Dataset of Bluetooth Low Energy IQ samples for Angle of Arrival determination

One significant challenge in research is to collect a large amount of data and learn the underlying relationship between the input and the output variables. This data, collected in a laboratory setting, is intended to approximate real-world industrial scenarios. The samples were collected using a Texas Instruments (TI) BOOST-XL-AOA antenna array and the Ground Truth (GT) position of the tag was tracked and logged by a motion capture system with millimetre accuracy. This position was used to calculate the angle between the tag and the antenna array. The collected samples and the process of generating GT labels were validated using the TI phase difference of arrival (PDoA) implementation on the data, yielding a mean absolute error (MAE) at one of the heights without obstacles of 25.71 degrees

Dataset of Bluetooth Low Energy IQ samples for Angle of Arrival determination

One significant challenge in research is to collect a large amount of data and learn the underlying relationship between the input and the output variables. This data, collected in a laboratory setting, is intended to approximate real-world industrial scenarios. The samples were collected using a Texas Instruments (TI) BOOST-XL-AOA antenna array and the Ground Truth (GT) position of the tag was tracked and logged by a motion capture system with millimetre accuracy. This position was used to calculate the angle between the tag and the antenna array. The collected samples and the process of generating GT labels were validated using the TI phase difference of arrival (PDoA) implementation on the data, yielding a mean absolute error (MAE) at one of the heights without obstacles of 25.71 degrees

How building design and technologies influence heat-related habits

The discrepancy between calculated heat demand and measured heat consumption – the performance gap – suggests that the energy efficiency of houses affects the energy-consuming habits of its occupants. This coincides with the theories of practice describing how materiality affects practices through reconfiguring practical understandings, e.g. comfort expectations. Heat-related habits are investigated in the paper across material contexts, e.g. building characteristics and technologies. Evidence based on a combined questionnaire survey and administrative data on occupants (n = 1216) living in single-family detached houses in Denmark shows that the practices of adjusting thermostats and the amount of clothing worn indoors as well as perceived indoor temperature correlate with building characteristics, e.g. energy efficiency of the building envelope and technical installations. These correlations are moderated by the socio-demographic characteristics of occupants. However, building characteristics are found to be less influential on the frequency of opening windows. The results indicate that occupants dress warmer and keep lower temperatures in energy-inefficient houses. This suggests that material arrangements have a significant influence on occupant expectations and practices, which lead to increased indoor temperatures and energy demand. A challenge for building regulations will be to account for how energy efficient house characteristics and technologies adversely affect occupants’ energy-consuming behaviour

How building design and technologies influence heat-related habits

The discrepancy between calculated heat demand and measured heat consumption – the performance gap – suggests that the energy efficiency of houses affects the energy-consuming habits of its occupants. This coincides with the theories of practice describing how materiality affects practices through reconfiguring practical understandings, e.g. comfort expectations. Heat-related habits are investigated in the paper across material contexts, e.g. building characteristics and technologies. Evidence based on a combined questionnaire survey and administrative data on occupants (n = 1216) living in single-family detached houses in Denmark shows that the practices of adjusting thermostats and the amount of clothing worn indoors as well as perceived indoor temperature correlate with building characteristics, e.g. energy efficiency of the building envelope and technical installations. These correlations are moderated by the socio-demographic characteristics of occupants. However, building characteristics are found to be less influential on the frequency of opening windows. The results indicate that occupants dress warmer and keep lower temperatures in energy-inefficient houses. This suggests that material arrangements have a significant influence on occupant expectations and practices, which lead to increased indoor temperatures and energy demand. A challenge for building regulations will be to account for how energy efficient house characteristics and technologies adversely affect occupants’ energy-consuming behaviour