The efficient management of storage units requires a reliable and streamlined move-out process. Manual validation methods are resource intensive. Therefore, the task is to introduce an automated approach that capitalises on modern smartphone capabilities to improve the move-out validation process. Hence, the purpose of this thesis project. The proposed solution is a Proof of Concept (POC) application that utilises the Light Detection and Ranging (LiDAR) sensor and camera of a modern iPhone. This is performed through RoomPlan, a framework developed for real-time, indoor room scanning. It generates a 3D model of the room with its key characteristics. Moreover, to increase the number detectable object categories, the solution is integrated with the image classifier Tiny YOLOv3. The solution is evaluated through a quantitative evaluation in a storage unit. It shows that the application can validate whether the storage unit is empty or not in all the completed scans. However, an improvement of the object detecition is needed for the solution to work in a commercial case. Therefore, further work includes investigation of the possibilities to expand the object categories within the image classifier or creating a similar detection pipeline as RoomPlan adjusted for this specific case. The usage of LiDAR sensors indicated to be a stable object detector and a successful tool for the assignment. In contrast, the image classifier had lower detection accuracy in the storage unit.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-531021 |
| Date | January 2024 |
| Creators | Rimhagen, Elsa |
| Publisher | Uppsala universitet, Avdelningen Vi3 |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UPTEC F, 1401-5757 ; 24026 |
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