Temperature Monitoring System For Plant Factory Based On Multi-Sensor Data Fusion

DOI

10.2991/jimec-17.2017.107How to use a DOI?

Keywords

plant factory; multi-sensor; data fusion; dixon criterion; adaptive weighting

Abstract

For the problem of low accuracy of temperature monitoring system, this paper proposed a multi-sensor data fusion algorithm applied to plant factory temperature monitoring system. First, Dixon criterion was used to eliminate the gross error in the measurement data, then the temperature data fusion value and variance in each group were obtained through patch estimation fusion method based on the average value, and finally the adaptive weighted fusion was conducted on each group of sensor data in accordance with the optimal distribution principle of the weight to obtain accurate temperature value. Results showed that the algorithm had higher accuracy and smaller error than the traditional average method.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shigang Cui
AU  - Kun Liu
AU  - Xingli Wu
AU  - Yongli Zhang
AU  - Lin He
PY  - 2017/10
DA  - 2017/10
TI  - Temperature Monitoring System For Plant Factory Based On Multi-Sensor Data Fusion
BT  - Proceedings of the 2017 2nd Joint International Information Technology, Mechanical and Electronic Engineering Conference (JIMEC 2017)
PB  - Atlantis Press
SP  - 492
EP  - 495
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimec-17.2017.107
DO  - 10.2991/jimec-17.2017.107
ID  - Cui2017/10
ER  -