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https://doi.org/10.1145/374473...
Article . 2025 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2024
License: arXiv Non-Exclusive Distribution
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From Uncertainty to Innovation: Wearable Prototyping with ProtoBot

Authors: İhsan Ozan Yildirim; Cansu Çetin Er; Ege Keskin; Murat Kuscu; Oğuzhan Özcan;

From Uncertainty to Innovation: Wearable Prototyping with ProtoBot

Abstract

Despite AI advancements, individuals without software or hardware expertise still face barriers in designing wearable electronic devices due to the lack of code-free prototyping tools. To eliminate these barriers, we designed ProtoBot, leveraging large language models, and conducted a case study with four professionals from different disciplines through playful interaction. The study resulted in four unique wearable device concepts, with participants using Protobot to prototype selected components. From this experience, we learned that (1) uncertainty can be turned into a positive experience, (2) the ProtoBot should transform to reliably act as a guide, and (3) users need to adjust design parameters when interacting with the prototypes. Our work demonstrates, for the first time, the use of large language models in rapid prototyping of wearable electronics. We believe this approach will pioneer rapid prototyping without fear of uncertainties for people who want to develop both wearable prototypes and other products.

12 pages, 2 figures

Keywords

FOS: Computer and information sciences, Computer Science - Computers and Society, Computer Science - Programming Languages, Computers and Society (cs.CY), Computer Science - Human-Computer Interaction, FOS: Electrical engineering, electronic engineering, information engineering, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, Human-Computer Interaction (cs.HC), Programming Languages (cs.PL)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green