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PreventDark:Automatically detecting and preventing problematic use of smartphones in darkness

Authors :
Ruan, Wenjie
Sheng, Quan Z.
Yao, Lina
Tran, Nguyen Khoi
Yang, Yu Chieh
Ruan, Wenjie
Sheng, Quan Z.
Yao, Lina
Tran, Nguyen Khoi
Yang, Yu Chieh
Publication Year :
2016

Abstract

Smartphone adoption has increased significantly and users can access the Internet, communicate, and entertain themselves anywhere and anytime. However, the negative aspects of smartphone overuse on young adults are being increasingly recognized recently. One such serious problematic usage is peering at brightly lit screens in dark, which can cause sleep loss and resultant health problems. In this paper, we investigate the potential of exploiting sensors embedded in smartphones to detect and prevent such unhealthy habit by measuring the ambient light intensity and detecting the smartphone motion. We implement our system through an Android APP, called PreventDark. We show the feasibility and accuracy of our developed system by experiments on different android smartphones. Field experimental results indicate our system can significantly prevent and decrease the problematic use after intervention with up to 93.6%, particularly in the dark residential environments.

Details

Database :
OAIster
Notes :
Ruan, Wenjie and Sheng, Quan Z. and Yao, Lina and Tran, Nguyen Khoi and Yang, Yu Chieh (2016) PreventDark:Automatically detecting and preventing problematic use of smartphones in darkness. In: 2016 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2016. IEEE, AUS, pp. 1-3. ISBN 9781509019410
Publication Type :
Electronic Resource
Accession number :
edsoai.on1125009206
Document Type :
Electronic Resource