Data-fusion for increasing temporal resolution of building energy management system data

摘要: Buildings are known to be significant energy consumers throughout the world. Thus, improving efficiency of buildings is a key research goal. However, maintaining occupant comfort while in requires close monitoring building environment and immediate control actions taken when sub-optimal behavior identified. Such high frequency data from sensors. Therefore, increasing collection rate or temporal resolution sensors can lead improved state-awareness. This paper presents an on-line learning, data-fusion based methodology that uses Artificial Neural Networks (ANNs) increase sensor data. The presented method utilizes information different predict higher specific Furthermore, capable learning changing for long-term accuracy. was applied real-world dataset shown able with accuracy compared classical methods. prediction operation.