Resize, Remix, Regen: Frankensteining IoT Design Methods
Albrecht Kurze
Abstract
There are numerous IoT design methods. Previous research shows that all of them have their strengths, but also their limitations. None of them is a universal, all-purpose method. However, experts often view these methods as more versatile than their creators intended. Therefore, analyzing existing methods and tools, as well as rearranging and combining their approaches and components - just as Frankenstein did with his creature - offers the possibility of new creations that may be better than any single method previously. We present the idea and concept of "Frankensteining", which is based on the repeated application of IoT design methods in various contexts. We present a practical Frankensteining creation that was used in a workshop, our own methods, and a serial Frankensteining approach that was tested in an educational context. We conclude with a discussion on Frankensteining and invite other experts and practitioners to share their perspectives and experiences.
Create a lesson
Related papers
Calmables: Demonstrating Closed-Loop Infrared Earables for Thermal Biofeedback and Relaxation Support
Valeria Zitz, Michael Küttner, Jonas Hummel et al.
"Okay, I've Actually Softened My Take on This": How People in Decentralized Social Media Reason about the Appropriateness of Generative AI
Romina Mahinpei, Manoel Horta Ribeiro, Andrés Monroy-Hernández et al.
Integrating Flipped Learning and Generative AI for Practice-Based Design Education: Evidence from a Knit Yarn Design Course
Hong Qu, Zichao Ling, Yadie Yang
EasyFashion: A Human-AI Co-Creation System for Personalized Fashion Design and Sewing Pattern Generation
Hong Qu, Zhaoxiang Xu, Jinbo Luo et al.
Verify, Offload, Extend & Recommend: Selective Complementarity in AI Support for Physical Activity Planning with Longitudinal Patient Data
Pavithren V S Pakianathan, Rania Islambouli, Diogo Branco et al.
Building a Cultural Perspective on Doctor-Patient Conversations
Krithi Shailya, Siddharth D Jaiswal, Ashish Makani et al.