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Digital Communications Lab - Team: LCD
32

Digital Communications Lab - Team: LCD - NIST

May 24, 2022

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Page 1: Digital Communications Lab - Team: LCD - NIST

Digital Communications Lab - Team: LCD

Page 2: Digital Communications Lab - Team: LCD - NIST

Our Project: ContactAR

Experiments Analysis SimulationData CT

Get a new Contact Tracing

Make other experiments

Page 3: Digital Communications Lab - Team: LCD - NIST

TC4TL: Our Roadmap

NIST Development setNIST Test set

MITRE Range Angle (Structured)

NIST Training set

Preprocessing

Exploration

Preprocessing

Model Training

Predictions and Evaluation

Preprocessing

Exploration

Preprocessing

Model Training

Predictions and Evaluation

Preprocessing

Exploration

Preprocessing

Model Training

Predictions and Evaluation

Page 4: Digital Communications Lab - Team: LCD - NIST

TC4TL DatasetsNIST Development set

NIST Training setNIST Test set

MITRE Range Angle (Structured)

0.9

1.2

1.5

2.4

2.7

3.0

3.6

4.5

1.8

Exact Distance [m]

0.9

1.2

1.5

2.4

2.7

3.0

3.6

4.5

1.8

Distance in a range [m] (fine_grain)

1.2

3.0

4.5

1.8

0.9

1.2

1.5

2.4

2.7

3.0

3.6

4.5

1.8

4.5

1.8

Distance in a range [m] (coarse_grain)

Page 5: Digital Communications Lab - Team: LCD - NIST

NIST Development setTX

TXDeviceTXPowerTXCarryTXPose

RX

RXDeviceRXCarryRXPose

RSSI

Accelerometer_xAccelerometer_yAccelerometer_z

Gyroscope_xGyroscope_yGyroscope_zAttitude_pitchAttitude_rollAttitude_yaw

Gravity_xGravity_yGravity_z

Magnetic_field_xMagnetic_field_yMagnetic_field_z

Altitude_x,Altitude_ywindow / look

(4s)step_size_in_sec

Page 6: Digital Communications Lab - Team: LCD - NIST

Data Preprocessing (Python-Pandas)

Imputation method Back-fill

a

Time

rssi values

sensor values

b a

Time

baaaa bbbb

Time feature 1(rssi)

feature 2(acceleration_x)

feature 3(acceleration_y)

feature 4(acceleration_z)

feature 5(gyroscope_x)

feature 6(...)

t1 rssi(t1)

t2 rssi(t2)

t3 rssi(t3)

t1 t2 t3 t1 t2 t3

1 Large Data file

Page 7: Digital Communications Lab - Team: LCD - NIST

Data Preprocessing (Python-Pandas)

Features added as columns

TXDeviceTXCarryTXPose

RXDeviceRXCarryRXPose

window_number attenuationTXPower coarse_grain distance_in_meters

One Hot Encoding

TXCarry_hand

TXCarry_pocket

TXCarry_unknown

1 0 0

0 1 0

0 0 1

TXCarry

One Hot Encoding

TXPower - 41 - RSSIRSSI > 0 were removed

step_size_in_sec = Inf were removed

File

Page 8: Digital Communications Lab - Team: LCD - NIST

Dataset Exploration

Page 9: Digital Communications Lab - Team: LCD - NIST

Dataset Exploration

Page 10: Digital Communications Lab - Team: LCD - NIST

Dataset Exploration

Page 11: Digital Communications Lab - Team: LCD - NIST

Dataset Exploration

Page 12: Digital Communications Lab - Team: LCD - NIST

Simple Linear Regression

each point is the mean attenuation value of 1 window

1 Feature: attenuation

Page 13: Digital Communications Lab - Team: LCD - NIST

Several Linear Regressions

hand_hand_sitting_sitting_Y

hand_hand_sitting_sitting_N

hand_hand_standing_sitting_Y

hand_hand_standing_sitting_N

………..

TXCarry_RXCarry_TXPose_RXPose_coarsegrain

split in scenarios

M1

M2

M3

M4

M...

