SERENUS: Alleviating Low-Battery Anxiety Through Real-time, Accurate, and User-Friendly Energy Consumption Prediction of Mobile Applications

要旨

Low-battery anxiety has emerged as a result of growing dependence on mobile devices, where the anxiety arises when the battery level runs low. While battery life can be extended through power-efficient hardware and software optimization techniques, low-battery anxiety will remain a phenomenon as long as mobile devices rely on batteries. In this paper, we investigate how an accurate real-time energy consumption prediction at the application-level can improve the user experience in low-battery situations. We present Serenus, a mobile system framework specifically tailored to predict the energy consumption of each mobile application and present the prediction in a user-friendly manner. We conducted user studies using Serenus to verify that highly accurate energy consumption predictions can effectively alleviate low-battery anxiety by assisting users in planning their application usage based on the remaining battery life. We summarize requirements to mitigate users’ anxiety, guiding the design of future mobile system frameworks.

著者
Sera Lee
KAIST, Daejeon, Korea, Republic of
Dae R. Jeong
KAIST, Daejeon, Korea, Republic of
Junyoung Choi
KAIST, Daejeon, Korea, Republic of
Jaeheon Kwak
KAIST, Daejeon, Korea, Republic of
Seoyun Son
KAIST, Daejeon, Korea, Republic of
Jean Y. Song
DGIST, Daegu, Korea, Republic of
Insik Shin
KAIST, Daejeon, Korea, Republic of
論文URL

https://doi.org/10.1145/3654777.3676437

動画

会議: UIST 2024

ACM Symposium on User Interface Software and Technology

セッション: 3. AI & Automation

Westin: Allegheny 3
4 件の発表
2024-10-15 19:40:00
2024-10-15 20:40:00