Human activity recognition for musculoskeletal accidents at workplace
| dc.contributor.author | Hafiz Muhammad Abdullah | |
| dc.contributor.author | FA17-BSE-014 | |
| dc.contributor.author | Dr. M. Aksam Iftikhar | |
| dc.contributor.author | LHR TP 7024 | |
| dc.date.accessioned | 2026-02-17T08:17:00Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | The industrial revolution that aims to automate industries without human interaction by using artificial intelligence. Employees are trained and are provided with standard operating procedures (SOPs) to work in a safe environment. However, sometimes due to the reckless behaviour of employees or improper training, accidents happen. Employers are held responsible for employee’s financial aid due to injuries or accidents that takes place at the workplace. This project will allow surveillance on employee’s activities for musculoskeletal injuries using Deep learning techniques for awkward posture recognition. The benefit of this project is that it will guide employers in training employees and will try to investigate the person responsible for the accident that takes place in the workplace. | |
| dc.identifier.uri | https://repository.cuilahore.edu.pk/handle/123456789/1793 | |
| dc.language.iso | en | |
| dc.publisher | Library Information Services, COMSATS University Islamabad, Lahore Campus | |
| dc.relation.ispartofseries | LHR TP 7024 | |
| dc.subject | TECHNOLOGY::Information technology::Computer science | |
| dc.subject | Dr. M. Aksam Iftikhar | |
| dc.title | Human activity recognition for musculoskeletal accidents at workplace | |
| dc.type | Thesis |
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