crisp slides v2

CRISP: Coopera-on among Smartphones to Improve Indoor Posi-on Informa-on

Chen Qiu and Ma& W. Mutka Department of Computer Science and Engineering Michigan State University

IEEE WoWMoM 2015, Boston

Everyone has a smartphone

Outdoor Localiza-on Indoor Localiza-on

GPS

Ultrasound RFID

WSNs WiFi

What’s Next ?

Dead Reckoning Approach

g

S1S2

SnSn−1

a x

a! a

!

g

O X

Y

Z

ay

az

a!= (ax ,ay ,az − g) Sn

!"!− Sn−1! "!!

= 12an−1! "!!

t 2 + vn−1! "!!

tnUniformly Accelerated Mo-on

Drawback of Dead Reckoning

Dead Reckoning relies on the measurement accuracy of accelerometer

Accelerometer records the acceleration of the mobile device rather than a person’s body

Drawback of Dead Reckoning Sensor used for localization, UM6 Small orientation errors cause serious deviation 0.5 degree error of the orientation sensor -> 308 meters error can occur within 1 minute

h&ps://www.pololu.com

Challenge

For user of the smartphone, could we enhance the position accuracy for dead reckoning?

•  When a user encounters other users, by sharing locaDon and signal strength, all of their locaDon accuracies can be improved

(Location, Signal Strength)

Our Solu-on

LocalizaDon Error

Time

LocalizaDon Error

Time

(Location, Signal Strength) Alice Bob

Received Signal Strength Indicator

Euclidean Distance

Our Solu-on •  User’s iniDal posiDon is obtained from dead reckoning

•  How to use the Received Signal Strength (RSS) ?

Distance and RSSI Traditional formula is not accurate •  various obstructions •  multipath effect •  other factors

Measure the distance and RSSI •  Train for different devices •  Store in Hashmap on a smartphone

Distance (meter) RSSI (dBm) 1m -‐40dBm 2m -‐45dBm

Distance (meter) RSSI (dBm)

1m -‐42dBm 2m -‐46dBm

Device 1 <-> Device 2 Device i <-> Device j

… …

d = 10[(P0−Fm−Pr−10×n×log10 ( f )+30×n−32.44)/10×n]

•  Locate a user’s position by knowing other devices’ locations and RSSI values

•  After times of iterations, the deviation of each device will converge

•  Encounter more other smartphones, the accuracy will be more accurate

Triangula-on Model

A Novel Perspective:

RSSI= -48dBm

RSSI = -69dBm

RSSI = -75dBm

Dist(A,B)=4.5m

Dist(A,C)=5.5m

Dist(B,C)=2m

Mapping

Mapping

Mapping

(x , y )b b

(x , y )c c

(x , y )a a

(?, ?)

TriangleEquation

Carson

Bob

Alice

Triangula-on Model

Triangula-on Calibra-on

1m

2m

Carson(C)

Bob (B) Alice (A)

$¶%¶

&¶

2m2m

$¶¶

ABC: the ground truth$¶%¶&¶: triangle with initial error$¶¶: estimated position bytriangle approach

0 5 100

0.5

1

Time (seconds)

CD

F

ABC ErrorDead Reckoning

0 5 100

50

100

Time (seconds)Erro

r of D

ista

nce

(dec

imet

ers)

DeadReckoningAB ErrorBC ErrorAC ErrorABC Error

Preliminary Observa-ons

0 200 400 6000

1

2

Time (seconds)Erro

r of D

ista

nce

(m

eter

s)

Device ADevice BDevice C

0 100 200 300 400 5000

1

2

3

Time (Seconds)Er

ror o

f D

ista

nce

(met

ers)

•  Within time increasing, the deviation is reduced effectively

Geometry Extension •  How about more than three users ? •  How about Quadrilateral, Pentagon, Hexagon … ? •  Decompose to triangle

Carson

Bob Alice(x , y )b b

(x ,y )c c

(x ,y )a a

David(x , y )d d

Carson

BobAlice

Bob Alice

David

Carson

Alice

David

Feature of different signals •  Bluetooth sensiDve to interference, also sensiDve to the distance low energy, supported by common smartphones, sampling frequency is not enough (>10s)

