what are people's responses to thermal discomfort? sensing
TRANSCRIPT
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.
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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
19
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’
20
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
25
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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