Solution Demo-Enhancing Expense Tracking: Building a Smart Receipt Scanner with Azure Gen Ai Form Recognizer

### Streamlining Receipt Management with Azure Cognitive Services: A Use Case for Generative AI

In today's fast-paced world, managing receipts can be a cumbersome task. Whether it's for personal expense tracking or business accounting, the process of manually entering receipt details is time-consuming and prone to errors. To address this challenge, we present a use case that leverages Azure Cognitive Services to build a mobile application that automates receipt management. This article explores how Generative AI, specifically Azure Form Recognizer, can simplify and enhance the accuracy of extracting key information from receipts.

#### Use Case Overview

Objective: Develop a mobile application for iOS using React Native that allows users to take pictures of receipts and automatically extract the total amount, merchant name, and date. The backend service, built with Node.js, will process these images using Azure Form Recognizer.

#### Business Requirements

Introduction:

The Receipt Scanner Mobile Application aims to streamline the process of managing receipts by leveraging AI-powered text extraction. This solution will save users time and effort in manually entering receipt details, enhancing productivity and accuracy in expense tracking.

Scope:

- User Interface:

- Simple and intuitive design for capturing and viewing receipt images.

- Display extracted information clearly and concisely.

- Support for taking pictures using the device camera or selecting images from the photo library.

- Backend:

- RESTful API to handle image uploads.

- Integration with Azure Form Recognizer for extracting receipt information.

- Secure and efficient processing of image data.

- Data Extraction:

- Accurate extraction of total amount, merchant name, and date from receipt images.

- Handling various receipt formats and ensuring robustness in text recognition.

Functional Requirements:

1. Image Capture:

- Users should be able to take pictures of receipts or select images from the photo library.

2. Image Upload:

- The application should upload the captured image to the backend server.

3. Data Extraction:

- The backend should process the image using Azure Form Recognizer to extract key information.

4. Display Extracted Data:

- The application should display the extracted total amount, merchant name, and date to the user.

5. Error Handling:

- The application should handle errors gracefully and notify users of any issues.

Non-Functional Requirements:

1. Performance:

- The application should process and display extracted data within a few seconds.

2. Usability:

- The user interface should be intuitive and easy to use.

3. Scalability:

- The backend should be able to handle multiple concurrent users and image uploads.

4. Security:

- Ensure data privacy and security during image upload and processing.

#### Technology Stack

- Frontend: React Native

- Backend: Node.js with Express

- AI Service: Azure Form Recognizer

#### Implementation Steps

1. Set Up Development Environment

- Install Node.js.

- Install React Native CLI.

- Install Xcode for iOS development.

2. Create React Native Project

- Initialize a new React Native project using npx react-native init ReceiptScanner.

3. Install Necessary Dependencies

- Install axios for making HTTP requests.

- Install react-native-image-picker for accessing the device camera and photo library.

4. Implement Image Picker in React Native

- Set up image picker functionality to allow users to take or select pictures of receipts.

- Display the selected image in the app.

5. Set Up Node.js Backend

- Initialize a new Node.js project and install necessary dependencies (`express`, multer, axios).

- Create an API endpoint to handle image uploads and call Azure Form Recognizer.

6. Integrate Frontend and Backend

- Use axios in the React Native app to send the selected image to the backend API.

- Handle the backend API response to display extracted data in the app.

7. Azure Form Recognizer Configuration

- Create an Azure Form Recognizer resource in the Azure portal.

- Obtain the endpoint URL and subscription key.

8. Configure Backend for Azure Form Recognizer

- Update the backend to use the Azure Form Recognizer endpoint and key to analyze uploaded receipts.

9. Testing

- Run the React Native app on an iOS simulator or device.

- Start the Node.js backend server.

- Test the functionality by taking pictures of receipts and verifying the extracted data.

10. Deployment

- Deploy the Node.js backend to a cloud service (e.g., Azure App Service).

- Update the React Native app to point to the deployed backend URL.

11. Enhancements

- Improve UI/UX for a better user experience.

- Implement error handling and user notifications.

- Add user authentication if required.

#### Agenda for Demo

To help understand the process better, here is an agenda that outlines the key steps and components involved in this use case. You can also refer to the [video demo](https://youtu.be/DtJZ9mH3jz4) for a visual walkthrough:

1. Understanding Azure Form Recognizer

- Overview of Azure Form Recognizer and its capabilities.

2. Creating Form Recognizer Service Endpoint in Azure

- Step-by-step guide to set up the Form Recognizer service in the Azure portal.

3. Making API Calls Overview

- Introduction to making API calls to the Form Recognizer service.

4. Make API Call with Postman

- Demonstration of how to make an API call using Postman to test the Form Recognizer service.

5. JSON Response from the API Call

- Understanding the JSON response received from the Form Recognizer API.

6. Integrating with a React Application

- How to integrate the Form Recognizer service with a React Native application.

7. Implementation of a React App to Integrate with the Service

- Step-by-step implementation of a React Native app that integrates with the Form Recognizer service.

8. Handling API Responses

- How to handle and display the data extracted from receipts in the React Native application.

#### Benefits

- Time Savings: Automates the manual entry of receipt details, significantly reducing the time required for this task.

- Increased Accuracy: Utilizes AI to accurately extract key information, minimizing errors.

- Enhanced Productivity: Streamlines the receipt management process, allowing users to focus on more important tasks.

- User-Friendly: Provides a simple and intuitive interface for capturing and managing receipts.

#### Conclusion

The Receipt Scanner Mobile Application showcases the power of Generative AI and Azure Cognitive Services in transforming mundane tasks into efficient, automated processes. By leveraging Azure Form Recognizer, we can provide users with a seamless and accurate solution for managing receipts, enhancing productivity and accuracy in expense tracking. This use case highlights the potential of AI in everyday applications, paving the way for further innovations in automating routine tasks.

For a comprehensive demonstration, please refer to the video below:

During job coaching our participant has done the below demo.

Demo Video:(https://img.youtube.com/vi/DtJZ9mH3jz4/0.jpg)]

Visit our site for more details on our coaching:

VSKUMAR ENTERPRISES (vskumarcoaching.com)

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