Detection of Personal Protective Equipment

Business challenges

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Safety hazards: Workers who do not wear PPE are at a higher risk of injuries, which can lead to increased workers' compensation claims and potential liability for the company.

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Reduced productivity: When workers neglect to wear PPE, it can lead to increased downtime due to injuries, which can reduce productivity and increase costs.

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Non-compliance with regulations: Not wearing PPE can put the company at risk of non-compliance with OSHA (Occupational Safety and Health Administration) regulations and penalties, which can be costly.

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Loss of reputation: Neglecting to wear PPE can be perceived as a lack of commitment to safety and can damage the company's reputation, potentially losing future business.

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Decreased moral: When workers see their colleagues not wearing PPE, it can lower the moral of the team and create an unsafe working environment.

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Increased training costs: When employees don't wear PPE, it can lead to increased training costs as more training may be needed to ensure compliance and safety.

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Legal Liabilities: If an incident occurs where a worker is not properly protected by PPE, the company may face legal liabilities for any injuries or illnesses that occur.

Solution Overview

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Workplace injuries can result in both personal loss and financial loss for the company.

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Safety protocols, such as PPE requirements, are often not followed, and traditional measures like safety training, manual monitoring, and safety billboards are not very effective in preventing violations.

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OptiSol has developed an accurate computer vision intelligence model that can detect PPE violations, such as hard-hats, reflective vests, and goggles, at construction sites and other industries to improve workplace safety and compliance with regulations.

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This deep learning-based computer vision solution detects and sends alerts when personnel are non-compliant, ensuring on-site safety.

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Machine learning models using TensorFlow or Yolo can be trained using annotated data through ``transfer learning`` techniques.

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These models can be optimized for use with hardware accelerators, such as Intel OpenVino or Nvidia TensorRT, to run on low-cost, low-power SBCs (Single Board Computers).

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These models can be hosted on cloud platforms, such as AWS, Azure, or Google, to easily scale and run on video streams from IP cameras, including regular CCTV cameras.

Business Impact

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Improved Safety: Improves safety on the construction site, reducing the risk of injuries and accidents.

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Increased Compliance: Helps to ensure compliance with safety regulations and industry standards, reducing the risk of penalties and fines.

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Reduced Costs: Helps to reduce costs associated with injuries, accidents, and non-compliance.

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Increased Productivity: By reducing the risk of injuries and accidents, the computer vision solution can help to increase productivity by minimizing downtime and allowing workers to focus on their tasks.

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Improved Reputation: By demonstrating a commitment to safety and compliance, the computer vision solution can help to improve the company's reputation and attract new business.

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Scalability: Easily scaled across multiple sites, improving safety and compliance across the entire organization.

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Real-time monitoring: Monitors the site in real-time and send alerts immediately, allowing for quick response and corrective action.

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Reduced human resource needs: With computer vision solution, human resource needs to monitor safety protocols are reduced, which can save costs and increase efficiency.

Sample Videos

Technology Stack

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