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Type, Talk, or Swype: Characterizing and comparing energy consumption of mobile input modalities
- Source :
- Pervasive and Mobile Computing. 26:57-70
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- It is reported that mobile users spend most of their time on texting SMS, Social Networking, Emailing, or sending instant messaging (IM), all of which involve text input. There are three primary text input modalities, soft keyboard (SK), speech to text (STT) and Swype. Each one of them engages a different set of hardware and consequently consumes different amounts of battery energy. Using high-precision power measurement hardware and systematically taking into account the user context, we characterize and compare the energy consumption of these three input modalities. We find that the length of interaction, or the message length, determines the most energy efficient modality. For short interactions, less than 14-30 characters, SK is the most energy efficient. For longer interactions, however, STT significantly outperforms both SK and Swype. When message length distributions of popular text activities are considered, STT provides near optimal energy consumption without requiring the user to predict the message length and decide between SK and STT. In terms of battery life, the choice of input modality makes significant differences. If users always choose SK for all their text activities, they will consume nearly 50% of the phone battery each day. Choosing STT over SK can save 30%-40% of the battery depending on the choice of STT software.
- Subjects :
- Modality (human–computer interaction)
Computer Networks and Communications
business.industry
Computer science
Mobile computing
020206 networking & telecommunications
Context (language use)
02 engineering and technology
Energy consumption
Computer Science Applications
Software
Hardware and Architecture
Phone
Embedded system
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
business
Set (psychology)
Information Systems
Computer network
Efficient energy use
Subjects
Details
- ISSN :
- 15741192
- Volume :
- 26
- Database :
- OpenAIRE
- Journal :
- Pervasive and Mobile Computing
- Accession number :
- edsair.doi...........fbf62ba887613b9561f53bdf88da42df
- Full Text :
- https://doi.org/10.1016/j.pmcj.2015.10.010