Mobile crowdsourcing based context-aware smart alarm sound for smart living

Jiaqi Wang; Yanxiang Guo; Wenhan Han; Jianbo Zheng; Hong Peng; Xiping Hu; Jun Cheng

doi:10.1016/j.pmcj.2019.02.003

Mobile crowdsourcing based context-aware smart alarm sound for smart living

Jiaqi Wang, Yanxiang Guo, Wenhan Han, Jianbo Zheng, Hong Peng^*, Xiping Hu, Jun Cheng

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

Alarm sounds are acknowledged to play an important role in daily life; however, sometimes improper alarm sounds may mess things up. In this paper, we construct a smart alarm sound recommendation system working with smartphones to deliver smart alarm sounds by considering not only specified information, such as sleep patterns, but also context information such as weather, and social information. Our system aims to provide a smart life through orchestrating sensing data collected by multiple sensors on smartphones and collaborating with cloud computing to recommend preferable alarm sounds. To demonstrate the effectiveness and efficiency of our system, we conduct experiments of using our system to recommend smart alarm sounds to wake people up in the morning. Experimental results show that our system can improve people emotional states by about 10.73%, compared to traditional alarm sound delivery methods.

Original language	English
Pages (from-to)	32-44
Number of pages	13
Journal	Pervasive and Mobile Computing
Volume	55
DOIs	https://doi.org/10.1016/j.pmcj.2019.02.003
Publication status	Published - Apr 2019
Externally published	Yes

Keywords

Context-aware
Mobile crowdsourcing
Smart alarm sound recommendation
Social-aware

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10.1016/j.pmcj.2019.02.003

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title = "Mobile crowdsourcing based context-aware smart alarm sound for smart living",

abstract = "Alarm sounds are acknowledged to play an important role in daily life; however, sometimes improper alarm sounds may mess things up. In this paper, we construct a smart alarm sound recommendation system working with smartphones to deliver smart alarm sounds by considering not only specified information, such as sleep patterns, but also context information such as weather, and social information. Our system aims to provide a smart life through orchestrating sensing data collected by multiple sensors on smartphones and collaborating with cloud computing to recommend preferable alarm sounds. To demonstrate the effectiveness and efficiency of our system, we conduct experiments of using our system to recommend smart alarm sounds to wake people up in the morning. Experimental results show that our system can improve people emotional states by about 10.73%, compared to traditional alarm sound delivery methods.",

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AU - Wang, Jiaqi

AU - Guo, Yanxiang

AU - Han, Wenhan

AU - Zheng, Jianbo

AU - Peng, Hong

AU - Hu, Xiping

AU - Cheng, Jun

PY - 2019/4

Y1 - 2019/4

N2 - Alarm sounds are acknowledged to play an important role in daily life; however, sometimes improper alarm sounds may mess things up. In this paper, we construct a smart alarm sound recommendation system working with smartphones to deliver smart alarm sounds by considering not only specified information, such as sleep patterns, but also context information such as weather, and social information. Our system aims to provide a smart life through orchestrating sensing data collected by multiple sensors on smartphones and collaborating with cloud computing to recommend preferable alarm sounds. To demonstrate the effectiveness and efficiency of our system, we conduct experiments of using our system to recommend smart alarm sounds to wake people up in the morning. Experimental results show that our system can improve people emotional states by about 10.73%, compared to traditional alarm sound delivery methods.

AB - Alarm sounds are acknowledged to play an important role in daily life; however, sometimes improper alarm sounds may mess things up. In this paper, we construct a smart alarm sound recommendation system working with smartphones to deliver smart alarm sounds by considering not only specified information, such as sleep patterns, but also context information such as weather, and social information. Our system aims to provide a smart life through orchestrating sensing data collected by multiple sensors on smartphones and collaborating with cloud computing to recommend preferable alarm sounds. To demonstrate the effectiveness and efficiency of our system, we conduct experiments of using our system to recommend smart alarm sounds to wake people up in the morning. Experimental results show that our system can improve people emotional states by about 10.73%, compared to traditional alarm sound delivery methods.

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KW - Smart alarm sound recommendation

KW - Social-aware

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Mobile crowdsourcing based context-aware smart alarm sound for smart living

Abstract

Keywords

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