Player interaction with procedurally generated game play from crowd-sourced data

Sylvester Arnab; Mark Lewis; Alessandro Bogliolo; Lorenz Cuno Klopfenstein; Saverio Delpriori; Samantha Clarke

doi:10.1145/3341215.3356257

Player interaction with procedurally generated game play from crowd-sourced data

Sylvester Arnab
, Mark Lewis
, Alessandro Bogliolo
, Lorenz Cuno Klopfenstein
, Saverio Delpriori
, Samantha Clarke

University of Urbino

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

1 Citation (Scopus)

Abstract

This paper discusses the potential for player-data interaction enabled through the medium of gameplay that is procedurally generated using crowd-sourced data. A mobile game, which is called ‘Balance Trucks’ procedurally generates levels containing terrains derived from data collected through the SmartRoadSense (SRS) application. SRS allows data on the quality of roads to be collected via a user’s mobile device whilst driving along various routes, providing open data towards boosting traffic conditions in Europe. Data collected can then be used to unlock game levels and the subsequent terrains. The paper describes the development considerations and process, providing insights on the technical infrastructure that could be adopted and adapted for different types of data. The player-data interaction demonstrated by this game provides a new form of human-computer interaction from the perspective of games and crowd-sourced data that can inform future data-driven games and also the engagement strategy for other crowd-sourcing and sensing initiatives.

Original language	English
Title of host publication	CHI PLAY 2019 - Extended Abstracts of the Annual Symposium on Computer-Human Interaction in Play
Publisher	Association for Computing Machinery, Inc
Pages	333-339
Number of pages	7
ISBN (Electronic)	9781450368711
DOIs	https://doi.org/10.1145/3341215.3356257
Publication status	Published - 17 Oct 2019
Event	6th ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play - Barcelona, Spain Duration: 22 Oct 2019 → 25 Oct 2019 https://chiplay.acm.org/2019/

Conference

Conference	6th ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play
Abbreviated title	CHI PLAY 2019
Country/Territory	Spain
City	Barcelona
Period	22/10/19 → 25/10/19
Internet address	https://chiplay.acm.org/2019/

Funding

This project received funding from the European Union?s Horizon 2020 research and innovation programme under grant agreement No 687959, and the Disruptive Media Learning Lab, Coventry University, UK.

Keywords

Crowd-sourcing
Gamification
Mobile games
Procedural content generation
Smart sensing

ASJC Scopus subject areas

Human-Computer Interaction

Access to Document

10.1145/3341215.3356257

Cite this

Arnab, S., Lewis, M., Bogliolo, A., Klopfenstein, L. C., Delpriori, S., & Clarke, S. (2019). Player interaction with procedurally generated game play from crowd-sourced data. In CHI PLAY 2019 - Extended Abstracts of the Annual Symposium on Computer-Human Interaction in Play (pp. 333-339). Association for Computing Machinery, Inc. https://doi.org/10.1145/3341215.3356257

Player interaction with procedurally generated game play from crowd-sourced data. / Arnab, Sylvester; Lewis, Mark; Bogliolo, Alessandro et al.
CHI PLAY 2019 - Extended Abstracts of the Annual Symposium on Computer-Human Interaction in Play. Association for Computing Machinery, Inc, 2019. p. 333-339.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Arnab, S, Lewis, M, Bogliolo, A, Klopfenstein, LC, Delpriori, S & Clarke, S 2019, Player interaction with procedurally generated game play from crowd-sourced data. in CHI PLAY 2019 - Extended Abstracts of the Annual Symposium on Computer-Human Interaction in Play. Association for Computing Machinery, Inc, pp. 333-339, 6th ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play, Barcelona, Spain, 22/10/19. https://doi.org/10.1145/3341215.3356257

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Player interaction with procedurally generated game play from crowd-sourced data

Abstract

Conference

Funding

Keywords

ASJC Scopus subject areas

Access to Document

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