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Continual two-year measurements of daylight illuminance were performed in order to evaluate the daylighting of a model room. The key research idea was to study room orientation and its effect on daylight availability by using real measurements from a physical scale model. Firstly, differences between the illuminance in the north- and south-oriented rooms were compared. Secondly, a characteristic annual profile of the external horizontal illuminance data was determined. Finally, the median external diffuse illuminance data from measurements were compared with values based on the values recommended in the standard. The goal of the research was focused on the evaluation of a regional daylight climate model applicable for daylight evaluations. The results of the daylight illuminance measurements showed the importance of climatic daylight data for indoor daylighting in building design performance. [ABSTRACT FROM AUTHOR]

The sunlight exposure represents one of key parameters of indoor climate comfort. The evaluation of sunlight access into buildings is based on a methodology of European standard EN 17037. The methodology is focused on specification of an insolation time which would comply with requirements for the sunlight expo sure of permanently occupied spaces like houses and residential buildings as well as schools or hospitals. The sunlight exposure evaluation is recommended to be between 1st February and 21st March. The specific date from the interval can be selected for individual evaluations. This is a relatively long period of days in which the insolation could vary meaningfully. The aim of this study is to evaluate how the sunlight exposure might be changed in the recommended standard period in dependence on the geographic locality and climatic conditions in the Central Europe region. It depends on the sunlight time and specific design situations as well as shading obstructions. The review of the sunlight exposure is determined. The review results can perform information about design possibilities for the sunlight exposure in real buildings in the given climatic locality. [ABSTRACT FROM AUTHOR]

Currently, there is an increasing need for reliable mechanisms for automatically detecting and localizing people—from performing a people-flow analysis in museums and controlling smart homes to guarding hazardous areas like railway platforms. A method for detecting people using FLIR Lepton 3.5 thermal cameras and Raspberry Pi 3B+ computers was developed. The method creates a control and capture library for the Lepton 3.5 and a new person-detection technique that uses the state-of-the-art YOLO (You Only Look Once) real-time object detector based on deep neural networks. A thermal unit with an automated configuration using Ansible encapsulated in a custom 3D-printed enclosure was used. The unit has applications in simple thermal detection based on the modeling of complex scenes with polygonal boundaries and multiple thermal camera monitoring. An easily deployable person-detection and -localization system based on thermal imaging that supports multiple cameras and can serve as an input for other systems that take actions by knowing the positions of people in monitored environments was created. The thermal detection system was tested on a people-flow analysis performed in the Czech National Museum in Prague. The contribution of the presented method is the development of a small and simple detection system that is easily mountable with wide indoor as well as outdoor applications. The novelty of the system is in the utilization of the YOLO model for thermal data. [ABSTRACT FROM AUTHOR]