There has been an upsurge recently in investigating machine learning techniques for Activity Recognition (AR) problems as that have been very effective in extracting and learn-ing knowledge from the activity datasets. The ...

Occupancy detection helps enable various emerging smart environment applications ranging from opportunistic HVAC (heating, ventilation, and air-conditioning) control, effective meeting management, healthy social gathering, ...

Human activity recognition using multi-modal sensing technologies to automatically collect and classify daily activities has become an active field of research. Given the proliferation of smart and wearable devices and ...

Activity recognition has applications in a variety of human-in-the-loop settings such as smart home health monitoring, green building energy and occupancy management, intelligent transportation, and participatory sensing. ...

Twitter is an extremely popular micro-blogging social platform with millions of users, generating thousands of tweets per second. The huge amount of Twitter data inspire the researchers to explore the trending topics, event ...

Green building applications need to efficiently communicate fine-grained power consumption patterns of a wide variety of consumer-grade appliances for an effective adaptation and percolation of demand response models down ...

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 ...

Activity recognition in smart environment has been investigated rigorously in recent years. Researchers are enhancing the underlying activity discovery and recognition process by adding various dimensions and functionalities. ...

Dementia is a clinical syndrome of cognitive deficits that involves both memory and functional impairments. While disruptions in cognition is a striking feature of dementia, it is also closely coupled with changes in ...

The success and impact of activity recognition algorithms largely depends on the availability of the labeled training samples and adaptability of activity recognition models across various domains. In a new environment, ...