An Automated Monitoring System for Controlled Greenhouse Horticulture

EasyChair Preprint 15187

Abstract

In the field of controlled horticulture, various methods have been studied to facilitate the environmental data retrieval. One of the great finding in this research is the attraction of insect's behavior towards the LED lighting of various wavelengths. Previous research show LED wavelength provides positive results in greenhouse environment population estimation. Therefore, an automated monitoring system is proposed as a standardization tool for environmental data gathering and estimation of pest population in the controlled horticulture envi- ronment. The proposed automated monitoring system integrates object recognition models (combination of YOLOv3 and SVM) that identify and classify the pest and benecial population density. The proposed system provides informative output via mobile application. As a result, the proposed system functions as an integrated IoT management tool that simplies information retrieval process.

Keyphrases: Decision Support System, Entomological Analysis, model evaluation, stochastic system

@booklet{EasyChair:15187,
  author    = {Matthias Becker and Kin-Woon Yeow},
  title     = {An Automated Monitoring System for Controlled Greenhouse Horticulture},
  howpublished = {EasyChair Preprint 15187},
  year      = {EasyChair, 2024}}