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IoT4Fun Rapid Prototyping Toolkit for Smart Toys

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Title:IoT4Fun Rapid Prototyping Toolkit for Smart Toys
Authors:De Albuquerque, Anna Priscilla
Kelner, Judith
Dias Nogueira, Thiago
Silva Rocha Junior, Railton
Keywords:Machine Learning, Robotic, and Toy Computing
battery consumption
hardware requirements
internet of things
rapid prototyping
show 1 moresmart toys
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Date Issued:07 Jan 2020
Abstract:Rapid prototyping tools turn the design of smart toys faster and easier for creative teams. Appropriate tools for smart toys should meet a list of requirements, which include distributed data collection and adaptability for assorted toy shapes and size. The IoT4Fun toolkit innovates by mixing the embedded, modular, and plug-and-play approaches. It supports motion tracking data, wireless communication, and contactless identification. IoT4Fun demonstrates its effectiveness to design a variety of smart toy solutions by fitting into a hula-hoop toy until spherical, cubic, and wearable shapes. Solutions connect with either mobile applications or other toys and play rules range from open-ended to closed behaviors. End-users exhaustively tested developed solutions, and technical assessment evaluates their integrity after playtesting sessions. Results show comparative data on battery consumption and vulnerabilities threats for data security and privacy of each design. Future versions of IoT4Fun can benefit from miniaturization, robustness, and reliability improvements.
Pages/Duration:10 pages
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections: Machine Learning, Robotic, and Toy Computing

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