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Survey and Implementation of Smart Space Scenarios Philipp H artinger Advisors: Marc-Oliver Pahl Benjamin Hof Chair for Network Architectures and Services Department for Computer Science Technische Universit at M unchen September

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SLIDE 1

Survey and Implementation of Smart Space Scenarios

Philipp H¨ artinger

Advisors: Marc-Oliver Pahl Benjamin Hof Chair for Network Architectures and Services Department for Computer Science Technische Universit¨ at M¨ unchen

September 29, 2014

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 1

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SLIDE 2

Outline

1

Motivation

2

Survey of Smart Space Scenarios Sources & Selection Criteria Results

3

Implementation of Occupancy Detection System Design Evaluation & Results

4

Sources

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 2

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SLIDE 3

Motivation

What are we talking about? Pervasive Computing

Mark Weiser [Wei91] computing in everything

Smart Space

physical space with sensors and actuators gather state of user and environment = context reason about context and act appropriately

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 3

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SLIDE 4

Table of Contents

1

Motivation

2

Survey of Smart Space Scenarios Sources & Selection Criteria Results

3

Implementation of Occupancy Detection System Design Evaluation & Results

4

Sources

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 4

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SLIDE 5

Survey

Goal

  • verview of implemented smart space scenarios

used hardware (sensors, actuators) used software (middleware) Sources HUC 1999–2000 UbiComp 2001–2013 Pervasive 2002–2012 Selection Criteria sensors and actuators in a well-defined physical space implementation in reality or simulation

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 5

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SLIDE 6

Survey Results

Category Project Title microphone motion camera contact switch RFID light location Other Sensors Middleware AAL, Health Care Monitoring Behavior in Home [Nou+00]

  • acceleration, tilt, vibration

Activity Recognition in Home [TIL04]

  • Health-Status Monitoring

[BBA05]

  • STAR

[WA05]

  • pressure, break-beam

Diet-Aware Dining Table [Cha+06]

  • weight

CAMP [Lun+07]

  • Height Sensors for Biometric Identification

[SSW10] distance Convenience AwareMirror [FKN05]

  • temperature
  • Audio Location

[SD05]

  • ReflectiveSigns

[M¨ ul+09]

  • Kitchen Activity Recognition

[LRF12]

  • Detecting Cooking State

[Hir+13] gas Break-Time Barometer [Kir+13]

  • electrical current, humidity

Find My Stuff (FiMS) [Nic+13]

  • Energy, Lighting

ViridiScope [Kim+09]

  • GasSense

[Coh+10]

  • SunCast

[LW12]

  • AgentSwitch

[Fis+13] electrical current Intelligent Luminaires [M¨ ak+13]

  • HVAC

Management of Energy & Thermal Comfort [BK01] CO2, mixed gas GPS-Thermostat [GIL09]

  • temperature

Smart Thermostat [Lu+10]

  • PreHeat

[Sco+11]

  • temperature

TherML [Koe+13]

  • Office

Smart Classroom [Xie+01]

  • EasyMeeting

[Che+04]

  • bluetooth sensing agent
  • Detect User Activity and Availability

[M¨ uh+04]

  • Detection of Interaction Groups

[BMR05]

  • Virtual Secretary

[DS08]

  • Weightless Walls

[Tak10]

  • ReticularSpaces

[Bar+12]

  • Philipp H¨

artinger: Survey and Implementation of Smart Space Scenarios 6

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SLIDE 7

Survey Results

Category Project Title microphone motion camera contact switch RFID light location Other Sensors Middleware AAL, Health Care Monitoring Behavior in Home [Nou+00]

  • acceleration, tilt, vibration

Activity Recognition in Home [TIL04]

  • Health-Status Monitoring

[BBA05]

  • STAR

[WA05]

  • pressure, break-beam

Diet-Aware Dining Table [Cha+06]

  • weight

CAMP [Lun+07]

  • Height Sensors for Biometric Identification

[SSW10] distance Convenience AwareMirror [FKN05]

  • temperature
  • Audio Location

[SD05]

  • ReflectiveSigns

[M¨ ul+09]

