"What If Smart Homes Could See Our Homes?": Exploring DIY Smart Home Building Experiences with VLM-Based Camera Sensors

The advancement of Vision-Language Model (VLM) camera sensors, which enable autonomous understanding of household situations without user intervention, has the potential to completely transform the DIY smart home building experience. Will this simplify or complicate the DIY smart home process? Additionally, what features do users want to create using these sensors? To explore this, we conducted a three-week diary-based experience prototyping study with 12 participants. Participants recorded their daily activities, used GPT to analyze the images, and manually customized and tested smart home features based on the analysis. The study revealed three key findings: (1) participants' expectations for VLM camera-based smart homes, (2) the impact of VLM camera sensor characteristics on the DIY process, and (3) users' concerns. Through the findings of this study, we propose design implications to support the DIY smart home building process with VLM camera sensors, and discuss living with intelligence.

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Publication Details

Journal
ArXiv.org
Published
2025-03-04
DOI
https://doi.org/10.1145/3706598.25713265
Primary Topic
Impact of Light on Environment and Health
Type
article
Field-Weighted Citation Impact
0.00
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article

"What If Smart Homes Could See Our Homes?": Exploring DIY Smart Home Building Experiences with VLM-Based Camera Sensors

Sojeong Yun, Youn-kyung Lim
ArXiv.org
Impact of Light on Environment and Health
article

"What If Smart Homes Could See Our Homes?": Exploring DIY Smart Home Building Experiences with VLM-Based Camera Sensors

Sojeong Yun, Youn-kyung Lim
article en

Abstract

The advancement of Vision-Language Model (VLM) camera sensors, which enable autonomous understanding of household situations without user intervention, has the potential to completely transform the DIY smart home building experience. Will this simplify or complicate the DIY smart home process? Additionally, what features do users want to create using these sensors? To explore this, we conducted a three-week diary-based experience prototyping study with 12 participants. Participants recorded their daily activities, used GPT to analyze the images, and manually customized and tested smart home features based on the analysis. The study revealed three key findings: (1) participants' expectations for VLM camera-based smart homes, (2) the impact of VLM camera sensor characteristics on the DIY process, and (3) users' concerns. Through the findings of this study, we propose design implications to support the DIY smart home building process with VLM camera sensors, and discuss living with intelligence.

ArXiv.org
Openalex Percentile: Top 72%
Impact of Light on Environment and Health
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