Name
Abstract | ||
|---|---|---|
One of the key selling points of smart home devices is that they provide solutions tailored to our needs. Identifying this need, however, is not always trivial, especially when dealing with infants who are not yet able to express their wishes using clear words. In this paper, we present preliminary work on identifying infants' needs based on categorizing their crying behavior. Our solution is embedded in a smart crib system which is designed to support parents in better understanding their babies' sentiment. The high accuracy of our experimental results are promising. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00047 | 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech) |
Keywords | Field | DocType |
smart crib, sentiment analysis, support vector machine, system design, crying process | Sentiment analysis,Computer science,Server,Feature extraction,Home automation,Human–computer interaction,Software,Crying,Control system | Conference |
ISBN | Citations | PageRank |
978-1-5386-7519-9 | 0 | 0.34 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ying Liu | 1 | 13 | 3.25 |
| Dequan Zheng | 2 | 74 | 21.56 |
| Tongmao Lin | 3 | 0 | 0.34 |
| Xianqi Liu | 4 | 0 | 0.34 |
| Deshuai Wang | 5 | 1 | 1.03 |
| Frank Hopfgartner | 6 | 535 | 57.69 |