Crowdsourcing Environment Data with Gamified Augmented Reality Mini-Games
: Laato, Samuli; Nummenmaa, Timo; Yoshida, Hironori; Chambers, Philip; Uhlgren, Ville-Veikko; Hu, Botao Amber; Kordyaka, Bastian; Hamari, Juho
Publisher: Association for Computing Machinery (ACM)
: 2025
: Proceedings of the ACM on Human-Computer Interaction
: GAMES009
: 9
: 6
: 253
: 276
: 2573-0142
DOI: https://doi.org/10.1145/3748604
: https://doi.org/10.1145/3748604
: https://research.utu.fi/converis/portal/detail/Publication/504987355
Remote sensing for observing and recording our surroundings is becoming mainstream. Technologies, such as light, detection, and ranging (LiDAR), are now part of consumer mobile devices and provide a variety of novel interaction opportunities with the environment. Mobile remote sensing also provides affordances for crowdsourcing through location-based applications such as games and gamified systems. While such use cases today are technologically feasible, there is a lack of understanding of how and what kinds of interactions and applications would be both (1) engaging and motivating for users and also (2) maximize the volume and quality of the data being gathered. In this study, we investigate these challenges by developing and testing four gamified augmented reality prototypes that use LiDAR for collecting point cloud data during location-based gaming. Through field testing, interviews, and surveys with 21 participants, followed by reflexive thematic analysis, we identified five themes of dynamics, which exemplify tensions and challenges to designing gamified AR crowdsourcing. The findings primarily point to hazards in design that may undermine user motivation as well as constraints of the environments themselves in facilitating and affording meaningful and rich (gameful) interaction.
:
This work was supported by the Research Council of Finland’s Flagship Programme UNITE (decisions 357906 and 357907) and the Research Council of Finland-funded GamiLiDAR project (decisions 359472 and 359473).
UTU Research Portal