36 H.B.Gunay et aL Building and Environment 70(2013)31-47 with venetian blinds,small movements account for a substantial many of the aforementioned limitations.It should also be noted reduction in number of hours occupants experience discomfort that if the discretization of the window state and the sampling glare (from 735 to 18 occupied hours)[83].This underlines the intervals are not fine enough,the data may be misleading,since the importance of interior design of office spaces,which allows occu- small window openings and short opening/closing intervals may be pants to reposition or change view direction,to reduce occupant lost.Warren and Parkins [31]and Brager et al.84]photographed discomfort and in turn,occupants'need for environmental behav- the facade of the building twice a day to quantify the window state ioral adaptations.The location (e.g.distance to the window)where which was discretized as open,slightly-open,or closed.Inkarojrit the occupant is seated in an office and the freedom to reposition or and Paliaga [38]automated the time lapse-photography technique change view direction should be noted as this accounts for some so that three major facades of a naturally ventilated office building variance in the reviewed studies [51,571.The physical variables were photographed at fixed times(four times per day for nine days) should be collected as close as possible to the workstations or during a shoulder season,while windows were recorded as a binary occupants. state(i.e.open/closed).Reinhart [56]suggested that observational round-offs due to crude state-discretizations (e.g.fully-closed or 2.1.7.Observation techniques,time and state discretization open-blinds)can cause critical information loss about smaller The technique employed to monitor the change in the state(e.g. behavioral adaptations.For example,some occupants may opt to window opening),the sampling interval (e.g.twice per day).and close their blinds up to a level to block direct sunlight by leaving the state discretization (e.g.open/closed or open/half-open/closed) some opening to maintain view to outdoors;but this may not be may represent limitations for the model prediction.Warren and noted as a behavioral adaptation if the state was discretized as on Parkins [31]carried out a survey on five buildings with a total of 196 off.Thus,a future research effort to understand the sensitivity of offices by employing a time-lapse photography technique.This such algorithms on the state and time discretization can be technique,despite being non-invasive and relatively inexpensive, beneficial. does not give any insight about the indoor environment [24.This is The reviewed literature on the window shades using the time- perhaps why Warren and Parkins [31]used weather variables lapse photography technique involves similar discretization in rather than the indoor variables to suggest a correlation.Brager time and state.The frequency of photographs ranges from once a et al.84]tackled this limitation with continuous desktop indoor week [54]to once each hour [85]during the official work hours. monitoring and questionnaire surveys along with the time-lapse Despite the predominant seasonal effects in the window shade photography in a naturally ventilated office building with 230 deployment,the diurnal variations were reported as noticeable people.Likewise,the positions of the window shading system were particularly for south,east,and west facades.Thus,it has been monitored using the time-lapse photography technique [32.52- suggested that the photography technique should be employed at 551.The limitation of using this technique for studying windows least twice a day [24].The discretization of the window shades was and window shades is that the slat angles of Venetian blinds and constrained with the image resolution and the post-processing the hinged-window openings may not be distinguishable[24].The technique (i.e.digital image processing or manual analysis).The insufficient image resolution [52.55.visual obstructions [29,54]. window shade states were discretized between 2 [49]and 10[85 and uncertainty in weather(e.g.fog)[54]represent other limita- discrete shade positions.Unlike roller blinds,the slat angle in tions for the technique.However,with the development of image Venetian blinds should be incorporated in the state discretization, recognition algorithms this technique can be more widely used for since the slat angle (i.e.tilted upwards or downwards)affects the retrieving information about the windows and window shades. amount of transmitted daylight by a factor of 10 [521.However,in O'Brien et al.85]demonstrated that this when coupled with image the reviewed literature,the Venetian blinds were discretized as recognition algorithms,as shown in Fig.2.can be used to improve open or closed [47]and open/tilted downwards/closed [55. ■里 ■ 12345678910111213141516 (a) (b) (c) Fig.2.(a)Original photograph.(b)Preprocessing image after cropping and transformation.