%0 Journal Article
	%A Rujijan Vichivanives and  Kittiya Poonsilp and  Canasanan Wanavijit
	%D 2016
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 115, 2016
	%T Developing Rice Disease Analysis System on Mobile via iOS Operating System
	%U https://publications.waset.org/pdf/10005043
	%V 115
	%X This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.

	%P 1359 - 1363