Challenges: Device-free Passive Localization for Wireless Environments Moustafa Youssef, Matthew Mah, Ashok Agrawala University of Maryland College Park MobiCom’07

Motivation Conventional location detection techs –Must carry “tracking” objects to localization –Examples) GPS, infrared, ultrasonic, radio frequency Device-free passive (DfP) localization? –RF signal is affected by changes in the environments –Off-the-shelf technology: e.g., WiFi Design goals –Detection –Tracking (mobility) –Identification (e.g., type, identify, size, shape, etc)

Feasibility Study Scenario: a person enters a room, makes four movements with 60s pause in between movements, and then exits.

Detection Moving average based detection –Compare the difference between short-term and long-term behavior –Discretize time and calculate the moving average –Control unit time size to capture short/long-term behavior –Event detected if the relative difference between two averages exceed a threshold Moving variance based detection –Instead of average, use variance for detection –Find the variance of RRSI samples during the entire measurement period –Event is detected if the sample deviation of a given time slot is beyond “r” times the deviation of a interference-free state

Results Moving variance to the raw data

Tracking Need to capture the relationship between signal strength and distance –Difficult due to multi-path, etc.. Radio map building –Person move around the area w/o carrying device –Measure RSSI values and build a RSSI map Passive Tracking –Given a map, determine the location of a mobile user –Baysian inference: Maximize P( dist | measured RSSI ) Map gives us P( measured RSSI | dist)

Challenges Identification function (DfP profiling) –Type, identity, mass, shape, etc. Handling multiple entities Automatic generation of a passive radio map Positioning of Access Points and Monitoring Points Other hardware and wireless techniques Dynamic changes in the environments –Interferences (microwaves, WiFi, etc) Privacy Robustness