finding mimo : tracing a missing mobile phone using daily observations

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FINDING MIMO: TRACING A MISSING MOBILE PHONE USING DAILY OBSERVATIONS Hyojeong Shin, Yohan Chon, Kwanghyo Park and Hojung Cha MobiSys 2011 - Sowhat 2012.03.19

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Finding MiMo : Tracing a Missing Mobile Phone using Daily Observations. Hyojeong Shin, Yohan Chon, Kwanghyo Park and Hojung Cha MobiSys 2011 - Sowhat 2012.03.19. Outline. Introduction System Design Evaluation Discussion Conclusion. Outline. Introduction System Design - PowerPoint PPT Presentation

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Page 1: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

FINDING MIMO: TRACING A MISSING MOBILE PHONE USING DAILY OBSERVATIONS

Hyojeong Shin, Yohan Chon, Kwanghyo Park and Hojung ChaMobiSys 2011

- Sowhat 2012.03.19

Page 2: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

Page 3: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

Page 4: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

MOTIVATION Missing handheld device problem

Existing solution MobileMe, provided by Apple Inc. and Skyhook GPS, cell tower ID, WiFi fingerprints Drawbacks - Inaccurate location estimations in indoor

GPS signal not reachable Pre-learned database for radio fingerprints not available

Page 5: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

CHALLENGES1. Efficient - limited battery duration

2. Indoor environment challenge GPS, floor plan, pre-learned radio map, non-

standard hardware not generally available

3. Room-level accuracy

4. Not necessary with additional hardware functionality or infrastructure

Page 6: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

Page 7: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

IDEA OF FINDINGMIMO

~ Warn / Cold Game ~

Sim() = Tanimoto coefficient function=

Page 8: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

PLACE-MATCHING PROBLEM Input

Initial known position Logged observations Live observations

Output Moving path of missing mobile Moving path of the chaser

Page 9: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

SYSTEM ARCHITECTURE

Missing MobileLifeMap

Missing mobile app.

ChaserSmartSLAM

Chaser app.

Page 10: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

LIFEMAP Functionality

Monitor user’s physical location with ambient features Construct nodes (places) & edges (paths)

Sensing GPS, GSM, WiFi Activity-based sensor selection (move / stationary) Detection of movement – Tanimoto Coefficient >

threshold Known place

Stationary state continuously maintained Role

Provide information of movement and known places

Missing

Mobile

LifeMap

Missing mobile app.

ChaserSmartSLAM

Chaser app.

Page 11: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

MISSINGMOBILE:DAILY AMBIENT LOGGER Role

Record ambient radio logs on the path, from last known place to current unknown place

Functionality Log WiFi vectors , LifeMap detect movement & no GPS signal

Sleep state , otherwise

Minimize stored information Collection period < 1 Day Reset when 1. revisit a known place 2. GPS signal available

Missing

Mobile

LifeMap

Missing mobile app.

ChaserSmartSLAM

Chaser app.

Page 12: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

SMARTSLAM:INDOOR PEDESTRIAN TRACKING Role

Provide indoor floor plan & location of the user

Functionality – floor plan construction Path

Accelermeter step count Digital compass heading direction

Location Use WiFi observation to identify locations Adjust path while revisting identified locations

Missing

Mobile

LifeMap

Missing mobile app.

ChaserSmartSLAM

Chaser app.

Page 13: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

CHASER: DEVICE TRACKINGCHASING INFORMATION Circumstantial evidence

Approximate missing time & previous known place Indoor pedestrian tracking

Display map & location of the user Log similarity

Similarity of current and logged observations

Trace similarity –

Target similarity –

Chasing progress -

Missing

Mobile

LifeMap

Missing mobile app.

ChaserSmartSLAM

Chaser app.

Page 14: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

CHASER: DEVICE TRACKINGCHASING INFORMATION

Missing

Mobile

LifeMap

Missing mobile app.

ChaserSmartSLAM

Chaser app.

If no specific location (GPS) in log data

Visit all possible entrances of last place

to find the one with largest similarity

Indoor Chasing

Page 15: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

Page 16: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

MISSING MOBILE Energy consumption & space complexity Setting

Similarity threshold = 0.7 5 students collect 2 weeks

Energy consumption

Rate Activate Interval

GPS ? 30sec 2min

WiFimove 5sec - -

stationary 10sec 30sec 2min

Page 17: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

MISSING MOBILE Space complexity

AP – 367 ~ 1573 Record – 50160~248700 4.5 ~ 22.3MB Reduction: ABCBD ABD

Page 18: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

CHASING A HIDDEN DEVICE

Page 19: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

CHASING A HIDDEN DEVICE

Page 20: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

VERTICAL LOCALIZATION

Page 21: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

HIDE-AND-SEEK GAME Goal: check if chaser could chase with only

the information from chaser app. Setting

4 games at 4 different buildings 36 people 1 participant hide, chaser group chase

Page 22: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

CASE STUDY: SHOPPING MALL Real environment & case Setting

195000 m2 shopping mall 3 hours log Extract 6 possible missing place generate logs User chase at the next day

Page 23: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

Page 24: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

DISCUSSION User guide

Move slow while chasing Places with similar radio signal may be on different

floor

Erroneous data GPS may be read via window Open space

Page 25: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

Page 26: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

CONCLUSION FindingMiMo with ambient observations to

help to trace missing mobile device

Not clear descriptions for detail settings

Page 27: Finding  MiMo :  Tracing a Missing Mobile Phone using Daily Observations

THANKS FOR LISTENING ~