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Data analysis on building load profiles: A stepping stone to future campus
For the sustainable development of smart cities across the globe, energy efficiency is becoming a major factor to the maintenance and planning of buildings. In order to demonstrate the potential of data driven approaches in understanding building energy usage, we conduct a data analysis study based on a 10-year data set from 361 buildings of a university campus that are equipped with 1951 smart meters. The preliminary results obtained from our analysis is presented. Results of both clustering analysis and prediction analysis offer a better understanding of common building energy usage as well as a better identification of anomalous behaviors in the usage patterns.
Data analysis on building load profiles: A stepping stone to future campus
For the sustainable development of smart cities across the globe, energy efficiency is becoming a major factor to the maintenance and planning of buildings. In order to demonstrate the potential of data driven approaches in understanding building energy usage, we conduct a data analysis study based on a 10-year data set from 361 buildings of a university campus that are equipped with 1951 smart meters. The preliminary results obtained from our analysis is presented. Results of both clustering analysis and prediction analysis offer a better understanding of common building energy usage as well as a better identification of anomalous behaviors in the usage patterns.
Data analysis on building load profiles: A stepping stone to future campus
Wang, Long (author) / Ding, Yong (author) / Riedel, Till (author) / Miclaus, Andrei (author) / Beigl, Michael (author)
2017-09-01
408132 byte
Conference paper
Electronic Resource
English
STEPPING STONE PROCESSING METHOD AND THE STEPPING STONE USING NATURAL STONE
European Patent Office | 2020
|STEPPING STONE PROCESSING METHOD AND THE STEPPING STONE USING NATURAL STONE
European Patent Office | 2021