Construction Tasks Electronic Process Monitoring: Laboratory Circuit-Based Simulation Deployment

• Type: Article in International Scientific Journal
• Date: 2022

Authors

Calvetti, D (Author) FEUP; Sanhudo, L (Author) Other; Pedro Mêda (Author) FEUP; Martins, JP (Author) FEUP; Goncalves, MC (Author) Other; Hipólito Sousa (Author) FEUP

Journal

Title: Buildings

Vol. 12

Final page: 1174

ISSN: 0007-3725

Publisher: MDPI

Indexing

ISI Web of Knowledge - 1 Citation

Scopus

Other information

Authenticus ID: P-00W-ZQA

DOI: 10.3390/buildings12081174

Abstract (EN): The domain of data processing is essential to accelerate the delivery of information based on electronic performance monitoring (EPM). The classification of the activities conducted by craft workers can enhance the mechanisation and productivity of activities. However, research in this field is mainly based on simulations of binary activities (i.e., performing or not performing an action). To enhance EPM research in this field, a dynamic laboratory circuit-based simulation of ten common constructions activities was performed. A circuit feasibility case study of EPM using wearable devices was conducted, where two different data processing approaches were tested: machine learning and multivariate statistical analysis (MSA). Using the acceleration data of both wrists and the dominant leg, the machine-learning approach achieved an accuracy between 92 and 96%, while MSA achieved 47-76%. Additionally, the MSA approach achieved 32-76% accuracy by monitoring only the dominant wrist. Results highlighted that the processes conducted with manual tools (e.g., hammering and sawing) have prominent dominant-hand motion characteristics that are accurately detected with one wearable. However, free-hand performing (masonry), walking and not operating value (e.g., sitting) require more motion analysis data points, such as wrists and legs.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 26