  • Kitchen Activity Recognition

[LRF12]

  • Detecting Cooking State

[Hir+13] gas Break-Time Barometer [Kir+13]

  • electrical current, humidity

Find My Stuff (FiMS) [Nic+13]

  • Energy, Lighting

ViridiScope [Kim+09]

  • GasSense

[Coh+10]

  • SunCast

[LW12]

  • AgentSwitch

[Fis+13] electrical current Intelligent Luminaires [M¨ ak+13]

  • HVAC

Management of Energy & Thermal Comfort [BK01] CO2, mixed gas GPS-Thermostat [GIL09]

  • temperature

Smart Thermostat [Lu+10]

  • PreHeat

[Sco+11]

  • temperature

TherML [Koe+13]

  • Office

Smart Classroom [Xie+01]

  • EasyMeeting

[Che+04]

  • bluetooth sensing agent
  • Detect User Activity and Availability

[M¨ uh+04]

  • Detection of Interaction Groups

[BMR05]

  • Virtual Secretary

[DS08]

  • Weightless Walls

[Tak10]

  • ReticularSpaces

[Bar+12]

  • Philipp H¨

artinger: Survey and Implementation of Smart Space Scenarios 6

Occupancy Detection

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SLIDE 8

Table of Contents

1

Motivation

2

Survey of Smart Space Scenarios Sources & Selection Criteria Results

3

Implementation of Occupancy Detection System Design Evaluation & Results

4

Sources

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 7

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SLIDE 9

Implementation Overview

Hardware and Software Design

DS2OS

SensorGateway Service

  • pulls

sensor readings

  • ver HTTP

OccupancyDetection Service

  • analyzes

sensor readings to infer occupancy RoomManager Service

  • manages

associations RoomID↔Galileo

Intel Galileo

motion (PIR) sensor brightness sensor temperature sensor Node.js Webserver TCP/IP Network

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 8

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SLIDE 10

Implementation: Hardware

Intel Galileo Ethernet RESTful Web Interface (Node.js) Sensors

Motion Temperature Brightness

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 9

Figure created with

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SLIDE 11

Implementation: Software (DS2OS)

DS2OS Services GalileoGatewayService OccupancyDetectionService

timer threshold parameter T if no motion for T seconds ⇒ unoccupied

RoomManagerService

facilitates access to sensors and occupancy state of a room get roomManager/office/occupancy/isOccupied/value

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 10

DS2OS

SensorGateway Service

  • pulls

sensor readings

  • ver HTTP

OccupancyDetection Service

  • analyzes

sensor readings to infer occupancy RoomManager Service

  • manages

associations RoomID↔Galileo

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SLIDE 12

Implementation: Software (UI)

Web User Interface HTML & JavaScript queries occupancy states periodically (via RoomManager) colors rooms on map accordingly

green = unoccupied red = occupied

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 11

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SLIDE 13

Evaluation

Experiment 1: controlled experiment in 1 room over 4 hours Expected Results: unoccupied or high activity ⇒ high detection rate

  • ccupied, but low activity ⇒ lower detection rate

detection rate depends on distance Experiment 2: measurements in 3 rooms over 5 days Expected Results: typical usage patterns of the rooms become inferable Middleware Usage fast and easy implementation due to DS2OS middleware

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 12

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SLIDE 14

Experiment 1: Setup

4 hours 0–3 persons 3 Galileo boards hand logged data different situations:

empty low motion high motion

desk A desk B 2 1 3 2.5 m 2 m 0.5 m 2 . 5 m

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 13

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SLIDE 15

Experiment 1: Results

1 Motion sensor data Galileo1 1 OccupancyDetectionService with T=60s −1 1 Difference between service output and hand logged data 10 46 80 92 109 133 150 181 195 218 240 1 Hand logged occupancy time in minutes low motion high motion

Galileo 1 (middle)

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 14

desk A desk B 2 1 3

Figure created with Matlab

false positive false negative

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SLIDE 16

Experiment 1: Results

1 Motion sensor data Galileo2 1 OccupancyDetectionService with T=60s −1 1 Difference between service output and hand logged data 10 46 80 92 109 133 150 181 195 218 240 1 Hand logged occupancy time in minutes low motion high motion

