Smart Farm: Automated Classifying and Grading System of Tomatoes using Fuzzy Logic

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Manual operation is considered as a big factor in a low production and the Smart Farm System is one way that can address this problem by improving and increasing the quality and quantity of production  by making farms more intelligent and more connected through the precision agriculture. With that, the proponents will develop a system through smart farm system that is capable of classifying and   grading the tomatoes.

This process will be done automatically using image processing and fuzzy logic. There will be a Fuzzy Inference Systems sto be established using MATLAB software to classify and grade the tomato fruit. In classifying, system will determine if tomato is damaged or not. On the other hand, system will distinguish if a specific fruit or crop is under ripe, ripe or overripe in  grading. It is believed that this study is of great help to farmers for high yield and productive plant harvests.


Presented in chapter 2 is the review of related literature and studies which the proponent believes,  has eloquent bearing to the present study. The proponents gathered relevant literatures which  provide and help them to build the thoughts, views and information in developing the study. Based from the different facts obtained, the proponent constructed conceptual and theoretical frameworks.


This chapter provides an overview of the methods and steps used in developing the sorting and grading system. The purpose of this chapter is to present the Conceptual and Theoretical Framework, as well as the proposed design which is based on the knowledge obtained from the different related literatures. This includes, but not limited to tools, processes and equipment used in the design and development of the study.

Conceptual Framework:

The study aimed to develop the automated classifying and grading system. It will be developed through the designs and smart fabrication. The proponents used visual representation like diagrams to show the step by step processes on how the system will be made. This diagrams will set as guide  for the proponents’ concept about the system. These visual aids was very helpful to them in conceptualizing and building the system.

Block Diagram

The Five Graphical User Interface Tools for the Fuzzy Inference System.

The Five Graphical User Interface Tools for the Fuzzy Inference System.

Theoretical Framework:

Fuzzy Logic Controller

Fuzzy Logic Controller is either be a software or a hardware. It is considered as a fuzzy code   designed which function is to control something and it can be used in anything from the small  circuits into the large frames. Fuzzy logic usually builds through the rules set by user-supplied human language.

Fuzzy systems was able to convert the set of rules to their respective mathematical equivalents. Through this, its function is to simplifies the work of the system designer and also the computer, and giving the results in highly accurate representations.

Proposed Design:

The process flow of the system. It will start from capturing the image in a light cell as image acquisition. The machine vision system will now take over processing the image through retrieving the RGB Color Maps, Image segmentation where threshold operation and binarisation were done, then feature extraction and the calculation of mean values.

After it undergo to the processing, the image will now be converted into binary of 0’s and 1’s and will serve as the input for the fuzzy logic classification and evaluation. Process will proceed to classification where it will be sorted to its quality whether it is good or bad. Only the good  quality will now undergo to the grading system  where the level of ripeness will be determined if it is under ripe, ripe or overripe.

Proposed Design

Proposed Design.

Source: Lyceum of the Philippines University
Authors: Lenard C. Dorado | Jules Ian C. Aguila | Rionel B. Caldo

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