Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2927
Title: Internet of Things (IoT) Approach to Detect and Modelling Fusarium Wilt Disease on Banana
Authors: Muhammad Akmal Mohd Zawawi 
Marinah Muhammad 
Laila Naher 
Nurul Syaza Abdul Latif 
Mohd Fauzie Jusoh 
Issue Date: Dec-2021
Publisher: UMK
Abstract: 
The continuing development of Internet of Things (IoT) is becoming progressively important in agriculture activities including plant disease identification. Consequently, the IoT technology will act as a game-changer in plant disease identification from manual to automated detecting plant disease. In ancient farming, most plant diseases identification were conducted manually based on the external symptoms which only can be done by experienced people and require more manpower to monitor the farms. Thus, this scenario brings difficulty for young or inexperienced farmers to identify the plant disease. This paper describes the development of IoT technology for detecting Fusarium wilt disease in bananas at the early stage of disease infestation under the greenhouse environment. Sensors will be equipped inside the greenhouse with microcontrollers, communication networks, and suitable protocols to capture soil parameters such as soil moisture content, pH, electrical conductivity (EC), and temperature. Then, all the measured data will be stored and managed properly using Thingspeak. To better understand the association of soil parameters with Fusarium wilt disease, a mathematical modelling will be done to simulate the disease progression using output data. As a result, this study will give insightful real-time data monitoring using IoT technology to determine the threshold of favourable soil conditions for Fusarium wilt disease occurrence.
Description: 
Others
URI: http://hdl.handle.net/123456789/2927
ISBN: 987-967-2912-88-0
Appears in Collections:Faculty of Agro Based Industry - Other publication

Files in This Item:
File Description SizeFormat
E-proceeding syposium.pdf791.05 kBAdobe PDFView/Open
Show full item record

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.