NextGen AI agent for perceived quality of cars
| dc.contributor.author | Eliasson, Erik | |
| dc.contributor.author | Johansson, Emil | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för mikroteknologi och nanovetenskap (MC2) | sv |
| dc.contributor.department | Chalmers University of Technology / Department of Microtechnology and Nanoscience (MC2) | en |
| dc.contributor.examiner | Larsson-Edefors, Per | |
| dc.contributor.supervisor | Svensson, Lars | |
| dc.date.accessioned | 2025-06-26T06:22:50Z | |
| dc.date.issued | 2025 | |
| dc.date.submitted | ||
| dc.description.abstract | This thesis details an AI-powered tool intended to assist designers in evaluating Percived Quality in the early stages of the design of the development of vechicles. The tool integrates machine learning models, image analysis, and a Retrieval-Augmented Generation system to provide real-time, context-aware insights based on customer data and design attributes. Enabling proactive decision-making aims to reduce costly design iterations and align products more closely with user expectations. | |
| dc.identifier.coursecode | MCCX04 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12380/309693 | |
| dc.language.iso | eng | |
| dc.setspec.uppsok | PhysicsChemistryMaths | |
| dc.subject | AI, perceived quality, RAG, machine learning, image analysis, automotive design, user feedback | |
| dc.title | NextGen AI agent for perceived quality of cars | |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.degree | Master's Thesis | en |
| dc.type.uppsok | H | |
| local.programme | Embedded electronic system design (MPEES), MSc |