Life science organizations are looking for ways to monitor Personal Protective Equipment (PPE) compliance more efficiently and detect missing PPE. Occupational Safety and Health Act (OSHA) Personal Protective Equipment (PPE) standards (in general industry, 29 CFR 1910 Subpart I) require the use of gloves, eye and face protection, and respiratory protection. Continuous monitoring for PPE compliance performed manually strains safety engineers in life science manufacturing and QC lab environments. However, scaling an automated solution requires automation of detection and notification and creating, deploying, and managing this automation requires weeks to months of IT staff time as well as AI and Machine Learning expertise. Finally, PPE ensembles may vary for different workers and additional PPE may include medical/surgical gowns, fluid-resistant coveralls, aprons, or other disposable or reusable protective clothing.
PPE compliance has to be constantly monitored
Automated PPE detector for work environment safety
Real-time CCTV based automated detection and reporting on PPE compliance
Automated PPE detection for work environment safety allows organizations to leverage AI powered vision to identify PPE use in the work environment using real-time CCTV stream. Powered by computer vision and image analysis on AWS, the solution processes live video footage from cameras to detect and classify custom cases of PPE non-compliance in real-time.Capable of detecting different types of protective attire, this solution automatically sends safety violation reports to the designated safety team. The solution is also capable of body temperature monitoring, even in crowded areas, if there are cameras with thermal imager function. If the solution identifies people with temperature higher than established normal, it automatically alerts to responsible personnel.
The solution serves as an assistant for the employee safety team, saving effort spent on monitoring PPE compliance and identifying violations. It can also measure body temperature through cameras. Using CCTV stream, the solution automatically identifies the absence of 4 object types on a person: medical coat, safety glasses, gloves, and mask. On client’s request other custom objects can be added to the solution.When the absence of the target object is noticed, the solution notifies the safety team responsible for PPE compliance. This product can provide significant results in reduction of PPE non-compliance rule by up to 90%. This provides an increased safety for employees and visitors.
Automated PPE detection can be used by:
Automating PPE compliance for your business in numbers
ONE instead of many
Centralized, connected camera-based automated monitoring lets you reduce the burden of manual safety monitoring
24/7 real-time monitoring
Real-time, around the clock analytics. Compatible with existing high-resolution cameras
up to 80%
Highly automated safety monitoring processes
Real-Time Video Processing and Analytics
The PPE Detector makes it easy to instantly detect and report on cases of PPE violations as it captures and processes CCTV streams for real-time analysis. The solution detects various PPE objects and, if a the absence of any of them is found,it sends an alert to a safety engineer.
Compatible with any high-resolution camera
Powered by computer vision and image analysis, the solution processes live video footage from cameras mounted on premises to detect and classify cases of PPE non-compliance in real-time. Camera Specifications. Any modern IP camera with minimal parameters: Resolution - from 2 MP, Video resolution - from 1920 × 1080 pixels, Video Format - H.264, Max FOV: 80 degrees, Color.
4 Object Classes Detection on person: lab coats, safety glasses, gloves, mask
On the one hand, these classes ensure employee safety in hazardous environments. On the other hand, they protect laboratory substances from micro-contaminants and particles that can be brought from the outer environments. On client’s request any other object may be added to the solution.
Body temperature monitoring
The detector automatically measure body temperature, if cameras have thermal imager function. If a high temperature is detected, the notification is automatically sent to responsible manager.
1. Users manage cameras by UI. UI calls backend for management of webcams/users and view collected alerts.
2. Backend calls workers for generation of new video streams.
3. Workers get video streams from cameras.
4. Workers send images from video streams to Amazon SageMaker model endpoint for detection of PPE violations.
5. Worker send every image with violation to Backend for storing (6,7).
8. UI gets URL for every video stream with violations and calls workers to view.
9. Amazon SES used for user password management and sending reports.