Tracking and behavior augmented activity recognition for multiple inhabitants
We develop CACE (Constraints And Correlations mining Engine), a framework that significantly improves the recognition accuracy of complex daily activities in multi-inhabitant smarthomes. CACE views the implicit relationships between the activities of multiple people as an asset, and exploits such co...
Saved in:
Main Authors: | UL ALAM, Mohammad Arif, ROY, Nirmalya, MISRA, Archan |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2021
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/6907 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
CACE: Exploiting behavioral interactions for improved activity recognition in multi-inhabitant smart homes
by: Alam, Mohammad Arif Ul, et al.
Published: (2016) -
Infrastructure-Assisted Smartphone-based ADL Recognition in Multi-Inhabitant Smart Environments
by: ROY, Nirmalya, et al.
Published: (2013) -
An Energy Efficient Quality Adaptive Multi-Modal Sensor Framework for Context Recognition
by: ROY, Nirmalya, et al.
Published: (2011) -
Ontology-aided feature correlation for multi-modal urban sensing
by: MISRA, Archan, et al.
Published: (2016) -
Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments
by: ROY, Nirmalya, et al.
Published: (2016)