Rice Inspection System

Rice quality assessment is essential for meeting high-quality standards and consumer demands. However, challenges remain in developing cost-effective and rapid techniques to assess commercial rice grain quality traits. However, Characteristics of rice appearance quality are very important to evaluat

Project Title

Rice Inspection System

Project Area of Specialization

Artificial Intelligence

Project Summary

Rice quality assessment is essential for meeting high-quality standards and consumer demands. However, challenges remain in developing cost-effective and rapid techniques to assess commercial rice grain quality traits. However, Characteristics of rice appearance quality are very important to evaluate rice quality. The conventional methods for determining rice quality are based on manual inspection which is an inefficient way and results in inconstant outcomes.

Rice Inspection System is essential for maintaining the quality standards for rice. Challenges remain for developing a cost-effective and rapid technique to assess commercial rice grain quality. we are making the Rice Inspection System will check the Characteristics of rice appearance are very important to evaluate rice quality. The normal method is manual inspection. Thus, we developed an automatic system that allowed us to evaluate rice appearance quality including rice chalkiness and shape. How: the application of computer vision (CV) and machine learning (ML) to classify commercial rice samples based on dimensionless morphometric parameters and colour parameters extracted using CV algorithms from digital images obtained from a smartphone camera. The artificial neural network (ANN) model was developed using nine morpho colorimetric parameters to classify rice samples into 15 commercial rice types. Furthermore, the ANN models were deployed and evaluated on a different imaging system to simulate their practical applications under different conditions. However, we will use hardware for the project we will use a smartphone for capturing images and a scanner for identification of rice.

Project Objectives

The purpose of the project is to assure the quality of the rice and its type. The adoption by the industry of rapid, reliable and accurate methods may allow the incorporation of different morphcolorimetric traits in rice with consumer perception and to deliver the product with the best quality and outcome.

Project Implementation Method

Rice quality assessment is essential for meeting high-quality standards and consumer demands. However, challenges remain in developing cost-effective and rapid techniques to assess commercial rice grain quality traits. This paper presents the application of computer vision (CV) and machine learning (ML) to classify commercial rice samples based on dimensionless morphometric parameters and color parameters extracted using CV algorithms from digital images obtained from a smartphone camera. The artificial neural network (ANN) model was developed using nine morpho colorimetric parameters to classify rice samples into 15 commercial rice types. Furthermore, the ANN models were deployed and evaluated on a different imaging system to simulate their practical applications under different conditions. Results showed that the best classification accuracy was obtained using the Bayesian Regularization (BR) algorithm of the ANN with ten hidden neurons at 91.6% (MSE = <0.01) and 88.5% (MSE = 0.01) for the training and testing stages, respectively, with an overall accuracy of 90.7% (Model 2). The deployment also showed high accuracy (93.9%) in the classification of the rice samples. The adoption by the industry of rapid, reliable, and accurate methods, such as those presented here, may allow the incorporation of different morpho colorimetric traits in rice with consumer perception studies.

Benefits of the Project

This project will make the process fast and reliable nad enhannce the export of pakistan.

By using this project easily differentiiate the qualities of rice as well as it's class.e.g 'basmati , silla .

this project protect you from scam by other consumer or  seller's. e.g "mixing the  differrent quality of rice and sell it on high price .

this project ensure you to high quality .

Technical Details of Final Deliverable

Iot Based software

The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Agriculture

Other Industries

Food

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People, Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com