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arXiv · 2412.14175

BiTSA: Leveraging Time Series Foundation Model for Building Energy Analytics

Xiachong Lin·Arian Prabowo·Imran Razzak·Hao Xue·Matthew Amos·Sam Behrens·Flora D. Salim
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Abstract

Incorporating AI technologies into digital infrastructure offers transformative potential for energy management, particularly in enhancing energy efficiency and supporting net-zero objectives. However, the complexity of IoT-generated datasets often poses a significant challenge, hindering the translation of research insights into practical, real-world applications. This paper presents the design of an interactive visualization tool, BiTSA. The tool enables building managers to interpret complex energy data quickly and take immediate, data-driven actions based on real-time insights. By integrating advanced forecasting models with an intuitive visual interface, our solution facilitates proactive decision-making, optimizes energy consumption, and promotes sustainable building management practices. BiTSA will empower building managers to optimize energy consumption, control demand-side energy usage, and achieve sustainability goals.

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Xiachong Lin, Arian Prabowo, Imran Razzak, Hao Xue, Matthew Amos, Sam Behrens, Flora D. Salim. 2024-11-20. BiTSA: Leveraging Time Series Foundation Model for Building Energy Analytics. https://doi.org/10.1109/icdmw65004.2024.00122

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