From Activity Recognition to Intention Recognition for Assisted Living Within Smart Homes
| dc.cclicence | CC-BY-ND | en |
| dc.contributor.author | Rafferty, Joseph | en |
| dc.contributor.author | Nugent, Chris | en |
| dc.contributor.author | Liu, Jun | en |
| dc.contributor.author | Chen, Liming | en |
| dc.date.acceptance | 2017-01-05 | en |
| dc.date.accessioned | 2017-03-08T09:47:00Z | |
| dc.date.available | 2017-03-08T09:47:00Z | |
| dc.date.issued | 2017-01-05 | |
| dc.description | The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. | en |
| dc.description.abstract | The global population is aging; projections show that by 2050, more than 20% of the population will be aged over 64. This will lead to an increase in aging related illness, a decrease in informal support, and ultimately issues with providing care for these individuals. Assistive smart homes provide a promising solution to some of these issues. Nevertheless, they currently have issues hindering their adoption. To help address some of these issues, this study introduces a novel approach to implementing assistive smart homes. The devised approach is based upon an intention recognition mechanism incorporated into an intelligent agent architecture. This approach is detailed and evaluated. Evaluation was performed across three scenarios. Scenario 1 involved a web interface, focusing on testing the intention recognition mechanism. Scenarios 2 and 3 involved retrofitting a home with sensors and providing assistance with activities over a period of 3 months. The average accuracy for these three scenarios was 100%, 64.4%, and 83.3%, respectively. Future will extend and further evaluate this approach by implementing advanced sensor-filtering rules and evaluating more complex activities. | en |
| dc.funder | N/A | en |
| dc.identifier.citation | Rafferty, J et al. (2017) From Activity Recognition to Intention Recognition for Assisted Living Within Smart Homes. IEEE Transactions on Human-Machine Systems, 47 (3), pp. 368-379 | en |
| dc.identifier.doi | https://doi.org/10.1109/THMS.2016.2641388 | |
| dc.identifier.issn | 2168-2291 | |
| dc.identifier.uri | http://hdl.handle.net/2086/13456 | |
| dc.peerreviewed | Yes | en |
| dc.projectid | N/A | en |
| dc.publisher | IEEE | en |
| dc.researchinstitute | Cyber Technology Institute (CTI) | en |
| dc.subject | Intelligent agents | en |
| dc.subject | Activity recognition | en |
| dc.subject | Smart homes | en |
| dc.subject | Hidden Markov models | en |
| dc.subject | Aging | en |
| dc.subject | Intelligent sensors | en |
| dc.title | From Activity Recognition to Intention Recognition for Assisted Living Within Smart Homes | en |
| dc.type | Article | en |