BiTSA: Leveraging Time Series Foundation Model for Building Energy Analytics

Autor:	Lin, Xiachong, Prabowo, Arian, Razzak, Imran, Xue, Hao, Amos, Matthew, Behrens, Sam, Salim, Flora D.
Rok vydání:	2024
Předmět:	Computer Science - Computational Engineering Finance and Science Computer Science - Computers and Society Computer Science - Human-Computer Interaction
Druh dokumentu:	Working Paper
Popis:	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. Comment: 4 pages, 4 figures, 3 tables
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2412.14175 Zobrazit plný text záznamu View this record from Arxiv