You are in : Home » Results & submissions » Select UOA » 15 - General Engineering » View submission: Coventry University » Outputs » Detail

Output details

15 - General Engineering

Coventry University

Return to search Previous output Next output

Output 29 of 67 in the submission

Article title

Edge mining the internet of things

Type

D - Journal article

DOI

10.1109/JSEN.2013.2266895

Title of journal

IEEE Sensors Journal

Article number

Volume number

Issue number

First page of article

3816

ISSN of journal

1530-437X

Year of publication

2013

URL

Number of additional authors

Additional information

The paper presents the theoretical foundation and practical exploration for using application knowledge to drastically reduce transmissions in wireless-sensor networks. It is the first approach of this sort to be generalised and demonstrated across slow-moving (temperature, humidity), fast-moving (accelerometer, audio) signals, and statistical summaries resulting from real-life deployments. It demonstrated delivery of 10-fold battery-life extension for several wireless sensing applications. Developed within £65,294 EPSRC/Orbit CASE (EP/H501134/1), the work led to and is exploited in the €7.8M FP7 STARGATE (no.314061, Dr. Mark Langley, Project Coordinator, Mark.Langley@meggitt.com) and was built into bespoke instrumentation for buildings (KTP008003, £300K) and vehicles (JLR, £106,000).

Interdisciplinary

Cross-referral requested

Research group

None

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract