Samer Hassnou

Introduction

This project aims to develop a comprehensive and efficient system for analyzing images using Amazon Web Services (AWS). The system allows users to upload images through a user-friendly web interface that supports multiple languages (Arabic, English, German) to be analyzed and have their labels extracted. This project is a practical example of how to use a cloud infrastructure to create flexible and scalable solutions in the field of visual data processing.

Project Benefits

This project offers a wide range of benefits, such as intelligent image analysis using Amazon Rekognition, high scalability due to the serverless nature of AWS services, and cost-effectiveness since you only pay for the resources you use. The system also provides ease of use through a simple user interface and the ability to manage user quotas to ensure fair resource usage.

Implementation Steps

• Frontend Setup: Create a frontend that supports multiple languages with a field for uploading images.
• API Gateway Configuration: Set up a REST API endpoint to receive image upload requests and route them to a Lambda function.
• Lambda Function Development: Write the necessary code for the Lambda function to store the image in an S3 Bucket, then call the Rekognition service to analyze it.
• S3 Bucket Setup: Create a storage bucket in Amazon S3, enabling encryption and appropriate CORS policies.
• DynamoDB Setup: Create a table to manage user quotas and the allowed number of requests.
• Monitoring and Logging: Set up CloudWatch Logs to record all activities and track system performance.

Project Features

• High Scalability: The system can handle a large increase in users and requests without major architectural changes.
• Data Security: Images are stored in S3 with encryption enabled.
• Cost-Effectiveness: The system relies on a pay-as-you-go model, which reduces operational costs.
• Usage Control: The quota system ensures fair resource usage and prevents misuse.

Technologies Used

• AWS Lambda: A serverless compute service for processing requests.
• Amazon S3: For storing uploaded images.
• Amazon Rekognition: For analyzing images and extracting labels.
• Amazon DynamoDB: For managing user quotas.
• Amazon API Gateway: As the entry point for receiving requests.
• Amazon CloudWatch: For monitoring and logging.