Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/59612

Non-personal Data Collection for Toy User Interfaces

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Item Summary

Title:Non-personal Data Collection for Toy User Interfaces
Authors:de Albuquerque, Anna Priscilla
Kelner, Judith
Keywords:Machine Learning, Robotic, and Toy Computing
Decision Analytics, Mobile Services, and Service Science
data collection, rapid prototyping, smart toys, toy user interfaces
Date Issued:08 Jan 2019
Abstract:Toy-user-interfaces (ToyUI) are computing devices or peripherals that leverage interactivity and connectivity with other devices to promote physical and social play. ToyUI products may collect both personal and non-personal data (NPD) on their users. We propose nine data patterns for NPD collection as part of ToyUI design based on the study of 297 ToyUI items from both the literature and industry. In addition, we introduce a printed circuit board (PCB) used for rapid prototyping that enabled NPD data collection concerning both objects and users by gathering non-personal identification, positioning system, and motion tracking. We demonstrate the effectiveness of our hardware architecture by embedding it into two design scenarios, namely, closed rules and open-ended rules solutions. The objectives here are to assist the ToyUI makers in creating more meaningful play experiences while ensuring the privacy of children’s and their parents’ data.
Pages/Duration:10 pages
URI/DOI:http://hdl.handle.net/10125/59612
ISBN:978-0-9981331-2-6
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Machine Learning, Robotic, and Toy Computing


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