Invoice Scanner App

Marty, Roger and Emjee, Tseten (2024) Invoice Scanner App. Other thesis, OST Ostschweizer Fachhochschule.

[thumbnail of HS 2024 2025-SA-EP-Emjee-Marty-Invoice Scanner App.pdf] Text
HS 2024 2025-SA-EP-Emjee-Marty-Invoice Scanner App.pdf - Supplemental Material

Download (12MB)

Abstract

In this day and age, invoices are received in a wide variety of formats. Some as physical
paper documents and others digitally. This makes it challenging to keep track of all
invoices, their status and other relevant information. To combat this issue a solution
should be created that allows scanning of physical invoices or uploading digital ones for
processing. Important information should be extracted and returned in a structured
format providing a tabular overview.

A mobile app for Android was developed for the frontend. The app is based on Kotlin
utilizing Jetpack Compose and Hilt. As a REST-API for the frontend to interact with, a
Python-based backend has been created using the FastAPI framework. The backend has
been containerized and runs on a virtual server behind a Traefik reverse proxy. Various
AWS services have been integrated for storage, including S3 and DynamoDB, as well
as computation with Lambda and data extraction using Textract, a machine learning
service that goes beyond ordinary OCR. The Firebase Cloud Messaging service was used
for push notifications.

The produced Invoice Scanner app solves the described problem. Invoices can be scanned
for automatic data extraction or manually created. The app provides an organized
overview of all invoices and options to edit, mark as paid and view the associated orig-
inal invoice file. Acting as a centralized place for invoices the app can be used for
management and archiving purposes.

Item Type: Thesis (Other)
Subjects: Topics > HCI Design
Topics > Internet Technologies and Applications > Amazon Web Services (AWS)
Area of Application > Image/Video Processing
Technologies > Databases
Technologies > Protocols > REST
Divisions: Bachelor of Science FHO in Informatik > Student Research Project
Depositing User: OST Deposit User
Contributors:
Contribution
Name
Email
Thesis advisor
Seelhofer, Martin
UNSPECIFIED
Date Deposited: 18 Feb 2025 12:28
Last Modified: 18 Feb 2025 12:28
URI: https://eprints.ost.ch/id/eprint/1249

Actions (login required)

View Item
View Item