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.
A review of video-based human activity recognition: theory, methods and applications
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.DC 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
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.