IoT Based Greenhouse Condition Monitoring System for Chili Plant Growth

Over the last few years, most of greenhouses have been managed traditionally based on manpower to monitor and maintain the plants, such as watering, fertilizing, and using their skill in detecting plant diseases. Thus, this study focuses on developing a greenhouse monitoring system by using IoT tech...

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Bibliographic Details
Published in:Journal of Advanced Research in Applied Sciences and Engineering Technology
Main Author: Pandi M.S.M.; Seman R.; Saod A.H.M.; Ramlan S.A.; Harron N.A.; Abdullah M.H.; Soh Z.H.C.
Format: Article
Language:English
Published: Semarak Ilmu Publishing 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186918994&doi=10.37934%2faraset.41.1.142153&partnerID=40&md5=a87d7b9c076ac0c591692dd97ebeb206
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Summary:Over the last few years, most of greenhouses have been managed traditionally based on manpower to monitor and maintain the plants, such as watering, fertilizing, and using their skill in detecting plant diseases. Thus, this study focuses on developing a greenhouse monitoring system by using IoT technology. It aims to assist the local farmers in monitoring their greenhouse, instead of applying the conventional methods that are tedious and required more labour works. For data collection, parameters for chilli plants are measured using temperature and humidity sensors, soil moisture sensor, and light dependent resistor (LDR) sensor. The data are sent to microcontroller and transferred to the Ubidots cloud for the monitoring purpose. Watering pump and exhaust fan can be activated to control the plant parameters so that the plant remains in its normal condition. The sensor data are processed through classification using Support Vector Machine (SVM) to analyse the plant condition, whether the proposed method is suitable or not for the chilli plant to grow. Overall, a mini greenhouse prototype for chilli plant has been successfully constructed with a system interface on Ubidots dashboard to monitor the condition of the greenhouse plant. Results show that the developed system can be an alternative in monitoring the greenhouse condition with accuracy of 94.5%. © 2024, Semarak Ilmu Publishing. All rights reserved.
ISSN:24621943
DOI:10.37934/araset.41.1.142153