2006 IEEE/RSJ International Conference on Intelligent Robots and Systems 2006
DOI: 10.1109/iros.2006.282284
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Adapting Playgrounds for Children's Play using Ambient Playware

Abstract: This paper presents an approach on how to adapt playgrounds using artificial neural networks (ANN). The playground consists of small tiles each capable of outputting coloured light, sensing force applied on them and communicating with neighbouring tiles. It is shown that a child's behaviour on the playground can be classified within eight categories by an ANN inputting the child's perception of the playground and the corresponding action performed; thus, enabling the playground to adapt real-time according to … Show more

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Cited by 14 publications
(22 citation statements)
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“…Feedback and multimodal feedback are introduced below. We have shown in more then one case [29,30] that using modular interactive tiles enabled us to detect user characteristics and adapt software execution to those. In further tests, we found that by capturing a user's conditional attitude and adapting software execution to this that, in some cases, we could eventually modify user behavior itself [30].…”
Section: Adaptive Interactivitymentioning
confidence: 99%
“…Feedback and multimodal feedback are introduced below. We have shown in more then one case [29,30] that using modular interactive tiles enabled us to detect user characteristics and adapt software execution to those. In further tests, we found that by capturing a user's conditional attitude and adapting software execution to this that, in some cases, we could eventually modify user behavior itself [30].…”
Section: Adaptive Interactivitymentioning
confidence: 99%
“…Digital and mixed reality games allow for interventions in the game state, game difficulty, or game behavior. Personalized adaptation of the interventions allows people with different skills to play together, increasing fairness and engagement in a fun and challenging experience [30,64].…”
Section: Steering Behavior In the Itpmentioning
confidence: 99%
“…Derakhshan et al presented an interac-tive playground that consisted of tiles that children could step on and interact with through force sensors and LEDs [70]. They used neural networks to learn and model different types of game styles, such as fast, slow, or continuous.…”
Section: Physical Activitymentioning
confidence: 99%
“…This can be achieved by developing models that reflect the player's behavior or preferences. Derakhshan et al used a platform that could recognize several player styles based on tempo, age and continuity of play [70]. The tempo of the game was adapted, along with other characteristics, to match what the player felt comfortable with to successfully promote physical activity.…”
Section: Game Mechanics Adaptationmentioning
confidence: 99%
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