Several energy gains or losses in buildings are influenced by occupant interactions with building services, such as lighting or HVAC systems, thermostat settings, and window and shading operations. Occupant behavior is usually triggered by discomfort, nevertheless actions taken to restore comfort can have an impact on final energy demand. Thus, an accurate energy assessment for both new and retrofit building design must properly account for occupant behavior, based on reliable models developed from real case studies and detailed monitoring. This work presents a new approach for continuous and non-intrusive monitoring of window opening angle, shading position, and lighting operation to determine the net air exchange area for ventilation. A camera-based device and a post-processing algorithm are developed, and a monitoring campaign over 6 month is carried out to showcase the monitoring system. The device consists of a camera setup connected to a microprocessor, and a dedicated script which enables the device to track window opening, shading movement and lighting operation through target and object identification. Results of the prototyping case study show that the proposed system can effectively detect window opening angles and shutter positions, dealing with multiple windows and shutters simultaneously and allowing the deployment of the benefits of continuous monitoring. The explored application is the direct use of the collected data for the calculation of natural ventilation rates from the net exchange area (EN 16798-7) over long term datasets. As future development, the monitoring system will be used to develop accurate behavioral models based on the experimental data to analyze and suggest the occupant’s response to discomfortable conditions in order to improve indoor air quality and save energy.
Read full abstract