| Affiliations: | STEM Research Leadership |
| Project Leader: | Muhammad Khan
mkhan13@tamu.edu Construction Science |
| Faculty Mentor: | Chukwuma (Chuma) Nnaji, Ph.D. |
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Meeting Times:
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TBA |
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Team Size:
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4
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| Open Spots: | 0 |
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Special Opportunities:
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Learn about new technologies, data collection, analysis, developing prediction models, also attending a conference and earning co authorship on publication, can join lab in future too. |
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Team Needs:
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Have little residential construction experence or knowledge. |
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Description:
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The project titled “Developing Hybrid Safety Monitoring (Computer Vision and Internet of Things) Model for Residential Construction Workers to Prevent Fall from Height Accidents” is an innovative approach aimed at enhancing the safety of construction workers in residential projects. This initiative integrates the cutting-edge technologies of Computer Vision and the Internet of Things (IoT) to create a comprehensive safety monitoring system. The primary objective is to significantly reduce, if not entirely prevent, fall from height accidents, which are among the most common and fatal accidents in the construction industry. The model will utilize computer vision to continuously monitor the construction site, identifying potential hazards and unsafe behaviors in real-time. In tandem, IoT devices, such as wearable sensors and environmental monitoring tools, will be deployed to gather data on worker movements, environmental conditions, and equipment usage. This dual-technology approach ensures a robust and dynamic safety system that not only identifies risks but also provides actionable insights to prevent accidents before they occur.
In the second phase of the project, the collected data will be analyzed using advanced algorithms and artificial intelligence to predict and identify high-risk scenarios. This predictive analysis will enable preemptive actions to be taken, enhancing the safety protocols on-site. The model aims to create a proactive safety culture, where technology aids in foreseeing and mitigating risks, rather than merely reacting to accidents post-occurrence. Additionally, the project will focus on the development of a user-friendly interface for the system, ensuring that it is accessible and easy to interpret by site managers and safety officers. The interface will display real-time analytics and alerts, facilitating quick decision-making and effective communication among the workers. The project aspires to set a new standard in construction safety, leveraging the synergy of computer vision and IoT to protect the lives of construction workers and create a safer working environment in the residential construction sector. |