Figure 1
Overview of the eCOMBINE framework.
Note: A mixed experimental approach is used for collecting objective and subjective data. Its research capacity depends on the combination of various data sources.
Figure 2
Surveying schedule and frequency for long- and short-term surveys within the eCOMBINE framework.
Note: LT-A = background information of global comfort; LT-B = seasonal perception of global comfort; PIT-A = perception of global discomfort in the workplace; PIT-B = motivations behind window and blinds control behaviour; and PIT-C = motivations behind light-switching behaviour.
Table 1
Overview of the characteristics of two open-plan offices.
| OFFICE ID | SURFACE AREA (m2) | ORIENTATION | WALL-TO-WINDOW RATIO | U-VALUE OF WALLS (W/m2K) | HEATING/COOLING SYSTEM | VENTILATION SYSTEM | AUTOMATIC ELEMENTS | OPERABLE ELEMENTS | PARTICIPATING OCCUPANTS |
|---|---|---|---|---|---|---|---|---|---|
| Office A | 259 | North, east | 0.42 | < 0.18 | Hydraulic radiant ceiling system | Mechanical | Desk lights, ceiling lights and thermostats | Windows (tilt–turn), blinds | 13 (65% from total) |
| Office B | 242 | South-west, south-east | 0.55 | < 0.18 | Wall radiators (only heating) | Mechanical | 31 (88% from total) |
Figure 3
Floor plan of the case studies and location of the measurement devices.
Note: An example layout of the monitoring set-up during winter is shown.
Table 2
Overview and timeline of the monitoring campaigns.
| CAMPAIGN ID | CASE STUDY | SEASON | PERIOD |
|---|---|---|---|
| A-F | Office A | Fall | 28 October–9 November 2019 |
| A-W | Office A | Winter | 27 January–7 February 2020 |
| B-F | Office B | Fall | 18–29 November 2019 |
| B-W | Office B | Winter | 17–28 February 2020 |
| B-S | Office B | Summer | 17–28 August 2020 |
Figure 4
Overview of the multi-domain experimental set-up for the objective data collection.
Note: B1 = occupancy detection; B2 = window reed sensors; B3 = angle sensors; B4 = wireless smart plugs; red dot on the radiator = heat flux sensor for recording heating energy; 1–5 = sensors for indoor thermal environment; 8–9 = sensors for indoor air quality; 11–12 = sensors for visual environment; and 17 = a sensor for acoustic environment. For details about the equipment labelled 1–17, see Appendix A in the supplemental data online.
Figure 5
Surveying of occupants: (a) response rates to surveys during different campaigns (adjusted response rate – response rate related to the seasonal tracked peak occupancy); (b) frequency of self-reporting interactions (answers to the question ‘Over the last two weeks, how often did you report your interactions on the mobile phones installed close to window and blinds?’); and (c) reasons for not taking action even when feeling uncomfortable (answers to the question ‘Over the last two weeks, it happened that I felt uncomfortable, but I did not interact with controls, because …’).
Figure 6
Post-campaign survey results regarding comfort (PIT-A) and action surveys (PIT-B).
Note: Numbers refer to the completed responses from both offices.
Figure 7
Logged window-opening actions from wireless window state loggers before (n = 22), during (n = 28) and after (n = 18) in office B’s winter measurement campaign (B-W).
Figure 8
Post-campaign survey results regarding the perceived intrusiveness of the eCOMBINE experimental set-up.
Note: Responses from both offices A and B.
Table 3
Confusion matrix and key performance metrics assessing the alignment between self-reported and tracked window opening actions.
| CAMPAIGN ID | FN | FP | TN | TP | PRECISION | RECALL | ACCURACY |
|---|---|---|---|---|---|---|---|
| A-F | 30 | 13 | 33,911 | 30 | 0.70 | 0.50 | 0.99 |
| A-W | 24 | 5 | 32,507 | 8 | 0.62 | 0.25 | 0.99 |
| B-F | 11 | 8 | 22,565 | 16 | 0.67 | 0.59 | 0.99 |
| B-W | 13 | 5 | 22,607 | 20 | 0.56 | 0.61 | 0.99 |
| B-S | 29 | 16 | 22,609 | 13 | 0.72 | 0.31 | 0.99 |
[i] Note: True positives (TP) indicate correctly reported tracked actions; false negatives (FN) are tracked actions with no corresponding report; false positives (FP) are reported actions without a matching tracked event; and true negatives (TN) represent instances where neither a tracked nor a reported action occurred. Precision reflects the accuracy of self-reports, recall measures the completeness of reporting and accuracy captures the overall correctness of classification.
Figure 9
Window-opening actions: percentage of reported (by employees) window-opening actions in the total tracked (with window reed sensors) actions during the different monitoring campaigns.
Note: For IDs, see Appendix A in the supplemental data online.