IoT4Fun Rapid Prototyping Toolkit for Smart Toys

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 plugand-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. As a means to demonstrate adequacy with elicited requirements, in Section 3, we first compare IoT4Fun features with other RPTs from literature and industry [1,4,5,6,7,8,9,10,11,12]. In Section 4, we introduce IoT4Fun, a toolkit that combines embedded, modular, and plug-and-play approaches. The first approach aims to embed the same RPT into different physical toys. Modularity permits better distribution of the hardware components and allows creators to decide which modules are essential to their solutions. The plug-andplay approach offers a rapid and easy-to-use experience for the creators to manage the modules. IoT4Fun uses Printed-Circuit Board (PCB) manufacture to favor miniaturization and robustness. It collects real-time motion tracking information, supports wireless communication with devices, and contactless identification of objects or users. Besides, it offers visual, auditory, and tactile feedback and permits programming all play behaviors using Arduino IDE. In Section 5, we detail how a group of 27 graduate students embedded IoT4Fun into five smart toy prototypes. Students selected RPT modules that were suitable for their designs. Prototypes present a variety of shapes and sizes (e.g., a hula-hoop toy, a plush toy, a hand-sized cube, a large box, and a glove). Solutions either connect with mobile applications or with tagged objects, and programmed behaviors range from openended play to closed-rules. A total of 40 end-users (23 males/17 females) exhaustively tested the prototypes in playtesting sessions. In Section 6, we check for the