Measuring and Comparing User Convenience in Smart Home Devices: Methods, Metrics, and User Perspectives

Objective:

This Master’s thesis aims to investigate how “convenience” — one of the main selling points of smart home technology — can be systematically defined, measured, and compared across different device types and use cases. Building on a heterogeneous collection of smart devices (e.g., smart lights, locks, smoke detectors, appliances, irrigation systems), the work will develop a conceptual and empirical framework for evaluating user-perceived convenience. A key part of the thesis will be the design and execution of one or more user surveys or structured interviews to collect qualitative and/or quantitative data from real users.

Potential Work Packages (not exhaustive):

• Literature review – analyze existing research on smart home usability, perceived value, and convenience-related metrics
• Device classification – identify and group smart home devices based on functionality, interaction patterns, and automation levels
• Definition of convenience dimensions – develop a structured model of convenience (e.g., time saved, ease of use, control, reliability, context-awareness)
• Design of empirical study – develop questionnaires or interview guides targeting everyday users of smart devices
• Study execution – conduct user surveys and/or structured interviews to gather data on subjective convenience across multiple devices or use cases
• Data analysis – apply qualitative and/or statistical methods to identify trends, patterns, and differences in perceived convenience
• Comparison framework – propose a method to evaluate and rank devices based on user feedback and usage context
• Critical reflection – assess limitations, generalizability, and implications of the findings for smart home design and adoption

Optional Extensions (depending on time and interest):

• Correlate convenience scores with technical metrics such as setup time, automation depth, or power consumption
• Explore cultural, demographic, or contextual factors that influence convenience perception
• Apply the model to real-world smart home scenarios or user profiles (e.g., elderly users, tech-savvy households)
• Suggest practical design recommendations for manufacturers or platform developers based on user insights
• Build a prototype tool for structured convenience evaluation across smart home systems

Note:

This topic is well-suited for students with an interest in Human-Centered Computing (HCC) and smart home technologies. It is strongly recommended that students have prior experience with empirical research methods — for example, through successful completion of courses such as Human-Centered Computing, Telematics, Embedded Systems Architecture and/or the Microprocessor Lab. Basic familiarity with survey design, qualitative analysis, usability testing will be beneficial. If you’re interested, please get in touch via e-mail to schedule a meeting where we can discuss the topic in more detail and align on the scope.