Human Activity Analytics for Enhancing Safety in Workplace
Logistics operations and procedures involve many labor-intensive operations which are error-prone. Human activity analysis can provide useful information for more effective management of the operations. It can help to enable a much more flexible and efficient process checking, assess workers' safety, and reduce the impact caused by human errors and increase productivity. However, having round-the-clock manual monitoring is impractical. Therefore, employing new machine vision and sensing technologies in logistics operations will be helpful.
This project of LSCM aims to develop machine vision and sensing tools to automate human activity analysis for process checking and safety monitoring. Specifically, machine vision and sensing techniques are being developed for the following procedures:
a. Pose tracking for activity analysis, e.g., toy manufacturing;
b. Pose comparison for vocational training, e.g., load lifting.
The project is to cater for the needs of the local industry, aiming to improve the workers’ safety, enhance the efficiency and flexibility of the logistics operations and procedures, and avoid human errors so as to boost the productivity of the industry.
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