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View all- Cretu GStamatescu IStamatescu G(2024)Modeling and Prediction of Occupancy in Buildings Based on Sensor Data Using Deep Learning MethodsIEEE Access10.1109/ACCESS.2024.343258412(102994-103003)Online publication date: 2024
Energy consumed for heating in northern China amounts to 40% of the total energy consumption of cities and towns of the country, and the resulting environmental pollution is very severe as coal is the main fuel for heating in China. As a result, there ...
Occupancy information in buildings is a crucial information to enable automated load controlling resulting in significant energy savings. Unfortunately, current methods obtain occupancy data by using additional infrastructure, which can be expensive and ...
Energy and environmental sustainability is a major global trend for the 21st century. Thermal discomfort and poor air quality in office buildings can result in loss of productivity, absenteeism and medical problems. The most frequently identified causes ...
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