Research Topic 7: Innovative AI Application: Making Construction Safety Training Fun and Effective
Research Description
In high-risk industries such as construction, attaining proficiency in intricate safety protocols is crucial. At present, construction safety training is mainly theoretical, typically delivered through readings or briefings, and often lacks customization for specific job sites. We invite you to be part of a groundbreaking initiative that leverages Artificial Intelligence (AI) to convert real-world scenes into immersive, interactive training modules. Our innovative approach enables contractors to craft instantly deployable training environments using footage captured directly from their work sites. This allows every worker to practice and internalize safety procedures within these environments, accessible via extended reality. As a result, individuals can develop muscle memory and gain confidence in mastering safety procedures before stepping onto actual construction sites, considerably reducing the likelihood of deviations from safety protocols. Join us in this transformative endeavor to raise the bar for safety training standards by making the learning experience more practical and interactive!
REU Research Plan
During the summer months, REU students will engage in developing an AI-powered tool capable of generating interactive safety training modules, alongside graduate student mentors and faculty advisors. The students’ involvement will include the following:
• Conduct literature review to understand the current state-of-the-art on safety training and technology application;
• Write code to develop components of the tool under extensive tutoring and guidance;
• Assess the tool’s efficacy against its intended objectives; and
• Contribute to the writing of a conference/journal paper to disseminate the project
More Details
Keywords: construction safety, human-computer interaction, artificial intelligence, civil engineering, construction management, building construction.
Required Skills: programming skills and basic knowledge of statistics.
Undergraduate Degrees: Computer Science, Civil Engineering, Building Construction, Construction Science/Management.
Potential Faculty Advisors: Dr. Zhenyu Zhang and Dr. Xi Wang