mobisys 2011 - sigmobilemobisys 2011 the 9th international conference on mobile system,...

MOBISYS 2011MOBISYS 2011The 9th International Conference on Mobile System, Applications, and Services

Tracing a Missing Mobile Phone using Daily Observations

Hyojeong Shin*, Yohan Chon, Kwanghyo Park, Hojung Cha

Hyojeong Shin ([email protected]) Mobile Embedded System Lab. Yonsei UniversityHyojeong Shin ([email protected]) Mobile Embedded System Lab. Yonsei University

Motivation (1)Motivation (1)( )( )

A mobile device is a precious one.A mobile device is a precious one.

The device carries personal informationThe device carries personal information

Mobile Embedded System Lab. Yonsei UniversityMobile Embedded System Lab. Yonsei University

The device carries personal information.The device carries personal information.

Motivation (2)Motivation (2)( )( )• A device will be unexpectedly lost . So …

• Service Coverage is critical.– A service should cover Indoor space.

• GPS coverage : only 20 %

– A service should employ well-deployed infrastructure.Place coverage [*]

– A service should consider various target devices.

• Smartphones, feature phones, laptops, tablets at others

• Accuracy: Indoor search requires room-level accuracy.

• Also, the service should consider multiple-story building.p y g

• Energy: A mobile device has limited power.

• Searching Time: A lost device should be found in very short time


• Searching Time: A lost device should be found in very short time. [*] Y. Chon, et. al., "Autonomous Management of Personalized Location Provider for Mobile Services," IEEE T SMC-C 2011

Motivation (3)Motivation (3)( )( )• Our answer is employing Wi-Fi fingerprints. SSID RSSI

1 AP1 -60dBm

– Well deployed in indoor space.

– Well deployed in diverse mobile device.

2 AP2 -90dBm

3 AP3 -45dBm

4 AP4 -77dBm

– Wi-Fi fingerprints are unique and stable for space and time.

• Problems– Generally, an indoor floor plan is not available.

– Wi-Fi fingerprint does not carry location information.g y

• FindingMiMo– In our daily life, a device records Wi-Fi fingerprints in daily basis.In our daily life, a device records Wi Fi fingerprints in daily basis.

– When it is lost, a chaser application searches the missing device by tracing the series of Wi-Fi fingerprints.


g g p

Related WorkRelated Work• Find-A-Lost-Phone Services Limitations

– Apple Mobile Me & MS Window Lives

– Localization service (WPS) : Service Coverage

• Infrastructure-based positioning approach– Bluetooth-tag, RFID-tag, Ubisense (UWB), : Supervised Areag, g, ( ),

Indoor GPSp

: Installation Cost

• Mobile-based positioning approach– Place Learning : SensLoc, iLoc, SoundSense,

SurroundSense and Jigsaw: Training Phase is required.: Energy CostSurroundSense and Jigsaw

– Geometric localization(Radio): Radar, PlaceLab

– Geometric localization(Sensor): MEMS, Greefield

: Energy Cost


FindingMiMoFindingMiMo ArchitectureArchitecturegg

Missing-Mobile Part Chaser Part

Missing‐Mobile Chaser

g

Missing-Mobile ChaserI t ll d t d iDaily basis Wi-Fi logging

Background serviceLow energy consumption

Installed on an extra device.(old smartphone, laptop, tablets…)Device tracking application.Wi Fi INS GPS enabled

LifeMap SmartSLAM

Wi-Fi, INS, GPS enabled.

SmartSLAMUser Context MonitorPlace LearningMovement Tracking

Pedestrian TrackingConstructing a floor plan

Movement Tracking


*Y. Chon,et.al.,"LifeMap: A Smartphone-based Context Provider for Location-based Service", IEEE Pervasive Comp.2011**H. Shin, et. al. "SmartSLAM: Constructing an Indoor Floor Plan using Smartphone" Yonsei University, 2011

Ambient LogAmbient Loggg• Inertial sensor is not available. (Energy issue, device diversity)

outdoor indoor

• Log: GPS(Long./Lat.), APs, Status, Accuracy, POI label, timestamp

outdoor indoor

( ) A bi L (? ?)SSID RSSI

(x,y) Ambient Log (?,?)

