Time-Benefit Analysis of Semiautomatic 3D Laser Scanning for BIM-based Facility Management

Background and Aim.
As-built data and knowledge of building structures are crucial for effective facility management (FM). Building Information Modeling (BIM) models offer the opportunity to integrate information from digital building models into FM systems, without information loss. Data acquisition methods include 3D modeling and point cloud-based 3D laser scanning. While modeling point clouds in BIM software manual can achieve precise results, the process is time-intensive. Semi-automated modeling that relies on AI-based software can contribute to as-built data acquisition and modeling with reduced time and personnel requirements, known as semi-automated. Therefore, this paper aims to investigate the efficiency and limitations of integrating AI with BIM for FM, comparing manual and semi-automatic modeling approaches.

Methodology.
Manual modeling based on point clouds is conducted before a semi-automatic classification is performed. The generated data models are then quantitatively evaluated for the required time for each measurement size and qualitatively evaluated concerning the accuracy.

Results.
The analysis illustrates that semi-automated modeling methods are particularly efficient for standardized and even historical buildings by a 65% faster data generation than manual building modeling. The results are proven by valid data.

Originality.
The investigation compares manual and semi-automatic modeling approaches. Evaluating time requirements and qualitative criteria provides a practical framework for decision-makers.

Practical or Social Implications.
The study offers insights for decision-makers in FM and related fields to make informed decision-making about modeling methods, contributing to process optimization by integrating modern technologies. Based on the results obtained, stakeholders receive a neutral approach backed up by valid key figures, providing a solid basis for future decisions in connection with data collection.