An Automated Monitoring System for Controlled Greenhouse Horticulture

verfasst von

Matthias Becker, Kinwoon Yeow

Abstract

In the field of controlled horticulture, various methods have been studied to facilitate the environmental data retrieval. One of the great findings in this research is the attraction of insect’s behaviour towards the LED lighting of various wavelengths. Previous research shows promising results using LED based insect traps for insect population estimation in greenhouses. Therefore, an automated monitoring system is proposed as a standardization tool for environmental data gathering and estimation of pest population in controlled horticulture settings. The proposed automated monitoring system integrates object recognition models (combination of YOLOv3 and SVM) that identify and classify the pest and beneficial population density. The proposed system provides informative output via a mobile application. As a result, the proposed system functions as an integrated IoT management tool that simplifies the information retrieval process.

Organisationseinheit(en)

Fachgebiet Mensch-Computer-Interaktion

Typ

Aufsatz in Konferenzband

Seiten

75-85

Anzahl der Seiten

11

Publikationsdatum

07.02.2025

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Allgemeine Entscheidungswissenschaften, Allgemeine Computerwissenschaft

Elektronische Version(en)

https://doi.org/10.1007/978-981-97-7419-7_7 (Zugang: Geschlossen)