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Project Overview
Project Name
GearGuard AI
Industry
Construction
Category
Computer Vision AI / Safety Monitoring
Objective
Develop a real-time monitoring system to detect protective wear compliance, enhancing safety standards on construction sites.
Core Objective
Improve construction site safety by automating the detection of mandatory protective wear.
Solution
Designed a deep learning model using CNN to identify safety gear like helmets, glasses, vests, gloves, and jackets in real-time video feeds, alerting supervisors to non-compliance.
Result
The system enhanced on-site safety by ensuring workers consistently wore protective gear, reducing potential risks and promoting a safety-first culture.
Introduction
Project Introduction
Especially in construction risk is always high and so the safety of the workers becomes very essential. However, it is difficult to enforce safety standards, particularly in expansive facilities. This project, managed by Gonzalo, proposed a real-time solution: an efficient protective wear detection model based on deep learning to help to locate the required safety accessories. This system uses computer vision to ensure workers are always wearing the right protective equipment hence trending down human oversight issues and enhancing overall safety standards across the workforce.
Problem
THE Problem
Construction zones hold certain risk factors and it is essential that there is consistency in wearing protective gear at the workplace. Most monitoring approaches involve people’s supervision, which often does not work well on giant construction sites where it is impossible to monitor every employee. Manual checks take longer time, are prone to errors, and can not be done at all times depriving every setting of a safety guarantee against major injuries.
Solution
The Solution
To meet these safety goals, we developed a protective wear detection model using deep learning techniques.
How It Work
Here's how it works
Deep Learning-Based Object Detection (YOLO)
Through the use of YOLO and CNNs, the model does a fantastic job at recognizing particular pieces of protective gear in real-time whether it be goggles, helmets, neck guards, etc effectively and accurately.
Comprehensive Gear Recognition
A variety of protective wear such as helmets, safety glasses, gloves, vests and jackets were taught to the model so that all mandatory safety aspects are included.
Real-Time Video Monitoring Integration
Using OpenCV and Python, the model was integrated into a live video feed, allowing continuous monitoring. The system is capable of real-time detection and can instantly alert supervisors of non-compliance.
Automated Alerts for Non-Compliance
When the model detects a worker without the required safety gear, it automatically triggers an alert, enabling supervisors to address the issue immediately, ensuring safety measures are upheld throughout the workday.
Automated Job Descriptions & Targeted Job Ads
It puts out accurate job specifications and leverages AI to produce job postings that reach the suitable candidate.
Smart Talent Sourcing & CV Matching
I searches career portals and social media for top candidates, and automatically matches resumes to job descriptions, ensuring only the most suitable candidates are shortlisted
Interview Assistance & Assessments
The platform helps with interview questions and provides
specialized tests to assess candidates’ skills.
Automated Offer & Onboarding
Facilitates the job offer to negotiation and final onboarding
process to its best capabilities
━ Key Features
-
Comprehensive Detection:
Our model is adept at identifying various protective wear items, ensuring comprehensive coverage and compliance monitoring. -
Real-Time Monitoring:
Integrated into live video feeds, the system provides instant alerts to supervisors, enabling immediate corrective actions. -
Versatile Use Cases:
The solution can be deployed at entry points to ensure workers are properly equipped before entering the site and used across the site to monitor compliance continuously. -
Mobile Notifications:
Supervisors receive real-time alerts on their phones, allowing them to address non-compliance issues swiftly and efficiently. -
Improved Safety Protocols:
By automating the detection process, the system minimizes human error and enhances overall site safety.
Technologies
Tools & Technologies
Feedback
Client Feedback
GearGuard AI has added a significant layer of safety to our sites. We now have a constant, reliable way to ensure workers are wearing the necessary safety gear without needing a supervisor to check each person individually.
Construction Industry Client
Results
GearGuard AI didn’t just streamline compliance; it actively reinforced safety culture on construction sites.
Deliverables:
Real-Time Gear Detection
Automated checks for safety equipment compliance in real time.
Instant Alerts
Immediate notifications to supervisors when non-compliance is detected.
Comprehensive Safety Monitoring
Coverage of essential safety gear to ensure regulatory compliance.
End-to-End Automation
It puts out accurate job specifications and leverages AI to produce job postings that reach the suitable candidate.
AI-Driven Tools
I searches career portals and social media for top candidates, and automatically matches resumes to job descriptions, ensuring only the most suitable candidates are shortlisted
Benefits:
Improved Site Safety
Reduced risk of accidents and enhanced compliance with safety protocols.
Operational Efficiency
Supervisors can focus on other tasks, confident that gear compliance is being monitored
Proactive Risk Management
Alerts allow for quick response, reducing potential hazards.
90% Less Manual Work
The platform reduces the proportion of manual tasks in the
recruitment process to a very minimum, thus allowing HR
professionals to focus on more strategic work.
Increased Efficiency & Accuracy
CV matching and candidate assessments through AI help the
platform avoid human intervention and shorter time-to-hire,
and decrease the possibility of hiring the wrong people.
Cost Savings
It is extensively cost-effective because, through automation, it eliminates burdensome tasks and thus is able to conduct
recruitments at relatively cheap costs
━ Conclusion
This project represents a significant leap forward in construction site safety management. By leveraging deep learning and real-time video analysis, we’ve created a system that ensures workers’ compliance with safety protocols, thereby reducing the risk of accidents. Our solution not only saves time and resources but also fosters a safer working environment. This project underscores the transformative potential of AI and computer vision technologies in enhancing operational safety and efficiency in the construction industry.
Why Us?
Why Us
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- 2108 N St, Sacramento, CA 95816, United States
- Office #301, 3rd Floor, Plot #80-C, Main Khayaban-e-Jami, Phase-VII, DHA Karachi
- +1 760-417-4769
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