CACE: Exploiting behavioral interactions for improved activity recognition in multi-inhabitant smart homes

• Main Authors: Alam, Mohammad Arif Ul, ROY, Nirmalya, MISRA, Archan, TAYLOR, Joseph
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: multi-modal sensing; multiple inhabitants; scalable activity recognizer; smart communities; Computer Sciences; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3581; https://ink.library.smu.edu.sg/context/sis_research/article/4582/viewcontent/CACE_2016_ICDS_afv.pdf
• Institution: Singapore Management University

We propose CACE (Constraints And Correlations mining Engine) which investigates the challenges of improving the recognition of complex daily activities in multi-inhabitant smart homes, by better exploiting the spatiotemporal relationships across the activities of different individuals. We first prop...