PoHAR enables distributed air quality sensor networks to collaboratively detect hyperlocal indoor activities with 97.41% accuracy using conflict-free data replication, hierarchical clustering, and off-the-shelf ML classifiers on resource-constrained devices.
Skelformer: An adaptive hierar- chical transformer-based approach on skeleton graphs for human action recognition in video sequences
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PoHAR: Understanding Hyperlocal Human Activities with Pollution Sensor Networks
PoHAR enables distributed air quality sensor networks to collaboratively detect hyperlocal indoor activities with 97.41% accuracy using conflict-free data replication, hierarchical clustering, and off-the-shelf ML classifiers on resource-constrained devices.