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Found 3 papers, 1 papers with code
Generative Resident Separation and Multi-label Classification for Multi-person Activity Recognition
This paper presents two models to address the problem of multi-person activity recognition using ambient sensors in a home.
Q-SMASH: Q-Learning-based Self-Adaptation of Human-Centered Internet of Things
As the number of Human-Centered Internet of Things (HCIoT) applications increases, the self-adaptation of its services and devices is becoming a fundamental requirement for addressing the uncertainties of the environment in decision-making processes.
SMASH: a Semantic-enabled Multi-agent Approach for Self-adaptation of Human-centered IoT
Nowadays, IoT devices have an enlarging scope of activities spanning from sensing, computing to acting and even more, learning, reasoning and planning.
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