Home // SENSORCOMM 2018, The Twelfth International Conference on Sensor Technologies and Applications // View article

Event Detection Using Abductive Reasoning on Sensor Data

Authors:
Bill Karakostas

Keywords: sensor data fusion, event detection, abductive reasoning, Raspberry Pi

Abstract:
We present an approach that detects physical events such as a fire or an explosion using sensor data fusion, where not all relevant signals describing the event are available due to non-presence or malfunctioning of some types of sensors. We employ abductive probabilistic reasoning to detect the occurrence of an event amongst several alternative events from imperfect sensor data. Influenced by Dempster-Shafer’s evidence theory, we reason on the available evidence produced by the sensor data, combined with counterevidence to establish degrees of confidence to the different hypotheses made about the occurrence of an event. The paper also describes an experimental sensor setup for detection of fire and explosion events, and its effectiveness in terms of false negative and false positive detection rates.

Pages: 6 to 10

Copyright: Copyright (c) IARIA, 2018

Publication date: September 16, 2018

Published in: conference

ISSN: 2308-4405

ISBN: 978-1-61208-659-0

Location: Venice, Italy

Dates: from September 16, 2018 to September 20, 2018