Context Inference for Mobile Applications in the UPCASE Project

• Type: Article in International Conference Proceedings Book
• Date: 2009

Authors

Santos, AC (Author) Other; Tarrataca, L (Author) Other; João M. P. Cardoso (Author) FEUP; Ferreira, DR (Author) Other; Diniz, PC (Author) Other; Chainho, P (Author) Other

Conference proceedings International

Title: MOBILE WIRELESS MIDDLEWARE, OPERATING SYSTEMS, AND APPLICATIONS

Pages: 352-365

2nd International Mobilware Conference

Berlin, GERMANY, APR 28-29, 2009

Indexing

ISI Web of Knowledge - 11 Citations

Scopus - 17 Citations

Other information

Authenticus ID: P-003-RBS

DOI: 10.1007/978-3-642-01802-2_26

Abstract (EN): The growing processing capabilities of mobile devices coupled with portable and wearable sensors have enabled the development of context-aware services tailored to the user environment and its daily activities. The problem of determining the user context at each particular point in time is one of the main challenges in this area. In this paper, we describe the approach pursued in the UPCASE project, which makes use of sensors available in the mobile device as well as sensors externally connected via Bluetooth. We describe the system architecture from raw data acquisition to feature extraction and context inference. As a proof of concept, the inference of contexts is based on a decision tree to learn and identify contexts automatically and dynamically at runtime. Preliminary results suggest that this is a promising approach for context inference in several application scenarios.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14