Summary Reader Response Draft 2

The article “Transforming Workplace Safety: Harnessing AI for Real-Time PPE Monitoring” explores the impact of Personal Protective Equipment (PPE) detection by AI and several advantages of the use of AI to deal with non-compliance of not wearing PPE (Rebecca, L., n.d).

The system, empowered with AI-enabled image and video analysis, can identify various personal protective equipment, promptly sending alerts for individuals who do not have proper gear (Lambert, R. 2023). Based on one of the few companies that supply this system, the system offers remote construction site monitoring and provides centralized oversight to managers through a user-friendly platform and by sending real-time safety alerts for PPE non-compliance. It also provides workplace recordings to obtain video data on workplace safety and potential hazards for identifying and preventing accidents (V3 Smart Technologies, 2024). The system simply works by obtaining red-green-blue (RGB) images from CCTV, which are transmitted through a monitoring system responsible for ‘detection and verification’ and ID association, and sending off alarms regarding non-compliant workers (SCITEPRESS, 2021).

The state-of-the-art system enhances safety and productivity within construction sites.

In my research for an advanced technology or a system that can be used at construction sites, real-time PPE detection with AI and computer vision stands out the most as it brings great benefits for both managers such as supervisors, and safety officers, as well as construction workers. On top of that, in fact, construction industry is recognized as one of the top contributors to all fatalities and injuries in Singapore (Workplace Safety and Health Report, 2023). Hence, this system is highly relevant for use in construction industry. Even though it may seem beneficial to use this system at construction sites, it is worth considering  a limitation that it may pose for a better understanding of how reliable this system is for construction use. 

The first advantage of the system is that it eliminates manual detection errors which results in a boost in productivity of managers (Rebecca, L., n.d). The AI-driven PPE compliments the work of managers in ensuring workers wear PPE. Managers will be more productive as the system allows them to focus on more important tasks without having to monitor the workers repetitively and laboriously at construction sites and check whether they are wearing PPE. Hence, the elimination of manual detection of PPE will bring productivity among managers. 

The second advantage is that managers will receive instant alerts for hazardous activities (Rebecca, L. n.d). Managers will receive alerts promptly and remotely for any non-compliance for not wearing PPE among workers at construction sites. Therefore, managers can make corrections before workers perform construction work and reinstate the importance of safety among workers. In this way, managers can prevent unforeseeable injuries or fatalities. Instant alerts do not just help with prompting managers for immediate correction but also make them think and put in place proper precautions before workers perform any construction work in the future.

Although it may seem that the system is favorable for use in construction, it also poses a considerable limitation. As the system is run by Artificial Intelligence (AI), many people perceive AI-based decision-making as more impartial than human-based methods due to its sophisticated and extensive data (NCS, 2023). However, examples learned by AI might amplify subjective and harmful biases and beliefs ingrained in training data (NCS, 2023). The training data imposes restrictions on workers strictly for full compliance to wear necessary PPE based on the system’s training data (NCS, 2023). This may cause unproductivity and inconvenience for workers as they must strictly abide by wearing PPE at construction sites. Based on a study, some workers do not comply with wearing PPE due to the ‘discomfort of wearing PPE’ and ‘the feeling that PPE interferes with their work’ (ScienceDirect, 2020).  Therefore, managers should always remember that the system only compliments their work by ensuring that workers wear PPE to reduce workplace accidents. Ultimately, they should assess the AI's data to determine the relevance of full PPE in specific construction works. This evaluation will help decide whether a worker should wear PPE for certain construction tasks with the aim to preserve the convenience and productivity of the workers.

In conclusion, the idea of the system is useful as it compliments the work of managers in ensuring that workers wear PPE to further minimize injuries and fatalities in construction. The advantage of accessibility to video data and instant alerts is essential for managers to boost their productivity so that they can focus on other crucial tasks. The use of the system brings benefits and is reliable for use at construction sites.

Sources:

Lambert, R. (2023, December 11). Transforming workplace safety: Harnessing AI for Real-Time PPE Monitoring. HSE People. https://www.hsepeople.com/transforming-workplace-safety-harnessing-ai-for-real-time-ppe-monitoring/

V3 Smart Technologies. (2023, July 11). PPE Detection System | Enhance your construction site safety. V3 Smart Technologies. https://v3smarttech.com/ai-solutions/ppe-detection/

SCITEPRESS. (2021). A Robust Real-time Component for Personal Protective Equipment Detection in an Industrial Setting. SCITEPRESS. https://www.scitepress.org/Papers/2021/104526/104526.pdf

Using Data and AI to Gain Insights into Your Safety Program. (2023). https://www.nsc.org/. Retrieved February 12, 2024, from https://www.nsc.org/getmedia/0e837673-651b-4763-bc99-b3991d32001a/predictive-analytics-machine-learning-priority-tech-wp.pdf

ScienceDirect. (2020). Deep learning for site safety: Real-time detection of personal protective equipment. Automation in Construction, 112, 103085. https://doi.org/10.1016/j.autcon.2020.103085