The PBC Model: Supporting Positive Behaviours in Smart Environments

Area of Science:

• Human-Computer Interaction
• Behavioral Science
• Smart Environments

Background:

• Office environments face behavioral challenges like sedentary habits and resource misuse.
• Current behavioral modeling in smart environments lacks personalization, impacting service provision effectiveness.
• Objective techniques, particularly behavioral modeling within smart environments (SEs), offer potential solutions.

Purpose of the Study:

• To introduce and evaluate a novel approach for behavioral modeling in smart environments using user models.
• To develop the Positive Behaviour Change (PBC) Model, emphasizing user-specific data for accurate behavioral analysis.
• To address the gap in understanding the effectiveness of current behavioral models concerning user preferences.

Main Methods:

• Development of the Positive Behaviour Change (PBC) Model, incorporating smart environments, user models, behavior models, classification, and intervention components.
• Evaluation of the PBC Model using Design Science Research Methodology.
• Naturalistic-summative evaluation through experimentation with office workers.

Main Results:

• Demonstrated that behavioral patterns can be successfully extracted from user models within smart environments.
• Showcased the ability to classify and quantify human behaviors based on extracted patterns.
• Confirmed that changes in behavior can be detected, facilitating the identification of appropriate interventions.

Conclusions:

• The novel PBC Model effectively integrates user models for enhanced behavioral modeling in smart environments.
• The model's components allow for the extraction, classification, quantification, and detection of behavioral changes.
• This approach provides a foundation for personalized interventions to address behavioral issues in smart environments.