Liu, Y., Zheng, D., Lin, T. et al. (3 more authors) (2018) Smart Crib Control System Based on Sentiment Analysis. In: 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). 16th Intl Conf on Dependable, Autonomic and Secure Computing, 12-15 Aug 2018, Athens, Greece. IEEE , pp. 222-227. ISBN 9781538675199
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 is promising.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Jul 2018 14:05 |
Last Modified: | 19 Dec 2022 13:49 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00047 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:132672 |