Siemens and Nanyang Technological University, Singapore (NTU Singapore) signed a research collaboration agreement on 28 February to develop new technologies that aim to optimise building performance. The joint research team will leverage machine learning to extract and analyse data gathered from building operations to help understand, predict and optimise building performance.
This will help building management teams and building owners enhance the performance of their infrastructure and see further energy savings and cost reductions.
The research collaboration will be conducted over three years, and will be segmented into five areas of work:
- data pre-processing; cleaning and collection
- soft sensors
- building predictive performance
- asset optimisation and automatic detection of performance anomalies
- review and development for commercialisation.
Sensors in buildings produce massive amount of data that are not fully utilised. Currently, this data is mostly used for calculating energy production and consumption, and fault detection within building management systems. The data will be used to develop algorithms to help forecast next-day energy demand. Understanding the cause of any increase in energy usage could be used to alert building management teams and end-users, establishing a new baseline for determining energy savings.
Siemens Building Technologies will support the research with domain-driven knowledge in equipment and equipment parameters, and will use its cloud-based platform, Navigator, to offer powerful analyses and reports. Siemens will also collect data via its proprietary software proxy to aid in the delivery of work packages related to fault detection, improvement of system performance and asset optimisation.
The research team will also extract data from the following sources on the NTU campus to facilitate testing methods, and thereafter predict and optimise building performance:
existing chiller plants solar panels and other energy systems various buildings and offices within the NTU campus weather data from the Singapore Meteorological Service
“In today’s digital age, buildings are increasingly becoming more intelligent, and are a core component of smart cities. This research further underlines Siemens and NTU Singapore’s commitment to work together to create a positive impact in Singapore’s building industry and to help build a smarter nation,” said Dr Thai Lai Pham, CEO of Siemens Building Technologies in ASEAN.
Professor Lam Khin Yong, NTU’s Vice President for Research, said, “NTU aspires to be one of the most eco-friendly and technologically advanced Smart Campuses in the world. The Research, Development and Demonstration (RD&D) project with Siemens will allow NTU researchers to test their machine learning algorithms in various smart building applications by leveraging on data gathered from our campus buildings.”
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