Behavior
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Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger
Chapters
Summary January 16th, 2020
This article describes a procedure for using and deploying an occupancy and light data logger which allows collecting data about light-switching behavior of participants in field settings.
Transcript
The occupancy and light data logger can be used in the field settings to gather information about the occurrence of a particular type of energy conservation behavior, which is light-switching. As opposed to natural observation, using data logger allows for fast, reliable, and uninterrupted measurement of participant's behavior, as well as provides an explicit operationalization of a given field experiment. To begin, connect the logger via USB cable to the computer by plugging the larger end of the USB interface cable into a USB port on the computer, and the smaller end of the USB interface cable into the port on the device.
Launch the software by clicking the launch icon on the toolbar, which opens the logger setup window. Enter a name for the launch. Select the light sensor.
Set the measurement to log state from the drop down list and choose the state description off and on from the drop down list. Select the occupancy sensor. Set the measurement to log state from the drop down list and choose the state description unoccupied occupied from the drop down list.
Click the filters button to enable automatic calculation of additional values. Select the sensor type of choice. Select the type of filter and the interval to use.
Edit the name and click create new series. Select the drop down menu choices then click done. Click the advanced button to access the sensor properties.
Select the light sensor. Select set to maximum sensitivity for calibration and click the save button. Select the occupancy sensor.
Select a preset timeout value, or select custom and enter a value in minutes and seconds if needed. Click the save button. It is advisable to run a pilot test of the logger's deployment on the experimental site.
Choose the most optional timeout value of occupancy sensor based on the actual occupancy frequencies of participants. Select when to launch the logger depending on the experimental plan:immediately, at intervals which is available when logging run time, on a specified date and time, or by manually using the start button. Select when the logger should stop logging:when memory fills, or never stop which results in the newest data overwriting the oldest, stop manually, or stop at a specified date and time.
Click the start button upon finishing the configuration. Unplug the logger from the computer. Equip the logger with an additional fiber optic light pipe by connecting it to the back of the logger in order to filter out any ambient light and ensure the most accurate readings.
Mount the logger with the light pipe next to the designated light source. If previously configured in the software, press the start button at the logger to begin recording. The placement of logger mounting should not be in proximity to any kind of heating sources to ensure that only the body heat of the room users will be recorded.
After finishing recording, revisit the experimental site and remove the logger for the purpose of data read-out. Connect the logger via USB cable to the computer and launch the analysis software package dedicated to the data logger. Click the read-out device button from the control panel, or select to read-out from the device menu, which will enable the logger to unload the gathered data.
Choose a location and the file name to save the data. Click save, and select the sensors and events to display in a graph and click plot. Select the series to view on the table data and plot.
Click the all or none button to select or deselect all series, or click the checkboxes to select or deselect individual series. Select export table data from the control panel. Choose a destination folder for the export.
Data loggers could serve as a useful tool for conducting field experiments in psychology. This table presents recorded data of light-switching behavior frequencies, as well as occupancy time of users that visited two public restrooms during a 15 day measurement. Data obtained by the logger can be analyzed by performing a logistic regression analysis for light status and restroom type.
This table shows the coefficient of the built model. When following this procedure, researchers can additionally test the effectiveness of various behavioral interventions such as prompts with persuasive appeals aimed at fostering light-switching behavior. In addition to nominal outcomes of light and occupancy status, data logger allows to collect and analyze quantitative information about time of room occupancy status, as well as time between occupancy events.
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