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Data Privacy and Security with Smart Home Devices

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Project Overview

Improvement to transparency and privacy for smart home device applications requires ease of accessing information. To develop a solution to this problem, we conducted user interviews, consulted with an expert, and analyzed data. The final product is a culmination of our research and process that resulted in user-centered solutions to data privacy and security for smart home devices.

Timeline
Fall 2021
4 weeks

Tools
Figma

Skills
User Interviews, Problem Solving

Collaborators
Spoorthi Cherivirala, Shannon Lin, Anthony Pan

Role
User Interviews, Data Analysis, Solution Development, Icon creation

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Process

​Problem Space

​There is an increasing stigma of data collection and security for smart home devices that stems from lack of clear communication of privacy policies. ​When users don't understand how their data is handled, mistrust occurs and can cause unnecessary discontinued use of the device.

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Research Methods

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Audience

  • College Students

  • Older generation

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Qualitative

  • User Interviews

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Quantitative

  • Survey Results

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Qualitative Data

Interviewed a field expert and eight student users.

Key Insights:

  • Paradox​ between personalization and information privacy

  • Less privacy concern for younger users

  • Unawareness of privacy policies

  • Smart Home device user perspective

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Quantitative Data

Language data from user interviews was analyzed to understand the confidence of knowledge and survey data was used to gain a general consensus of smart home skepticism.
 

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User Centered Solution 01

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Increasing awareness about existing smart home device features regarding data security and privacy
 

  • Most users don't know all of the smart home device's capabilities 

  • Low overhead cost build on existing features and solutions

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User Centered Solution 02

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Redesign the UI of the accompanying smart home device app for clarity, organization, and information flow.
 

  • Prevents confusion and increases user confidence of understanding the device

  • Make customizing data privacy options easier 

  • Increase accessibility of the device and app UI

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Assumptions and Weaknesses

A main weakness of our research and solutions was caused by a small and specific sample size of user data. 
 

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Design Principles

During the process of researching and problem solving, we mainly utilized three design principles: mental models, personas, and Ockham's razor.
 

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