What Are People's Responses to Thermal Discomfort?!Sensing Clothing and Activity Levels Using SenseCam

Behavior, Energy and Climate Change Conference November 2011

Stephanie Gauthier

Supervisor : Dr. David Shipworth

Supervisor: Prof. Robert Lowe

a | Introduction | Framework

2

a | Introduction | Context

Total Energy Consumption by Final User 2008

Total Domestic Energy Consumption by End Use 2007

16% of total

ENERGY

consumption in the

UK

is used for

SPACE HEATING

3

a | Introduction | Context

Climate Change Act, 2008 (c.27)

Programs of Interventions

•  improve building fabric •  upgrade services •  integrate renewable

energy technologies

AIM reduce energy consumption in

dwellings

How dwelling thermal comfort systems are conceptualised and understood by their users / occupants ?

4

Energy continues to rise

‘re-bound effect’

a | Introduction | Thermal Comfort

What is thermal comfort? ‘that condition of mind which expresses satisfaction with the thermal environment’

Data source: Schematic diagram of the passive system- D. Fiala, K.J. Lomas, M. Stohrer (1999) A computer model of human thermoregulation for a wide range of environmental conditions: the passive system. J Appl Physiol Vol. 87, Issue 5, 1957-1972.

5

Involuntary physiological mechanisms: thermoregulation

Basis of the heat balance equation Fanger (1970)

Voluntary behaviour or action response Brager (1998)

Habituated behaviour Glaser (1966)

a | Introduction | Summary

Current models:

[+] Identify issues within the thermal environment [+] Predict and assess thermal sensation

[-] How occupants form their responses

Occupants Dwellings

thermal comfort system

THERMAL DISCOMFORT RESPONSES

b | Field Study | Methods selection

Aim: Test methods to gather and analyse information

What: Mapping occupants thermal discomfort responses

How: Mixed methods approach

Building Survey Occupant Survey

Observation Checklist

-  Building location -  Building age -  Building fabric

-  Heating system -  Hot water system

Monitoring

- Temperature - Relative humidity

- Illuminance

Questionnaire

- Socio-demographic

- Thermal environment

Diary

-  User interactions

-  Temperature -  Illuminance

Focus Group

-  Responses -  Thresholds -  Influencing

factors

recorded information reported information

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b | Field Study | Method: Diary - SenseCam

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b | Field Study | Method: Diary - SenseCam

•  Manually •  Automatically: •  Timer (1min)

•  Sensors: •  Temperature sensor; •  Light level sensor; •  Passive infrared detector; •  Multiple-axis accelerometer; •  Magnetometer.

Output 1: Log of 4 main variables

Output 2: Images

1.  ACC Accelerometer: x (R/L), y (Up/Down), z (F/B) 2.  MAG Magnetometer: x, y, z 3.  CLR Colour light sensor: value for white light 4.  PIR Passive infrared detector: 1 triggered, 0 not 5.  TMP Temperature (°C) Others RTC (real-time clock), BAT (battery),

CAM (image capture), FIL (filename), VER (version of firmware), SYS (system info.)

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b | Field Study | Method: Diary - SenseCam

PARTICIPANT 04 DAY 01

b | Field Study | Results

Heat Balance Equation

Activity Level (met)

Clothing (clo)

Ambient Air

Temp. (°C)

Mean Radiant Temp.

(°C)

Relative Air

Velocity (m.s-1)

Relative Humidity

(%)

VBA - BS EN ISO 7730: 2005

Predicted Responses

Estimation of PMV

CIBSE guide A 1.3.1.2 Monitoring Diary (BS EN ISO 7730: 2005)

Diary

Recorded Responses

11

Questionnaire Interview

Focus Group

Reported Responses

b | Field Study | Results

Heat Balance Equation

Activity Level (met)

Clothing (clo)

Ambient Air

Temp. (°C)

Mean Radiant Temp.