1 Model / scenario(1 Feature: attenuation)

Page 14: Digital Communications Lab - Team: LCD - NIST

Score comparison

Several Linear Regressions

Simple Linear Regression

Page 15: Digital Communications Lab - Team: LCD - NIST

RandomForestRegressor

GridSearch + Cross Validation All features: mean values / window

Page 16: Digital Communications Lab - Team: LCD - NIST

RandomForestRegressor

Several Regressions

Score comparison

Page 17: Digital Communications Lab - Team: LCD - NIST

Feature Importance Analysisusing: RSSI & attenuation

using: RSSI & attenuation & Altitude_y

Page 18: Digital Communications Lab - Team: LCD - NIST

Place A -> Experiment 1 -> Distance 1Train Data

1

Test Data

1

Place B -> Experiment 2 -> Distance 2Train Data

2

Test Data

2

Place C -> Experiment 3 -> Distance 3

Train Data

3

Test Data

3

Altitude 1

Altitude 2

Altitude 3

Omid’s hypothesis

Page 19: Digital Communications Lab - Team: LCD - NIST

MITRE Range Angle (Structured)

https://mitll.github.io/PACT/datasets.html#datasets-submit

Page 20: Digital Communications Lab - Team: LCD - NIST

Data Preprocessing

Range 3Angle 0Angle 45Angle 90Angle 135Angle 180Angle 225Angle 270Angle 315

Range 4Angle 0Angle 45Angle 90Angle 135Angle 180Angle 225Angle 270Angle 315

Range 5Angle 0Angle 45Angle 90Angle 135Angle 180Angle 225Angle 270Angle 315

Range 6Angle 0Angle 45Angle 90Angle 135Angle 180Angle 225Angle 270Angle 315

Range 8Angle 0Angle 45Angle 90Angle 135Angle 180Angle 225Angle 270Angle 315

Range 10Angle 0Angle 45Angle 90Angle 135Angle 180Angle 225Angle 270Angle 315

Range 12Angle 0Angle 45Angle 90Angle 135Angle 180Angle 225Angle 270Angle 315

Range 15Angle 0Angle 45Angle 90Angle 135Angle 180Angle 225Angle 270Angle 315

0.9 m 4.5 m

coarse_grain exact distance

Page 21: Digital Communications Lab - Team: LCD - NIST

Data Exploration

RSSI attenuation

0.9144 m

1.2192 m

1.524 m

2.4384 m

2.7432 m

3.048 m

3.6576 m

4.572 m

1.8288 m

Distance

Page 22: Digital Communications Lab - Team: LCD - NIST

Data Exploration

(Varying Distancein each environment)

Page 23: Digital Communications Lab - Team: LCD - NIST

Data Exploration

(Varying Anglein each environment)

Page 24: Digital Communications Lab - Team: LCD - NIST

Simple Linear Regression

attenuation [dB]

Dis

tanc

e [m

]

Page 25: Digital Communications Lab - Team: LCD - NIST

NIST Training set:Multiple RandomForestRegressors

Page 26: Digital Communications Lab - Team: LCD - NIST

What we have left to do

● Try different aggregation techniques per file

● Try other Regression/Classification Algorithms

● Feature engineering with sensors data

Page 27: Digital Communications Lab - Team: LCD - NIST

Thank you !!!

Page 28: Digital Communications Lab - Team: LCD - NIST

BACKUP

Page 29: Digital Communications Lab - Team: LCD - NIST

15500 files

10 files

hand_hand_sitting_sitting

hand_hand_sitting_standing

hand_hand_standing_sitting

hand_hand_standing_standing

pocket_hand_sitting_standing

pocket_hand_standing_standing

pocket_pocket_sitting_sitting

pocket_pocket_sitting_standing

pocket_pocket_standing_sitting

pocket_pocket_standing_standing

TXCarry_RXCarry_TXPose_RXPose

Page 30: Digital Communications Lab - Team: LCD - NIST

10 files

hand_hand_sitting_sitting

hand_hand_sitting_standing

hand_hand_standing_sitting

hand_hand_standing_standing

pocket_hand_sitting_standing

pocket_hand_standing_standing

pocket_pocket_sitting_sitting

pocket_pocket_sitting_standing

pocket_pocket_standing_sitting

pocket_pocket_standing_standing

TXCarry_RXCarry_TXPose_RXPose

M1

M2

M3

M4

M5

M6

M7

M8

M9

M10

LinearRegression, RandomForestRegressor

Page 31: Digital Communications Lab - Team: LCD - NIST

M1

M2

M3

M4

M5

M6

M7

M8

M9

M10

8000 filesPredictions

Page 32: Digital Communications Lab - Team: LCD - NIST

Time

Atte

nuat

ion

15

14

16

11

12

13

17

percentil 50 / median

0.9144 m

1.2192 m

1.2 m

Distance fine_grain