Reading the tea leaves in an intelligent Coffee Corner: challenges for understanding behavior

Area of Science:

• Human-Computer Interaction
• Ubiquitous Computing
• Behavioral Science

Background:

• Living Labs offer experimental settings for studying technology in real-world contexts.
• Context-aware systems collect and utilize information about users and their environment.
• Intelligent environments can enhance user experience through personalized services.

Purpose of the Study:

• To discuss challenges and opportunities for methodological innovation in context-aware systems.
• To explore the use of a Living Lab for unobtrusive and trustworthy behavioral data collection.
• To demonstrate how contextual data can be used for user behavior modeling and service customization.

Main Methods:

• Implementation of an experimental Living Lab: a context-aware Coffee Corner.
• Deployment of a context-aware infrastructure to collect sensory information on user movement and interaction.
• Utilization of proximity-aware and context-aware security features for user identification and authentication.
• Analysis of contextual data to construct user behavioral models.

Main Results:

• The Coffee Corner Living Lab successfully collected unobtrusive and trustworthy user behavior data.
• Contextual data enabled the development of a behavioral model for service customization.
• Proximity and context awareness were leveraged for security and personalized services.
• Methodological challenges in context-aware system development were addressed through practical experience.

Conclusions:

• Living Labs provide a valuable framework for advancing methodological innovation in context-aware computing.
• Unobtrusive and privacy-respecting data collection is feasible in intelligent environments.
• User behavior modeling based on contextual data can lead to enhanced and customized services.
• The experimental Coffee Corner demonstrates the potential of ubiquitous computing in everyday settings.