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Sensor Network - IOT
❯Predictive analytics for the behaviour and psycho-emotional conditions of eSports players using heterogeneous data and artificial intelligence
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Predictive analytics for the behaviour and psycho-emotional conditions of eSports players using heterogeneous data and artificial intelligence
For:
End usersGoal:
OtherProblem addressed
Predict psycho-emotional conditions of eSports players in particular game
scenarios based on collected heterogeneous data.
Scope of use case
Prediction of psycho-emotional conditions of eSports players. To form
predictions, we collect physiological data from wearables/video cameras/eye
trackers, game telemetry data from keyboard/mouse/demo files, and
environmental conditions followed by the application of machine learning
methods for the analysis of the collected data.
Description
eSports is organized video gaming where single players or
teams compete against each other with the aim of achieving
a specific goal by the end of the game. The eSports industry
has progressed considerably within the last decade: a huge
number of professional and amateur teams take part in
numerous competitions where the prize pools achieve tens
of millions of dollars USD. Its global audience has already
reached 380 million in 2018 and is expected to reach more
than 550 million in 2021. However, there is a lack of tools to
help assess the physiological and psycho-emotional
conditions of eSports players.
In this project, we collect three classes of data (physiological,
game telemetry, and environmental conditions) followed by
a data analysis using artificial intelligence based on machine
learning algorithms. For example, we apply machine learning
and recurrent neural networks with attention to assessing
player performance dynamics.
Sensor Network - IOT
AI: Perceive
Predictive analytics
sensor networks
Deep learning
AI: Understand