Ensuring real-time data integrity in smart building applications: A systematic end-to-end comprehensive pipeline evaluated in numerous real-life cases

作     者：Stefanopoulou, Aliki Michailidis, Iakovos Karatzinis, Georgios Lepidas, Georgios Boutalis, Yiannis S. Kosmatopoulos, Elias B. 

作者机构：Ctr Res & Technol Hellas Informat Technol Inst 6th Km Harilaou Thermis Thessaloniki 57001 Greece Democritus Univ Thrace Sch Engn Dept Elect & Comp Engn Vasilissis Sofias 12 Xanthi 67100 Greece 

出 版 物：《ENERGY AND BUILDINGS》 (Energy Build.)

年 卷 期：2025年第336卷

核心收录：

学科分类：0820[工学-石油与天然气工程] 08[工学] 0813[工学-建筑学] 0814[工学-土木工程] 

基　　金：European Union [101023666  101123238] 

主　　题：Smart buildings Data filtering Data imputation Real-time data processing 

摘      要：In this study, we propose a comprehensive, end-to-end data healing pipeline, developed and tested in real buildings facing diverse severity problems. This pipeline is designed to ensure the accuracy and reliability of smart building data in a fast and responsive manner, using computationally lightweight statistical approaches for outlier detection and LightGBM for data imputation. Both methods are optimized for low computational cost, making them ideal for real-world scenarios requiring immediate feedback and capable of handling very large datasets efficiently. Our system is designed to operate automatically, capable of applying real-time data processing and periodic model updates without manual intervention. It was evaluated using Key Performance Indicators over nine weeks across five smart buildings in the EU, revealing discrepancies in performance across different time periods and buildings. These findings highlight the need for tailored data healing strategies for varying dataset sizes, ultimately enhancing data quality for more reliable analyses and informed decision-making. The implementation of this pipeline contributes to more accurate energy usage, improved occupant comfort, and more efficient building operations, supporting the broader goals of sustainability and energy efficiency in smart buildings.