## 6 Conclusions  
The topic of human-robot collaboration and its possibilities in industrial scenarios is of great interest and at the center of debate within the scientific community. This is mainly because collaborative robotics is unanimously considered one of the most promising technologies for manufacturing companies that aspire to develop more flexible, adaptive and efficient production systems. In this research, the use of a neural model integrated with a cobot was explored to assess and optimize 3D human poses. The architecture created is based on temporal information with dilated convolutions through trajectories of 2D keypoints for the automatic calculation of joint angles. Our ergonomic analysis produced a dataset that provides objective values for postures, with the acquisition and processing of data completely independently from the evaluation phase. For the alleviation of human stress and to improve some production parameters, a collaborative robot was implemented, which was possible thanks to the technologies of adaptive systems based on flexibility, reconfigurability and production efficiency. The main contribution of this work lies in the calculation of the joint angles based on 3D human pose estimations in workplaces. A second contribution of this work is the \(\text{I}_{\text{TOT}}\) calculation, which assesses various ergonomic indicators through a fuzzy inference system. \(\text{I}_{\text{TOT}}\) defines the elementary operation for which it is most critical to implement the collaborative robot to evaluate ergonomic stress and production capacity. These methods outperform those in [1, 37, 57], in which posture scores are appraised by detecting the 2D coordinates of body joints. The automation of observation-based techniques for posture assessment using computer vision is able to eliminate errors due to human subjectivity and to reduce the times needed for posture evaluation in workplaces.  
Our research results were validated by comparing them with risk classes computed using the classical method based on tabular values and nominal angle values for each elementary operation.  
Future research will address the following:  
Testing our methodology on different personal protective equipment worn by operators, or considering different environmental conditions, to evaluate whether they can influence the obtained results.  
The processing of video sequences in real-time systems with an automatic alerting system for identifying the most critical operations.  
The evolution of 3D pose estimations for multiple people in the same area.  
Comparing ergonomic assessments between workers and investigating the impact of cobot implementation on different workstations while changing the operators.  
Conceptualization, M.M., C.R. and V.B.; methodology, M.M., C.R., F.G. and V.B.; software, F.G. and V.B.; validation, M.M., F.G. and V.B.; formal analysis, M.M., F.G. and V.B.; investigation, M.M. and C.R.; resources, M.M., F.G. and V.B.; data curation, M.M., C.R., F.G. and V.B.; writing--original draft preparation, M.M., F.G. and V.B.; writing--review and editing, M.M.S. and L.T.; visualization, M.M.S., L.T., M.M., F.G. and V.B.; supervision, M.M.S. and L.T. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest.