BeeMate the Game: A hunting treasure serious game for raising awareness and audience engagement in air pollution monitoring

The current paper presents a serious game approach to engage citizens in monitoring pollution, mainly in urban areas, and raise awareness regarding its effects in modern human lifestyle. A prototype mobile application is proposed, urging users to capture images showing polluting sources (e.g., traffic jams, trucks) and their audio footprint (if applicable) to assist in the process of monitoring air pollution. A deep learning algorithm is running in the backend of the application and is responsible for image and audio pattern recognition. The results of this module feed the application which in turn, is asking contributors to validate and further annotate the pollution sources identified by the image and audio recognition algorithms. A repository containing datasets with audiovisual content related to polluting sources’ footprints is gradually constructed and carefully annotated through crowd intelligence strategies. Spatiotemporal information that is extracted and related to the content itself also allows for indirect pollution monitoring. Gamification strategies are employed to reward players with scoring points according to the level of engagement and the quality of their contributions. Based on the achieved score, the application unlocks access to regional pollution monitoring maps, allowing users to check pollution levels in nearby areas, while also levels up different ranks (i.e., worker-bee, corporal-bee, sergeant-bee, lieutenant-bee, captain-bee, etc.). The ultimate goal of the proposed application is to identify those users who are willing to participate in dedicated pollution monitoring campaigns, using dedicated sensors and measurement protocols.