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Detection of Rice and Rice Type Based on AI/ML Using Web-Based System and Smartphone Camera to Prevent Artificial Rice�

Submitted by

Amitava Das (20EE23A12014), Ayush Garg (32EE22A12003),

Md Saddam Ansari (20EE23A12012), Chandra Sarkar (20EE24J12005),

Sudeshna Das (32EE23A12005)

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Primary objective

  • To develop an AI/ML-powered web-based system that can accurately detect and classify various types of rice, while also identifying artificial rice. The system will use smartphone cameras to enable users, including farmers, consumers, and quality inspectors, to capture images of rice samples for analysis. By using machine learning algorithms, the system will process these images and provide real-time feedback on the authenticity and type of rice. Ultimately, this project seeks to protect consumers from counterfeit food products, enhance food safety, and contribute to the overall well-being of rice-dependent populations.

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Proposed Solution: AI/ML-Based Rice Detection System

1.System Architecture and Design

Web Interface and Mobile Integration

AI/ML Model Integration

Database

2. AI/ML Model Development

Data Collection and Preprocessing

Feature Extraction

Training and Testing

3. Web-Based System

4. Smartphone Camera Integration

5. Real-Time Feedback and Alerts

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Societal Impact

Consumer Protection

Food Safety Enhancement

Empowerment of Farmers and Producers

Strengthening Regulatory Frameworks

Challenges and Limitations

Image Quality Variability

Model Training and Generalization

Scalability