Article

Abstract

• We demonstrate the feasibility of constructing a novel and practical real-world mobile cloud system, called myBlackBox, that efficiently fuses multimodal smartphone sensor data to identify and log unusual personal events in mobile users' daily lives. The system incorporates a hybrid architectural design that combines unsupervised classification of audio, accelerometer and location data with supervised joint fusion classification to achieve high accuracy, customization, convenience and scalability. We show the feasibility of myBlackBox by implementing and evaluating this end-to-end system that combines Android smartphones with cloud servers, deployed for 15 users over a one-month period.

Creator

• Han, Richard
• Ahn, Junho

Date Issued

• 2016-05-23

Academic Affiliation

• Computer Science

Journal Title

• Sensors

Journal Issue/Number

• 5

Journal Volume

• 16

File Extent

• 31708-31708

Editor

• Xue-Bo Jin

Subject

• blackbox
• unusual event
• mobile user
• fusion
• behavior pattern

Zuletzt geändert

• 2019-12-06

Identifier

• PubMed ID: 27223292

Resource Type

• Article

Urheberrechts-Erklärung

• In Copyright

DOI

•  https://doi.org/10.3390/s16050753

ISSN

• 1424-8220

Language

• English [eng]

Beziehungen

Artikel

Miniaturansicht	Titel	Datum Hochgeladen	Sichtbarkeit	Aktionen
	myblackboxBlackboxMobileCloudSystemsForPersonalizedUnusua.pdf	2019-12-06	Öffentlichkeit	Herunterladen