What Are People's Responses to Thermal Discomfort? Sensing

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)

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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

22

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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