Galileo 2 (desk)

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 15

desk A desk B 2 1 3

Figure created with Matlab

false positive false negative

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SLIDE 17

Experiment 1: Results

1 Motion sensor data Galileo3 1 OccupancyDetectionService with T=60s −1 1 Difference between service output and hand logged data 10 46 80 92 109 133 150 181 195 218 240 1 Hand logged occupancy time in minutes low motion high motion

Galileo 3 (door)

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 16

desk A desk B 2 1 3

Figure created with Matlab

false positive false negative

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SLIDE 18

Optimization of Threshold Parameter

gaps in low motion phases need to be filled in this experiment: low overall error for T = 300 seconds

100 200 300 400 500 600 700 800 10 20 30 40 50 60 70

OccupancyDetectionService threshold T in seconds error rate in %

total error false positive false negative

sensor near desk A (2)

100 200 300 400 500 600 700 800 10 20 30 40 50 60 70

OccupancyDetectionService threshold T in seconds error rate in %

total error false positive false negative

sensor near door (3)

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 17

Figures created with Matlab

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SLIDE 19

Experiment 2: Setup

measurements over 5 weekdays 3 rooms:

  • ffice

laboratory meeting room

1 2 3

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 18

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SLIDE 20

Experiment 2: Results Office

15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 22 23 24 25 26 27 28 29 30 31 32 temperature in °C

Temperature sensor data

Monday Tuesday Wednesday Thursday Friday 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 2 4 6 8 10 12 14 16 18 sensor values

Brightness sensor data

15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 1

Motion sensor data

15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 1 Time of day [hours]

OccupancyDetectionService with T=300s

1

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 19

Figure created with Matlab

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SLIDE 21

Experiment 2: Results Laboratory

15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 20.5 21 21.5 22 22.5 23 23.5 24 24.5 25 25.5 temperature in °C

Temperature sensor data

Monday Tuesday Wednesday Thursday Friday 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 0.5 1 1.5 2 2.5 sensor values

Brightness sensor data

15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 1

Motion sensor data

15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 1 Time of day [hours]

OccupancyDetectionService with T=300s

2

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 20

Figure created with Matlab

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SLIDE 22

Experiment 2: Results Meeting Room

15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 21.5 22 22.5 23 23.5 24 24.5 25 25.5 26 temperature in °C

Temperature sensor data

Monday Tuesday Wednesday Thursday Friday 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 0.5 1 1.5 2 2.5 3 sensor values

Brightness sensor data

15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 1

Motion sensor data

15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 1 Time of day [hours]

OccupancyDetectionService with T=300s

3

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 21

Figure created with Matlab

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SLIDE 23

Effect of Timer Threshold

13:30 13:45 14:00 14:15 14:30 14:45 15:00 15:15 15:30 15:45 16:00 16:15 16:30 16:45 17:00 17:15 17:30 17:45 18:00 1 Motion sensor data 13:30 13:45 14:00 14:15 14:30 14:45 15:00 15:15 15:30 15:45 16:00 16:15 16:30 16:45 17:00 17:15 17:30 17:45 18:00 1 Time of day [hours] OccupancyDetectionService with T=300s

The timer threshold T closes the gaps where no motion is detected Causes false positive detection of length T at the end of each occupancy block

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 22

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SLIDE 24

Utility of Middleware

Low Programming Effort

Java service-template GalileoGatewayService: 144 LoC (86 self-written) OccupancyDetectionService: 170 LoC (97) RoomManagerService: 204 LoC (108)

Facilitated Inter-Service Communication

publish-subscribe mechanism i.e. OccupancyDetectionService subscribes to the sensor nodes of GalileoGatewayService

Extensibility

additional Galileo board: new instance of GatewayService services can be used as input for advanced services

Persistence

data is stored in Virtual State Layer (VSL)

Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 23

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Philipp H¨ artinger: Survey and Implementation of Smart Space Scenarios 24