Year: 2025
Type: conference-paper
Abstract: Hispanic workers represent about one third of the total workforce of the construction industry in the United States. Nevertheless, this demographic has disproportionately higher rates of fatalities and injuries. Each year, over 300 Hispanic workers lose their lives due to construction related incidents. Various efforts have been made to prevent casualties among this population, of which safety training has been found to be the most effective. However, traditional safety training methods have not been found to be adequate, particularly failing to address barriers such as language differences, cultural factors, immigration concerns, and issues related to construction operation skills. A potential solution to effectively address these challenges is to utilize advanced technologies such as Artificial Intelligence (AI) to improve safety training and outcomes for Hispanic workers. The objective of this prospective research is to develop AI-based safety training systems for Hispanic workers which provides personalized and adaptive training for better knowledge retention and engagement through the enhancement of four core aspects such as communication, culture, workers’ rights, and construction operational safety. By addressing these critical challenges, this study designs the foundation for healthier and safer workplace for Hispanic laborers. In the broader context, the proposed intelligent training systems create a platform with comprehensive safety programs that connect vulnerable groups of workers across the U.S. construction industry.
Source: CIB Conferences
Authors: Gulzhanat Akhanova, Chien-Ho Ko
Institution: University of Kansas
Language: English
Subfield: Radiological and Ultrasound Technology
Field: Health Professions
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4411471427