Browse By Repository:

 
 
 
   

Development of remote monitoring system using IoT system for greenhouse (G-REM)

Salzazary, Muhammad Syahmi (2024) Development of remote monitoring system using IoT system for greenhouse (G-REM). Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

[img] Text (Full Text)
Development of remote monitoring system using IoT system for greenhouse (G-REM).pdf - Submitted Version

Download (3MB)

Abstract

In this era of globalization, technology is one of the best initiatives to improve the quality of an agriculture-based especially greenhouse-based product. As globalization continues to connect markets and worldwide consumers, utilizing technology will be crucial for maximizing sustainable and efficient greenhouse systems. Moreover, the main challenge that the Malaysian industry faces is to have proficient workers with specific skills in agriculture products. Based on their expertise, skills, and dedication, will play a vital role in ensuring the success of growth in the agriculture industry and ensuring it is always of high quality. It also maximizes productivity in any greenhouse area. The objective of this project is to develop an application of a greenhouse system for the agriculture industry based on mobile development, to monitor the concentration of reproduction parameters integrated with machine learning development to predict the condition of greenhouse planting. Also, to analyze the performance of a greenhouse system by a specific planting structure in the agriculture industry. This hydroponic development system used Android Studio software to develop mobile applications that involve specific elements to support the implementation of the entire greenhouse process. Additionally, by integrating machine learning, this system has a wide range of built-in applications that have the capability of collecting, exchanging, and analyzing data from specific crops, especially for low-crop greenhouse plants. This includes a user interface, image processing, and data analytics which can improve the efficiency of various aspects of the agriculture industry. Overall, this project introduces a user-friendly system that can be operated in real-time situations for all agriculturalists and can lead to advancement for specific greenhouse plant growth

Item Type: Final Year Project (Project Report)
Uncontrolled Keywords: Greenhouse, Argriculture, Deep learning, Machine learning, Application
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Library > Final Year Project > FTKE
Depositing User: Norfaradilla Idayu Ab. Ghafar
Date Deposited: 19 Nov 2024 07:46
Last Modified: 19 Nov 2024 07:46
URI: http://digitalcollection.utem.edu.my/id/eprint/32405

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year