Location-Based Work Sampling

Abstract

Previous studies have applied the Work Sampling (WS) technique in different job sites to determine how workers employ their time in relation to a taxonomy of various work activities. However, no other significant contribution has been discussed for including location information of the work activities. This study added a geographic location to each random WS observation for a more comprehensive work efficiency analysis. In this paper, an implementation analysis was presented based on the findings from a case study. The research process followed four steps: (1) clarifying the categories of the activities;(2) deciding the confidence interval; (3) collecting and extracting data; and (4) analyzing the data. For adding location data to the technique, the authors used the geographic coordinates provided by smartwatches used by the research team connected to two Global Navigations Satellite Systems (GNSS), and the coordinates obtained from photos taken for each observation. Each observation made contained the following information: (1) photo; (2) timestamp; (3) trade observed; (4) work category; and (5) geographic coordinates, consequently, workspace category. This paper presents as the main contribution an adaption of the WS technique, named Location-based Work Sampling (LBWS), which can provide a better understanding of the ongoing activities' behavior.

Framework for Integrating Productive, Contributory, and Noncontributory Work with Safe and Unsafe Acts and Conditions

“…Pose estimation techniques are widely used in ergonomics studies, however, these still need to be improved to determine the categories of productive work [ 47 ]. Furthermore, there is a study in progress that analyzes the opportunities of combining data from geographically located observations of workers with data obtained from WS [ 51 , 52 ]. However, there is no further information on whether it could be implemented in real time.…”