TRAAKY
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Date
2024
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Abstract
This thesis describes the development of a web application that is part of a larger collaborative project with FH-Sankt Pölten. The project aims to provide businesses with a cost-effective solution for asset tracking. Rather than engaging costly consultants, users can complete a form on the website and receive insights into three implementations by other companies with similar requirements.
The implementation includes a web interface that is hosted internally at FH. The interface was developed using HTML, CSS, and Bootstrap. Users are required to fill out a form, and the data is processed by a K-Means algorithm that is implemented in PHP and stored in a MYSQL database. The algorithm identifies the three most similar solutions from a set of use cases, and the results are displayed on the website. Furthermore, the website can provide recommendations using the Large Language Model ChatGPT.
The result is a website that offers businesses without asset tracking systems an introduction to suitable localization methods. The website operates smoothly on FH St. Pölten's internal systems. To ensure high accuracy and understanding, users receive assistance from a supervisor when filling out the form. The PHP Slim Framework API facilitates seamless communication between the user interface and backend services. This project offers a solution that is both effective and cost-efficient for businesses of all sizes to find the most appropriate localization method.