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Related Concept Videos

Personal Protective Equipment01:20

Personal Protective Equipment

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Personal protective equipment (PPE) is unique clothing or equipment worn by an employee to minimize or prevent exposure to infectious agents. PPE creates a barrier between the employee and the infectious materials. PPE must be readily available in the patient care area. PPE includes gloves, gowns and aprons, masks and respirators, goggles, face shields, shoes, and headcovers:
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PPE Use in Healthcare Settings I: Donning01:22

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Donning PPE must be completed before contact with the patient. This process protects from infectious agents. The sequence and action included in each donning are critical, and the steps must be systematic to avoid exposure to pathogens. The institutional policy also needs to be followed while donning PPE. The pre-donning preparations are gathering equipment, inspecting the PPE equipment for tears, holes, or damage, removing jewelry, removing any garments below the elbows, and tying the hair...
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PPE Use in Healthcare Settings II: Doffing01:10

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The sequence of removing or doffing PPE starts with the gloves, as they are the most contaminated. Next is removal of the face shield or goggles, as they would interfere with removing other PPE. Then remove the gown, followed by the mask or respirator. Perform hand hygiene between steps if hands become contaminated and immediately after removing all PPE. Generally, the outside front and sleeves of the isolation gown, the goggles or the mask, the respirator, and the face shield are contaminated.
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Survey Safety01:28

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Surveying near highways, rough terrain, or power lines involves significant risks. Working along highways is particularly dangerous and requires the use of warning signs and flagmen. It is safest to avoid working directly on roads and use offsets whenever possible. When highway work is unavoidable, it must follow all safety guidelines. Surveyors should wear bright clothing, such as orange reflective vests, to ensure visibility to motorists, coworkers, and hunters. In construction zones, wearing...
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Transmission-based Precautions II: Airborne and Protective Environment01:25

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Transmission-based precautions are for patients infected or suspected to be infected (or colonized) with organisms posing a significant risk to others. The transmission precautions include airborne and protective environment precautions.
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Standard Precaution01:26

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Standard precautions are the minimum infection control safeguards used while caring for all patients, irrespective of their disease condition. They help prevent the spread of common infectious microorganisms to healthcare workers, patients, and visitors in all healthcare settings.
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Intelligent Platform Based on Smart PPE for Safety in Workplaces.

Sergio Márquez-Sánchez1,2, Israel Campero-Jurado3, Jorge Herrera-Santos1

  • 1BISITE Research Group, University of Salamanca, Calle Espejo s/n, Edificio Multiusos I+D+i, 37007 Salamanca, Spain.

Sensors (Basel, Switzerland)
|July 24, 2021
PubMed
Summary

Smart Personal Protective Equipment (PPE) integrates AI and edge computing to enhance worker safety. This system uses wearable technology to predict and notify about workplace anomalies, significantly improving occupational health.

Keywords:
AIoTDeeptechanomaly detectionartificial intelligenceedge computingmachine learningsmart PPE

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Area of Science:

  • Occupational Health and Safety
  • Artificial Intelligence
  • Wearable Technology

Background:

  • Workers spend a significant portion of their lives at work, necessitating enhanced safety measures.
  • Traditional workplace equipment requires adaptation to integrate new technologies for improved safety and connectivity.
  • Smart Personal Protective Equipment (PPE) and wearable technologies offer potential for real-time data extraction to mitigate workplace risks.

Purpose of the Study:

  • To propose an architecture for smart PPE that enhances worker safety using AI and edge computing.
  • To develop a system capable of early prediction and notification of environmental anomalies in the workplace.
  • To improve the overall safety and reduce occupational illnesses and accidents.

Main Methods:

  • An architecture utilizing three smart PPE devices: helmet, bracelet, and belt.
  • Processing collected worker and environmental data using artificial intelligence (AI) techniques via edge computing.
  • Employing a combination of models including convolutional neural networks, long short-term memory, and Gaussian Models, with a support vector machine for final decision-making.

Main Results:

  • The proposed system effectively processes information from smart PPE using AI and edge computing.
  • An ensemble of AI models was utilized, with a support vector machine weighting their outputs.
  • The system achieved an area under the curve (AUC) of 0.81 in anomaly detection.

Conclusions:

  • The developed smart PPE architecture effectively enhances worker safety through early anomaly detection.
  • AI and edge computing integrated into wearable devices provide a robust solution for improving occupational health.
  • The system demonstrates significant potential in reducing workplace accidents and occupational illnesses.