Title
EnergonQL: A Building Independent Acquisitional Query Language for Portable Building Analytics
Abstract
ABSTRACTEmerging building analytics heavily rely on data-driven machine learning algorithms. However, writing these analytics is still challenging: developers not only need to know what data is required but also where this data is in each individual building when writing applications. To bridge this gap between analytics and the actual resources in buildings, we present EnergonQL, a building independent acquisitional data query language that extracts data for building analytics with a declarative query processor. EnergonQL provides logic views of building resources that universally apply to all buildings, thus allowing portable building analytics across buildings. We evaluate EnergonQL with four different building analytics and show that with EnergonQL the line-of-code and development efforts can be effectively reduced.
Year
DOI
Venue
2020
10.1145/3408308.3427979
SENSYS
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Fang He100.34
Cheng Xu200.34
Yanhui Xu300.34
Dezhi Hong430.75
Dan Wang5415.01