Real-time Error Detection Based on Time Series Prediction for Embedded Sensors (임베디드 센서를 위한 시계열 예측 기반 실시간 오류 검출 기법)

Hyung-Il Kim (김형일)

Real-time Error Detection Based on Time Series Prediction for Embedded Sensors

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2011, 16(12), pp.11~22
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science

Hyung-Il Kim ¹

¹나사렛대학교

Accredited

ABSTRACT

An embedded sensor is significantly influenced by its spatial environment, such as barriers or distance, through low power and signal strength. Due to these causes, noise data frequently occur in an embedded sensor. Because the information acquired from the embedded sensor exists in a time series, it is hard to detect an error which continuously takes place in the time series information on a realtime basis. In this paper, we proposes an error detection method based on time-series prediction that detects error signals of embedded sensors in real time in consideration of the physical characteristics of embedded devices. The error detection method based on time-series prediction proposed in this paper determines errors in generated embedded device signals using a stable distance function. When detecting errors by monitoring signals from an embedded device, the stable distance function can detect error signals effectively by applying error weight to the latest signals. When detecting errors by monitoring signals from an embedded device, the stable distance function can detect error signals effectively by applying error weight to the latest signals.

KEYWORDS

Embedded System, Sensor Network, Error Detection, Time Series

Citation status

* References for papers published after 2024 are currently being built.

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