AI Powered Form Filling
ICT & Artificial Intelligence
Client company:Infoland
Eli Brouwers
Eric van den Berge
Victoria C. A. Fong
Project description
Our project aims to improve incident reporting efficiency and effectiveness through the development of an automated incident report form filling tool. In collaboration with Infoland, we have created a software platform that generates context-specific questions based on user descriptions. Leveraging question-answering models, the tool fills in the incident report form by selecting the best answer for each label, accompanied by a confidence score. The generated form is then presented to the user for review and editing if necessary. Through the successful design and development of a minimum viable product (MVP), focusing on Zenya's Incident forms, we have demonstrated how contextual information can be utilized to automatically populate each label in the form. This prototype showcases the potential of utilizing deep learning models to streamline incident reporting processes, leading to enhanced efficiency and accuracy
Context
This project involves the collaboration between Fontys University's Advanced Artificial Intelligence department and Infoland to develop an automated incident report form filling tool. The tool generates questions based on user descriptions, fills in the form using question-answering models, and aims to enhance the efficiency and effectiveness of incident reporting processes.
Results
Our team has achieved the successful design and development of an MVP software platform that centers around Zenya's incident forms. Through this platform, we have effectively demonstrated how contextual information can be utilized to automatically populate each label within the form, along with its corresponding confidence score
About the project group
As students from Fontys University's Advanced Artificial Intelligence department, we have partnered with Infoland to develop a prototype capable of automatically filling in incident forms from Zenya using spoken context. With a project duration of 6 months, our objective is to create a solution that streamlines the incident reporting process and improves efficiency.
