London, July 18(SocialNews.XYZ) A team of researchers from China and the Netherlands has successfully developed an innovative solution using GPT-4 to automate data for building energy management.
GPT-4, OpenAI's generative large language model, has previously demonstrated remarkable human-level performance in various real-world scenarios such as coding, writing, and image generation.
However, its ability to analyse building operational data using data mining tools at a comparable human-level performance remains uncertain.
The building sector is a significant contributor to global energy consumption, accounting for approximately 33 per cent of the world's final energy usage.
While data mining technologies can save approximately 15-30 per cent of the energy consumed in buildings, their practical application has been limited due to its labour-intensive nature, resulting in a scarcity of real-world use cases.
The team from Eindhoven University of Technology in the Netherlands and Zhejiang University in China, successfully showcased GPT-4's capability to generate codes that forecast building energy loads, even when provided with limited user information.
Furthermore, GPT-4 exhibited the ability to identify device faults and detect abnormal patterns in system operations by analysing building operational data.
When applied in real-world buildings, the codes generated by GPT-4 demonstrate a high level of accuracy in energy load prediction.
In addition, GPT-4 offers reliable and precise explanations for fault diagnosis and anomaly detection outcomes, the study showed.
"By automating coding and data analysis tasks, GPT-4 effectively liberates humans from tedious work, resulting in a more accessible and cost-effective approach to data-guided building energy management,” said Chaobo Zhang, a post-doctoral researcher at Eindhoven's Department of the Built Environment.
The study, published in the KeAi journal Energy and Built Environment, represents a breakthrough in the domain of building energy management.
Automated data mining solutions are still rare for building energy management until now.
"Our study indicates that GPT-4 is a promising solution to enabling computers to implement customised data mining solutions for building energy management with limited assistance from humans,” said Yang Zhao, a professor at Zhejiang University, and senior author of the study.
"We hope more scientists can explore the potential of GPT-4 in this domain, so that the building energy management will be smarter and more efficient in the future."
Source: IANS
About Gopi
Gopi Adusumilli is a Programmer. He is the editor of SocialNews.XYZ and President of AGK Fire Inc.
He enjoys designing websites, developing mobile applications and publishing news articles on current events from various authenticated news sources.
When it comes to writing he likes to write about current world politics and Indian Movies. His future plans include developing SocialNews.XYZ into a News website that has no bias or judgment towards any.
He can be reached at gopi@socialnews.xyz