(c)Post-processing image with window shades deployments discretized with 10 in- termediate states (taken from O'Brien,Kapsis et al.241).with venetian blinds, small movements account for a substantial reduction in number of hours occupants experience discomfort glare (from 735 to 18 occupied hours) [83]. This underlines the importance of interior design of office spaces, which allows occu￾pants to reposition or change view direction, to reduce occupant discomfort and in turn, occupants’ need for environmental behav￾ioral adaptations. The location (e.g. distance to the window) where the occupant is seated in an office and the freedom to reposition or change view direction should be noted as this accounts for some variance in the reviewed studies [51,57]. The physical variables should be collected as close as possible to the workstations or occupants. 2.1.7. Observation techniques, time and state discretization The technique employed to monitor the change in the state (e.g. window opening), the sampling interval (e.g. twice per day), and the state discretization (e.g. open/closed or open/half-open/closed) may represent limitations for the model prediction. Warren and Parkins [31] carried out a survey on five buildings with a total of 196 offices by employing a time-lapse photography technique. This technique, despite being non-invasive and relatively inexpensive, does not give any insight about the indoor environment [24]. This is perhaps why Warren and Parkins [31] used weather variables rather than the indoor variables to suggest a correlation. Brager et al. [84] tackled this limitation with continuous desktop indoor monitoring and questionnaire surveys along with the time-lapse photography in a naturally ventilated office building with 230 people. Likewise, the positions of the window shading system were monitored using the time-lapse photography technique [32,52e 55]. The limitation of using this technique for studying windows and window shades is that the slat angles of Venetian blinds and the hinged-window openings may not be distinguishable [24]. The insufficient image resolution [52,55], visual obstructions [29,54], and uncertainty in weather (e.g. fog) [54] represent other limita￾tions for the technique. However, with the development of image recognition algorithms this technique can be more widely used for retrieving information about the windows and window shades. O’Brien et al. [85] demonstrated that this when coupled with image recognition algorithms, as shown in Fig. 2, can be used to improve many of the aforementioned limitations. It should also be noted that if the discretization of the window state and the sampling intervals are not fine enough, the data may be misleading, since the small window openings and short opening/closing intervals may be lost. Warren and Parkins [31] and Brager et al. [84] photographed the facade of the building twice a day to quantify the window state which was discretized as open, slightly-open, or closed. Inkarojrit and Paliaga [38] automated the time lapse-photography technique so that three major facades of a naturally ventilated office building were photographed at fixed times (four times per day for nine days) during a shoulder season, while windows were recorded as a binary state (i.e. open/closed). Reinhart [56] suggested that observational round-offs due to crude state-discretizations (e.g. fully-closed or open-blinds) can cause critical information loss about smaller behavioral adaptations. For example, some occupants may opt to close their blinds up to a level to block direct sunlight by leaving some opening to maintain view to outdoors; but this may not be noted as a behavioral adaptation if the state was discretized as on/ off. Thus, a future research effort to understand the sensitivity of such algorithms on the state and time discretization can be beneficial. The reviewed literature on the window shades using the time￾lapse photography technique involves similar discretization in time and state. The frequency of photographs ranges from once a week [54] to once each hour [85] during the official work hours. Despite the predominant seasonal effects in the window shade deployment, the diurnal variations were reported as noticeable particularly for south, east, and west facades. Thus, it has been suggested that the photography technique should be employed at least twice a day [24]. The discretization of the window shades was constrained with the image resolution and the post-processing technique (i.e. digital image processing or manual analysis). The window shade states were discretized between 2 [49] and 10 [85] discrete shade positions. Unlike roller blinds, the slat angle in Venetian blinds should be incorporated in the state discretization, since the slat angle (i.e. tilted upwards or downwards) affects the amount of transmitted daylight by a factor of 10 [52]. However, in the reviewed literature, the Venetian blinds were discretized as open or closed [47] and open/tilted downwards/closed [55]. Fig. 2. (a) Original photograph, (b) Preprocessing image after cropping and transformation, (c) Post-processing image with window shades deployments discretized with 10 in￾termediate states (taken from O’Brien, Kapsis et al. [24]). 36 H.B. Gunay et al. / Building and Environment 70 (2013) 31e47