Advanced Supervision of Smart Buildings Using a Novel Open-Source Control Platform

Area of Science:

• Building energy management systems
• Industrial control systems
• Artificial intelligence in automation

Background:

• Effective data presentation and real-time evaluation are crucial for smart building energy efficiency and occupant comfort.
• Timely fault detection and response are essential for maintaining building performance and preventing issues.

Purpose of the Study:

• To develop an advanced supervision procedure for smart buildings, acting as an artificial operator.
• To implement a system for continuous online monitoring and analysis of building processes.
• To enhance energy efficiency and comfort through autonomous process supervision.

Main Methods:

• Developing a procedure for an artificial operator to autonomously supervise processes.
• Utilizing signal analysis techniques for data evaluation.
• Implementing the procedure on an open-source control system platform suitable for advanced control techniques.

Main Results:

• The developed advanced supervision procedure was successfully tested in simulations.
• A practical case study using a real two-storey family house validated the procedure's effectiveness.
• The system demonstrated capabilities for autonomous process supervision and fault detection.

Conclusions:

• The proposed artificial operator provides a robust solution for advanced supervision in smart buildings.
• The use of an open-source platform facilitates the implementation of advanced control strategies.
• This approach enhances building performance by enabling real-time monitoring and autonomous fault management.