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Use of Multi-Agent Theory to Resolve Complex Indoor Air Quality Control Problems
Shang-Yuan Chen1, Cheng-Yen Chen2
1School of Architecture, Feng Chia University, No. 100, Wenhwa Rd., Seatwen, Taichung 40724, Taiwan. shangyuanc@gmail.com.
Sensors (Basel, Switzerland)
|March 13, 2019
Summary
This study introduces a multi-agent system for indoor air quality control in Taiwan. The system uses agents to manage air quality and resolve conflicts, enhancing indoor environments.
Area of Science:
- Environmental Science
- Computer Science
- Artificial Intelligence
Background:
- Taiwan faces significant challenges with widespread haze and poor indoor air quality.
- Effective indoor air quality (IAQ) management is crucial for public health and comfort.
Purpose of the Study:
- To develop and evaluate an indoor air quality control system using Multi-Agent theory.
- To establish a conflict resolution mechanism for maintaining a healthy indoor environment.
Main Methods:
- Utilized Multi-Agent theory with pre-defined agent rules for decision-making.
- Implemented the system using Arduino for data collection and equipment control.
- Developed the user interface and control program with LabVIEW.
Main Results:
- Verified the feasibility of applying multi-agent theory to IAQ control systems.
- Demonstrated that individual intelligent agents can autonomously resolve basic conflicts.
- Identified limitations in handling complex scenarios with multiple factors and user statuses.
Conclusions:
- Multi-agent systems show promise for intelligent indoor air quality management.
- Further algorithm development is needed for complex decision-making and context control beyond binary logic.
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