Smart Home Technology Research Project

December 2020-May 2022
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Project Title: A User‑Centric Evaluation of Smart Home Resolution Approaches for Conflicts Between Routines

Project Overview

As an undergraduate research assistant, I’ve had the opportunity to contribute to this project with PhD student Ali Zaidi, co-advised by Professor Karrie Karahalios and Professor Indril Gupta. This research project was conducted as part of Professor Karahalios’ Social Spaces group at the University of Illinois at Urbana-Champaign’s Computer Science department.

This group focuses on investigating sociable systems and encompasses many methods such as exploring virtual-physical spaces for mediated communication, building communication objects and interactive interfaces that connect people and/or spaces, and analyzing how people interact within social spaces.

My Role

Undergraduate Research Assistant
‍Data Collection, Systematic Literature Review, Qualitative Coding, Data Analysis, Interactive Visualization, Data Visualization

This page is solely my contribution to this project to maintain user privacy and project anonymity as it goes through paper submission.

Abstract

The purpose of the smart home project is to understand the core issues that current smart device owners face from both a technical and social perspective.

We collected thousands of posts from several prominent Reddit smart home communities first in 2020, and then one year later in 2021. We conducted qualitative analyses of these posts to extract higher-level themes and analyzed them to see how the core issues and problems for smart device owners changed in this year-long period.

Utilizing the data analysis, we then built encompassing visualizations to communicate the breadth of research findings. These findings can be used to create design principles for future smart device owners, as well as to understand how the pandemic affected smart device owners from a holistic perspective with regard to their device ownership.

‍At the core of this interaction, we understand that there is a user, who has a specific goal in mind, who either already has a set of smart devices in their home and a set of actions that they are willing to do with those devices in order to achieve that goal.

Research Questions

Throughout this project, we hoped to answer the following questions through Reddit data analysis:

What are common difficulties people face with smart devices?
What are their motivations for using smart devices?
How do people address their difficulties with smart devices?
Does brand loyalty play a role in people's decisions to acquire smart devices?
Does the task of owning and managing smart devices ever outweigh the convenience of owning the smart device(s) at all?
How do users address this?
What do users consider while they create their expectations for smart home routine execution?

Qualitative Coding & Analysis

Over the span of this project, I used qualitative coding to extract findings from 18 Reddit threads, over 2000 posts, throughout a span of 2 years.

I began my work on this project by analyzing the user data that was web scraped from relevant Reddit threads on smart home devices. These threads were selected on the basis of the following questions.

Is the subreddit active?
Does it relate to either the technical or social aspects of smart homes or devices?

Then, I utilized qualitative coding, a research method of categorizing data in order to extract themes, to find overarching patterns amongst users. In order to do this, I used Nvivo, a data analysis software, to code the collected data in accordance with a codebook I developed.

This codebook was intentionally divided into the social and technical issues that users noted throughout their discussions to allow for efficient categorization of the data.

By analyzing the frequency of users’ discussions in certain categories, I was able to extract the core issues users faced in order to conclude relevant findings. The goal throughout this process was to discover the main problems users experienced with smart home devices. By discovering these patterns, this research aims to understand users in order to develop optimized design principles for future smart device owners.

Data Visualization

Throughout the course of this project, Professor Karahalios emphasized the importance of telling a story through our data analysis.

My goal was to understand issues faced by users by creating visualizations to find and identify major patterns amongst user data. Utilizing Tableau, an interactive data visualization software, I created visualizations to model major thematic findings discovered in my qualitative coding.

First, I created pie charts to visualize the numerical categorization of the data for each of the social and technical issues faced by users. This visualization illustrates the portion of data that was coded to each socio-technical issue. This allows for a visualization of the prevalent issues faced by users as seen in our collected data.

In addition to the pie charts, I created bar charts to depict the socio-technical issues faced by users in 2020 and 2021. The purpose of this visualization was to see the effect of the pandemic on the most commonly encountered issues as well as how these issues progressed over a span of these years.
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Conclusion

After finalizing the qualitative coding and the data visualization, I created a graphic to illustrate the major findings. Throughout the course of the data analysis, I found that the most commonly faced issues among Smart Home device owner are as follows:

As depicted in the graphic, the main socio-technical issues users face are growing overwhelmed while integrating smart devices into their daily lives and homes, wanting more control over their devices, feeling apprehensive about device privacy and safety, and facing trouble while integrating multiple smart devices.

Through these findings, I concluded an overarching theme extracted from the data and user experiences: The increasing ubiquity of smart devices poses difficulties as individuals adopt more technological automation in their lives.‍

Key Takeaways

This project was my first experience delving into HCI research. I had the opportunity to contribute to this project and learn foundational research methods in addition to working alongside other members of this lab to learn about their projects and experiences. This research allowed me to exercise a different skillset from my previous work and school experiences and taught me more about academia and the field of HCI.

Here are some key takeaways I gained:

Research does not have instructions: Starting research after being focused on completing academic assignments was a stark change. I struggled not having instructions and often felt lost about what my next tasks would be. However, not having instructions allowed me to push my boundaries and explore new concepts and methods. When I ran into roadblocks, I learned how to shift my focus and try out new ways to work toward a solution.
Progress is not linear: During the course of this project, there were often spans in which there was a lot of progress and others where there was not. While this was sometimes frustrating, I learned that progress is not always linear. Instead, I realized research is an iterative process and that I could continue to make progress toward my goals throughout the ups and downs of the project.