Agenda 1. Location Matters! 2. Indoor Localisation Techniques 3. SmartSpace Framework (SSF) 4. Opportunities 16 von 24

SSF - Architecture Custom Application Position API Motion Detector Core Framework Positioning Core Framework Persistance Sensor Synchronization Layer 17 von 24

SSF- Core Framework : Fixed Position : Motion LFPT Position GSM/WLAN/ X Marker Position + LFPT Training Inertial Position Tracking with IMUs 18 von 24

Sensor Data Condensation SSF - Sensor Synchronization Layer Core Framework Synchronization Strategy Sensor Fusion Sensor Data Processing Raw Sensor Data 19 von 24

Agenda 1. Location Matters! 2. Indoor Localisation Techniques 3. SmartSpace Framework (SSF) 4. Opportunities 20 von 24

New kinds of applications can be built Context aware Applications Localization of resources Automated service execution Implicit context recording, for later retrival Household Applications Room profiles Light applications Energy saving Shopping center Augmented (Reality) product search 21 von 24

SmartSpace Platform: Summary Extends the android platform by indoor localisation capabilities Uses WLAN, GSM/CDMA, IMUs and Camera Uses existing RF-infrastructure Sensor Fusion On-site positioning Autonomous Learning Trainings.apk Open Source Everybody can use it! 22 von 24

Thank you! Take everything you can get and cope with it! 23 von 24

Questions?? 24 von 24

Questions?? Stephan Linzner @onlythoughtwork linzner@ilimitado.de Daniel Kersting @drewenut kersting@ilimitado.de 24 von 24

Future of Localisation Mobile devices with multiple sensors Omnipresent RF- Infrastructure Localisation Cope with any available sensor data Seamless outdoor and indoor localisation