The log does not reveal the exact

1 AP1 -60dBm

2 AP2 -90dBm

3 AP3 -45dBm

4 AP4 77dB


location of the missing device.4 AP4 -77dBm

FindingMiMoFindingMiMo ScenarioScenariogg

Cold Warm

progress

vicinityvicinity

• The ambient log does not contain the location information.– Analyzing the log, the chaser application displays “warm/cold” signs.y g g, pp p y g– The system signs out “warm” when a chaser is headed in the right direction

and “cold” when he is not, while he is searching.f W /C ld h f h ld


– cf. Warm/Cold game, a treasure hunt game for children[Thank you for a reviewer’s comment]

Design IssueDesign Issuegg

Missing-Mobile Part Chaser Partg

• Energy Limitation • No energy issue (rechargeable)

– In normal operation: Energy efficient logging

– In missing:

• Signal Processing– How to generate the tracking

i f i– In missing: NOT rechargeable

– Adaptive sensing schedule

information

– Wi-Fi similarity (warm/cold)

– Searching Progress• Storage Limitation

– Storage complexity

Searching Progress

• Searching a device– How to search to the device

– Massive APs are observed.

– Linear-scale growth is not feasible.

– Log reduction method

– Warm/cold game

– User Interface


– Log reduction method

MissingMissing--Mobile : Energy (1)Mobile : Energy (1)gg gy ( )gy ( )

• Adaptive Sensing Schedulingp g g– Moving-State monitoring (w/o sensor)

• When radio signal becomes stable: stationary state g y

• When radio signal rapidly changes: moving state

– GPS :GPS :

• Turns off GPS in stationary state

– Wi-Fi:Wi Fi:

• Increases sample interval in stationary state

[*]Ti C[Fi di MiM ]Ti C

GPS GSM Wi-Fi

Coverage 4 5% 99 6% 94 5%

[*]Time Coverage

move stay

Coverage 13% 87%

[FindingMiMo]Time Coverage


Coverage 4.5% 99.6% 94.5%

[*] LaMarca, A.a et al., “Place lab: Device positioning using radio beacons in the wild”, pervasive 2005

Coverage 13% 87%

MissingMissing--Mobile : Energy (2)Mobile : Energy (2)gg gy ( )gy ( )

– People spent approximately 13% of a day to move.

Average movement time vs. stationary time Average energy consumption

– Adaptive Sensing: 3.7kJ (vs. Continuous sensing : 41.1 kJ [*])

• reducing the battery’s lifetime by 14% in average.

• The result depends on individual usage patterns.


[*] D. H. Kim, et. al., SensLoc: Sensing Everyday Places and Paths using Less Energy, Sensys 2010.

MissingMissing--Mobile : Storage (1)Mobile : Storage (1)gg g ( )g ( )• Storage Complexity for Logging

h b l d ll d– The missing-mobile periodically scan GPS and Wi-Fi.

– The log tends to grow in linear scale.

– When a user visit known place, the log becomes useless.

• c.f. LifeMap provides user’s POI (Point of Interest) and GPS

– The redundant log is flushed.

– Log: GPS(Long./Lat.), Status, Accuracy, POI label, timestamp, APs

Ambient LogRedundant Log


MissingMissing--Mobile : Storage (2)Mobile : Storage (2)gg g ( )g ( )When a user visit a known place, the log is flushed

Mbytes)

4

5

the log is flushed.d Storage (M

1

2

3

Time (Hour)6 8 10 12 14 16 18 20 22 24

Used

0

• Storage ComplexityAll scan data 4 5 MB to 22 3 MB in a day (1 500 APs)– All scan data : 4.5 MB to 22.3 MB in a day (1,500 APs)

– The storage usage was around 5 MB. (empirical data)


Chaser : Signal Processing Chaser : Signal Processing g gg g

Missing-mobileMissing mobile

SSID RSSI

1 AP1 -60dBm

2 AP2 90dB

chaser

• Wi-Fi signal comparison• Si il it T i t C ffi i t

2 AP2 -90dBm

3 AP3 -45dBm

4 AP4 -77dBm

• Similarity: Tanimoto Coefficient

• Warm/cold: the similarity of the best-match observation• Progress: the index of the best match observation in the log


• Progress: the index of the best-match observation in the log

Chaser : Searching a DeviceChaser : Searching a DeviceggG

AE GDF F

lari

ty

A GD

simil

B

CC

D

time(sec)BA

E

• Chasing Strategy

C

• Chasing Strategy– Visit a unvisited place in vicinity

– Warm : Visit a next place


Wa : p

– Cold: Come back to the previous place / and visit another place.

