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Location Optimization Model of a Greenhouse Sensor Based on Multisource Data Fusion

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  • DianJu Qiao
  • ZhenWei Zhang
  • FangHao Liu
  • Bo Sun

Abstract

In the traditional case, the uncertainty of the ambient temperature measured by the experiential distributed sensor is considered. In this paper, a model based on the moving least square method in the fusion algorithm is proposed to study the optimal monitoring point of the sensor in the greenhouse and determine the most suitable installation position of the sensor in the greenhouse to improve the control effect of the temperature control device of the system. MATLAB simulation software is used to simulate each working condition of the greenhouse. Temperature data measured at 15 locations in the greenhouse were used to evaluate all possible combinations of monitoring locations and to estimate the optimal location for indoor temperature sensors. Compared with the traditional method, the error is reduced to 0.373, and the data are more accurate.

Suggested Citation

  • DianJu Qiao & ZhenWei Zhang & FangHao Liu & Bo Sun, 2022. "Location Optimization Model of a Greenhouse Sensor Based on Multisource Data Fusion," Complexity, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:complx:v:2022:y:2022:i:1:n:3258549
    DOI: 10.1155/2022/3258549
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    1. Mirzaee, Farshid & Solhi, Erfan & Naserifar, Shiva, 2021. "Approximate solution of stochastic Volterra integro-differential equations by using moving least squares scheme and spectral collocation method," Applied Mathematics and Computation, Elsevier, vol. 410(C).
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