Detection of Untrustworthy IoT Measurements Using Expert Knowledge of Their Joint Distribution. / Nouretdinov, Ilia; Darwish, Salaheddin; Wolthusen, Stephen.

16th International Conference On Smart homes and health Telematics (ICOST'2018). Springer, 2018. p. 310-316 (Lecture Notes in Computer Science).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

E-pub ahead of print

Documents

Links

Abstract

The aim of this work is to discuss abnormality detection and explanation challenges motivated by Medical Internet of Things. First, any feature is a measurement taken by a sensor at a time moment, so abnormality detection also becomes a sequential process. Second, an anomaly detection process could not rely on having a large collection of data records, but instead there is a knowledge provided by the experts.
Original languageEnglish
Title of host publication16th International Conference On Smart homes and health Telematics (ICOST'2018)
PublisherSpringer
Pages310-316
Number of pages7
DOIs
StateE-pub ahead of print - 19 Jun 2018
Event16th International Conference On Smart homes and health Telematics: ICOST - Singapore
Duration: 10 Jul 201812 Jul 2018
http://www.icostconference.org/

Publication series

NameLecture Notes in Computer Science

Conference

Conference16th International Conference On Smart homes and health Telematics
Period10/07/1812/07/18
Internet address
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 29918646