TY - GEN
T1 - The Impact of Digital Alarm Sound to Human Emotions
T2 - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
AU - Han, Wenhan
AU - Wang, Jiaqi
AU - Hu, Xiping
AU - Cai, Hanshu
AU - Cheng, Jun
AU - Ning, Zhaolong
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - In many people's daily life, alarm sounds play an important role, which reflects the fast paced life in the modern society. On most occasions, people uses alarm sounds to wake them up in the morning. Improper alarm sounds could make people feel terrible. In this paper, we mainly propose a smart alarm sound recommendation system and construct an application to study how alarm sounds can impact human emotions. The recommendation system is deployed on the cloud, working with smartphones to deliver smart alarm sounds by considering not only sleep patterns, but also context information such as weather. The designed system can recommend smart alarm sounds to users, orchestrate sensing data collected by multiple sensors on smartphones, and collaborate with cloud computing to recommend preferable alarm sounds. An application is developed to demonstrate system effectiveness, which consists of the fore-end on Android OS and the back-end on the cloud. Experiments demonstrate that our system can recommend smart alarm sounds to wake participants up in the morning and the participants give feedback about their emotional states. The results show the system can improve people's emotion states by about 14.57%, compared to traditional alarm sound delivery.
AB - In many people's daily life, alarm sounds play an important role, which reflects the fast paced life in the modern society. On most occasions, people uses alarm sounds to wake them up in the morning. Improper alarm sounds could make people feel terrible. In this paper, we mainly propose a smart alarm sound recommendation system and construct an application to study how alarm sounds can impact human emotions. The recommendation system is deployed on the cloud, working with smartphones to deliver smart alarm sounds by considering not only sleep patterns, but also context information such as weather. The designed system can recommend smart alarm sounds to users, orchestrate sensing data collected by multiple sensors on smartphones, and collaborate with cloud computing to recommend preferable alarm sounds. An application is developed to demonstrate system effectiveness, which consists of the fore-end on Android OS and the back-end on the cloud. Experiments demonstrate that our system can recommend smart alarm sounds to wake participants up in the morning and the participants give feedback about their emotional states. The results show the system can improve people's emotion states by about 14.57%, compared to traditional alarm sound delivery.
KW - Context-aware
KW - emotion
KW - smart alarm sound recommendation
UR - http://www.scopus.com/inward/record.url?scp=85062244354&partnerID=8YFLogxK
U2 - 10.1109/SMC.2018.00329
DO - 10.1109/SMC.2018.00329
M3 - Conference contribution
AN - SCOPUS:85062244354
T3 - Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
SP - 1903
EP - 1908
BT - Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 October 2018 through 10 October 2018
ER -
