Smart Buildings: A Comprehensive Systematic Literature Review on Data-Driven Building Management Systems

Area of Science:

• Computer Science
• Building Technology
• Information and Communication Technologies (ICTs)

Background:

• Buildings are complex systems requiring dynamic management for occupant needs and resource optimization.
• The proliferation of ICTs has made Building Management Systems (BMS) a multidisciplinary field.
• Existing research on data-driven BMS solutions necessitates systematic review and classification.

Purpose of the Study:

• To provide a comprehensive overview of the BMS field.
• To systematically review and classify data-driven BMS research from a computer science standpoint.
• To identify key topics, methods, architectures, and smartization features in BMS.

Main Methods:

• Conducting a systematic literature review (SLR).
• Applying a rigorous methodology from a computer science perspective.
• Analyzing research papers on data-driven solutions for BMS.

Main Results:

• Identification of main topics within the BMS field.
• Classification of recent data-driven methods used in BMS.
• Understanding of the underlying computing architectures of BMS.
• Analysis of features contributing to building smartization.

Conclusions:

• The study synthesizes current trends in data-driven BMS.
• It offers a computer science-focused perspective on BMS research.
• Provides directions for future research in smart building technologies.