Study and Implementation of Data Mining in Urban Gardening

Mohana, Muniandy and Lee, Eu Vern (2019) Study and Implementation of Data Mining in Urban Gardening. INTI JOURNAL, 2019 (36). ISSN e2600-7320

Text ij2019_36.pdf - Updated Version Available under License Creative Commons Attribution. Download (348kB)

Abstract

The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. Linking of these platforms are through a five-step process – monitoring, recording, processing, optimising, and reporting. The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. This information is then utilised to optimise the automated plant-caregiving features that the system contains, which are irrigation and sunlight through LED grow lights. Feedback given to the user to inform them of methods by which they can improve their plant’s health condition, derived through the information generated from the data-mining module. A user can then remotely monitor and care for their plants. The major caregiving tasks of the plants in this system is automated and its users are equipped with a powerful tool that informs and educates them on the conditions of their plant, providing them with information that aids with improvement of the plants’ health conditions

Item Type:	Article
Uncontrolled Keywords:	Urban gardening, data mining, learned irrigation
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Information Technology
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	19 Nov 2019 03:56
Last Modified:	17 Apr 2024 06:04
URI:	http://eprints.intimal.edu.my/id/eprint/1309

Actions (login required)

View Item