Autonomous Human Monitoring: A Safety 4.0 Approach

Abstract

Following the volatile nature of the global market, warehouses and assembly lines have grown in size. These industries are critical components of the interrelated production, distribution, and supply management system. Warehouses and assembly lines are vital for the modern global economy. While important, they can be dangerous for people working in hazardous environments.

Occupational health and safety is a fundamental aspect that underpins the well-being of the modern workforce (Jain et al., 2018). It represents a moral and ethical imperative, ensuring that individuals can work in environments that not only sustain their health but also support a robust and productive labor force. In the context of assembly line work, where repetitive tasks, ergonomic challenges, and exposure to potentially hazardous materials are routine, the importance of health and safety takes on heightened significance.

This study presents a case study of a framework that can detect health and safety concerns in warehouses and assembly lines, such as fall/ slip, forklift path concerns, prolonged standing, posture concerns, and helmet detection scenarios. The framework will detect possible injuries in the case of a fall/slip scenario and or prevent injuries in the case of a worker standing in the forklift path near a heavy-machinery/hazardous area, where the framework will notify the personnel such as the foremen of such concern being detected. Furthermore, when it comes to the health aspect, the framework will help prevent chronic diseases that emerge over a long period of time from prolonged standing by notifying the worker in that case and the personnel in charge of such concern and other cases such as lifting objects using a posture that could affect the spine over time, and looking down a screen/machine.

Date of Award	19 Dec 2023
Original language	American English
Supervisor	Saed Amer (Supervisor)