AWARE: Mobile Context Instrumentation Framework

By Denzil Ferreira, Vassilis Kostakos, Anind K. Dey. Frontiers in ICT, 2015

416 citations recorded by the source corpus.

We present a mobile instrumentation toolkit, AWARE, an open-source effort to develop an extensible and reusable platform for capturing, inferring, and generating context on mobile devices. Mobile phones are sensor-rich but resource-constrained, and therefore several considerations need to be addressed when creating a research tool that ensures problem-free context collection. We demonstrate how AWARE can mitigate researchers’ effort when building mobile data-logging tools and context-aware applications, with minimal battery impact. By encapsulating implementation details of sensor data retrieval and exposing the sensed context as higher-level abstractions, AWARE shifts the focus from software development to data analysis, both quantitative and qualitative. We have evaluated AWARE in several case studies and discuss its use, power consumption, and scalability.

Subfields: Computer Networks and Communications, Computer Science Applications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/7abc97950a1f6bc66af7a092b292aa0d917d46f2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. N. van Berkel
2. Vassilis Kostakos
3. Denzil Ferreira

In Computer Science Applications

1. N. van Berkel
2. Vassilis Kostakos
3. Denzil Ferreira

In Computer Vision and Pattern Recognition

1. N. van Berkel
2. Vassilis Kostakos
3. Denzil Ferreira

Citations in the corpus

• The Experience Sampling Method on Mobile Devices (2017, methodology): “In the current smartphone era, freely available software packages (e.g., AWARE (Ferreira et al .”