(°C)

Relative Air

Velocity (m.s-1)

Relative Humidity

(%)

VBA - BS EN ISO 7730: 2005

Predicted Responses

Estimation of PMV

CIBSE guide A 1.3.1.2 Monitoring Diary (BS EN ISO 7730: 2005)

12

b | Field Study | Results! Responses to thermal discomfort

13

Thermal resistance of clothing

(clo)

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EN ISO 7730:2005

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EN ISO 7730: 2005 Table C.1 Thermal insulation for typical combinations of garments

SenseCam Diary Images

b | Field Study | Results! Responses to thermal discomfort

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SenseCam accelerometer sensor readings to

determine cut-in / cut-off points in time

Activity Level (met)

EN ISO 7730: 2005 Table B.1

Metabolic rates

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SenseCam Diary Images

•  83% of monitored time outside of the comfort zone set by ANSI/ASHRAE standard 55-2004, table 5.2.1.2 acceptable thermal environment for general comfort

•  Most participant should be feeling ‘slightly cool’ (-1), ‘cool’ (2) and ‘cold’ (-3)

Up To 3

b | Field Study | Results! PMV and PPD models (through recording period)

15

b | Field Study | Results

Heat Balance Equation

Activity Level (met)

Clothing (clo)

Ambient Air

Temp. (°C)

Mean Radiant Temp.

(°C)

Relative Air

Velocity (m.s-1)

Relative Humidity

(%)

VBA - BS EN ISO 7730: 2005

Predicted Responses

Estimation of PMV

CIBSE guide A 1.3.1.2 Monitoring Diary (BS EN ISO 7730: 2005)

Diary

Recorded Responses

16

Questionnaire Interview

Focus Group

Reported Responses

b | Field Study | Results

CIBSE guide A 1.3.1.2 Monitoring Diary (BS EN ISO 7730: 2005)

Diary

Recorded Responses

17

b | Field Study | Results! Responses to thermal discomfort

3 days - SenseCam recording - 1500 to 6300 images

Events Segmentation

Process

Event A – TRVs Event C – Eating Event B – Putting a jumper on

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Event Segmentation Approach 1 (manual) ‘1-2-3 analysis’

•  Stage 1: setting out the criteria where differences may indicates events

•  Stage 2: comparison of adjacent images

•  Stage 3: comparison every 2nd images New Event

Not an Event

b | Field Study | Results! Responses to thermal discomfort

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SenseCam Images

125 Events

Segmentation

16 Events

Comparison

LR, standing-up 17.60%

Kitchen, standing-up 16.80%

LR, seated, laptop 11.20%

LR, phone 7.20%

Bathroom, standing-up 7.20%

LR, seated, drink 7.20%

Black 7.20%

LR, seated, TV 6.40%

LR, seated, eating 5.60%

LR, seated on sofa, questionnaire 4.80%

Bedroom, standing-up 4.00%

Hallway, standing-up 1.60%

LR, standing-up, TV 0.80%

Hallway, standing-up 0.80%

LR, seated, reading 0.80%

LR, seated, table 0.80%

b | Field Study | Results! Responses to thermal discomfort

Event Segmentation Approach 1 (manual) ‘1-2-3 analysis’

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Event Segmentation Approach 2 (automatic)

SenseCam Images

40 Events

Detected

Segmentation

22 Events

Represented

Segmentation

b | Field Study | Results! Responses to thermal discomfort

STAGE 1

STAGE 2

STAGE 3

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Event Segmentation Approach 2 (automatic)

software developed by Dublin City University (DCU)

•  Stage 1: MPEG-7 features - Scalable Colour - Colour Structure - Colour Moments - Edge Histogram

•  Stage 2: Metadata information - Light level

- Temperature - Accelerometer

•  Stage 3: Group Image into classes: static person, moving person, static camera

b | Field Study | Results! Responses to thermal discomfort

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SenseCam Images

40 Events

Detected

Segmentation

22 Events

Represented

Segmentation

[?] image clustering

[?] parameter threshold level,

events’ boundaries

b | Field Study | Results! Responses to thermal discomfort

Event Segmentation Approach 2 (automatic)

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b | Field Study | Responses and PMV model

Heat Balance Equation

Activity Level (met)

Clothing (clo)

Ambient Air

Temp. (°C)

Mean Radiant Temp.

(°C)

Relative Air

Velocity (m.s-1)

Relative Humidity

(%)

VBA - BS EN ISO 7730: 2005

CIBSE guide A 1.3.1.2 Monitoring Diary (BS EN ISO 7730: 2005)

SenseCam Image

24

Predicted Responses

Estimation of PMV

Recorded Responses

10/11/2010 09/11/2010 08/11/2010 07/11/2010

Change activity Change location Change activity & location

b | Field Study | Responses and PMV model

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d | Conclusion | Future research

To develop an automatic segmentation method

Possible method: images // metadata

•  When Time stamping •  Where Accelerometer and Magnetometer sensors •  Clo Temperature sensor and Infra-Red Camera •  Activity Accelerometer sensor and Heart Rate Monitor

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Any questions ? Email: s.gauthier@ucl.ac.uk !

!

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