Chaser GUIChaser GUI


ExperimentsExperimentspp• Environment

– Android Platform (ver. 2.2)

– HTC Hero, HTC Desire, Samsung Galaxy A/S, G l N O /S d P h Si iGoogle Nexus One/S, and Pantech Sirius

– in 4 buildings

• Missing-Mobile– Log size

– Energy consumption

• Chaser partp– Hide & Seek Game

– Shopping mall case


pp g

HideHide--andand--Seek GameSeek Game• Game design

– To remove the memory-effect

– Hider : hides a device

– Chaser group : searches the hidden device

• using the ambient log.

• Environment– 4 multi-story buildings (w/ 6 ~ 9 floors)y g

Game 1 2 3 4Building A B C DSquare (m2) 6505 5366 3482 3646q ( )Moving distance (hider, m) 116 183 105 117Number of floors 9 6 9 8Number of observed APs 70 206 139 122


Number of observed APs 70 206 139 122Number of participants 6 9 9 8

HideHide--andand--Seek Game : ResultSeek Game : Result20

Set1 20 meter

12

14

16

18

nce (m

)

Set 1

Set 2

Set 3

20 meter

ce (

m)

6

8

10

12

approach dista

Set 4

ch d

ista

nc

0

2

4

0 300 600 900 1200

a

4 meter

appr

oac

• Approaching distance

0 300 600 900 1200chasing time (sec)chasing time (sec)

Approaching distance– In 4 meters distance: the chaser can see the device.

– In 20 meters distance: the chaser can hear ring sound from the device.


g

• Failure : 3 / 32 trials

Shopping MallShopping Mallpp gpp g• Scenario:

T t j d h i f 3 h– Testers enjoyed shopping for 3 hours

– 6 possible missing points are extracted from the log. (took a break)

– The tester finds a missing point with the randomly selected logg p y g

• Environment– COEX convention center, Seoul, Korea

– One of the largest shopping mall in Korea ( 195 000 m2)

– Multi-storied building ( d d )(underground )


Shopping Mall : ResultShopping Mall : Resultpp gpp g( min: sec )

PlaceSP* (min:sec)(distance(m))

FindingMiMo (increment)

B 4 00 (360) 6 26 (2 26)Beverage 4 : 00 (360) 6 : 26 (2 : 26)

Shop 1 4 : 05 (368) 6 : 14 (2 : 09)

O hOn a path 4 : 23 (395) 6 : 13 (1 : 50)

Restaurant 6 : 01 (541) 8 : 20 (2 : 19)

Shop 2 5 : 48 (523) 13: 3 (7 : 15)

Rest Room 6 : 18 (567) 15: 33 (9 : 15)

• The chaser finished each search in 9 min. in average.

h h

* SP (shortest path): time to walk to the destination via the shortest path.


• The pure searching time is 4 : 30 in average.

FindingMiMoFindingMiMo FeaturesFeaturesgg• Non-intrusive operation

The ambient logger totally non intrusive background service– The ambient logger: totally non-intrusive background service– Energy consumption for daily-basis logging : Insurance fee

• Tracking a moving deviceTracking a moving device– Tracking a moving object is possible. – A missing-mobile continuously updates current ambient log.g y g– cf. Finding missing children

• Protecting privacy– FindingMiMo employs the minimum sensors.– Some sensors could invade user’s privacy.

• Microphone a wiretap Camera a candid camera• Microphone: a wiretap, Camera: a candid camera

• Limitations– Service Coverage: the solution employs Wi-Fi fingerprints.


Service Coverage: the solution employs Wi Fi fingerprints.– cf. rural environment, basement (no GPS, no Wi-Fi)

ConclusionConclusion• Contribution

– Finding a lost personal property

– Expanding the Service Coverage

• Indoor / Diverse device / No additional infrastructure

– (missing-mobile) Non-intrusive ambient loggers

– (chaser app.) Fast search, Room-level accuracy

Spinoza said, “Even if the end of the world were to come tomorrow,

I will plant an apple tree.”p ppI will say,

“Even if my phone were to go tomorrow, I will collect a W-Fi log ”


I will collect a W Fi log.

g{tÇ~lÉâ 4g{tÇ~lÉâ 4hjshin@cs yonsei ac [email protected]


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