•  WiFi supported by common smartphones sensiDve to interference, not sensiDve to the distance sampling frequency is not enough (>4s) •  Zigbee sensiDve to interference, also sensiDve to the distance sampling frequency is enough not supported by common smartphones

Combine different signals

WiFi + Bluetooth

Cloud�Server

Zigbee Device ID Time Stamp RSSI

Bluetooth RSSI-Distance Mapping

Distance

Device ID Time Stamp RSSI

Zigbee RSSI-Distance Mapping

Distance

Device ID Time Stamp RSSI

Bluetooth

Zigbee

WiFi Filter

Synchronous

Data Sample Format

WiFi Direct Filter

0 50 100 150 200−90

−80

−70

−60

−50

−40

−30

−20

Time (seconds)

RSS

I (dB

m)

WiFiBluetoothBluetooth (Filtered)ZigbeeZigbee (Filtered)

NP NP

WiFi Direct enables devices to connect with each other without requiring a wireless access point

Replace the abnormal RSSI in the Noise Period

Extra Benefit: Step Coun-ng

•  Electronic pedometer on the smartphones

•  Measuring steps by the accelerometer

Extra Benefit: Step Coun-ng •  Accelerometer is not reliable for pedometers

•  Even if a user does not move, the received

acceleration can be changed sharply

Extra Benefit: Step Coun-ng ! Users obtained the location continuously in different periods

!  In each time period, we assume people walk straight

! Count steps for a user:

number of steps = ( moving distance / step length )

! Add the number of steps in each time period, the user can determine the number of steps they walked in total

100 200 300 400 5000

20

40

60

80

100

Time (seconds)

Erro

r Num

ber

of S

teps

ACCUPEDO

Noom Walk

CRISP

System Evalua-on

Experiment Setup:

Data Collection in a Room Data Collection in a Hallway

!  Train and collect data in Engineering Building of MSU ! More than 100 rooms and hallways, 6 volunteers ! Samsung S5, S3, Google Nexus, etc ! Android 4.4

System Evalua-on

0 10 20 30 40 50

0

1

2

3

Time (per 20 seconds)

Erro

r of D

ista

nce

(

met

ers)

Triangle Approach

Combination Approach


5 10 15 20 25 30 35 40 450

2

4

6

8

10

Time (minutes)

Erro

r of D

ista

nce

(met

ers)

Dead ReckoningTriangle AppCombine App

Room measurement one time Room measurement 200 times

5 10 15 20 25 30 35 40 450

2

4

6

8

Time (minutes)

Erro

r of D

ista

nce

(met

ers)

Dead ReckoningTriangle AppCombine App

Hallway measurement one time

0 10 20 30 40 50

0

1

2

3


Erro

r of D

ista

nce

(m

eter

s)


Triangle Approach


Hallway measurement 200 times

System Evalua-on

Measurement in a complex environment

Dead Reckoning Trace Combination Approach Trace

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��

100 200 300 400 5000

2

4

6

8

10

Time (seconds)

Erro

r of D

ista

nce

(m

eter

s)



Triangle Approach

10 20 30 40 500

1

2

3

4

Time (Minutes)

Erro

r of D

ista

nce

(met

ers)

BluetoothBluetoth+ZigbeeBluetooth+Zigbee+WiFi

0 10 20 30 40 50

0

0.5

1


Erro

r of D

ista

nce

(met

ers)

Bluetooth + Zigbee + WiFi

Bluetooth + Zigbee

Bluetooth

System Evalua-on

Comparison of different types of signals

0 100 200 300 400 500

0

0.5

1

1.5

Time (seconds)

Erro

r of D

ista

nce

(met

ers)

2+1 devices

3+1 devices

0 10 20 30 40 50−1

0

1

2

3

4


Erro

r of D

ista

nce

(met

ers)

2 assisted customers

no assisted customer

3−4 assisted customers

Comparison of the number of smartphones’ users

Contribu-on Highlight

!  Interact with other scanned smartphones to improve a user’s own localizaDon accuracy

!  Improve the accuracy of the pedometer on a smartphone by RSSI rather than acceleraDon

!  Combine the RSSI from Zigbee, WiFi and Bluetooth, and design a WiFi filter to reduce the noise

Contact InformaDon： [email protected] eLANS Lab, CSE Dept. MSU

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