PPE Detection

Prevent Workplace Injuries and Occupational Hazards with Vision AI powered real-time PPE Detection

PPE Detection, PPE Compliance, PPE Violation Detection

With Visonify’s Fully-Automated PPE detection, achieve complete PPE compliance

Key Features

Empower Workplace Safety through Seamless Deployment, Continuous Intelligence, Customized Models, and Intuitive Tools

Instant Deployment

Immediate Deployment with Zero Additional Training. Seamlessly integrate into your existing systems while Prioritizing Security and Privacy on your Premises.

Continuous Intelligence and Data analysis

Post-deployment, our solutions evaluate elements such as lighting, brightness, contrast, and weather conditions. They perpetually monitor and self-tune to changes, guaranteeing heightened accuracy and precision.

Custom models

Tailor-made models for your workplace that adapts to your business challenges. Designed to cater unique requirements, our team ensures you receive a solution that perfectly suits your environment.

User-friendly Web App that makes everything simple

Keep a pulse on your workplace with our advanced web app, a user-centric platform with intuitive interface that enables users to easily navigate and utilize our tools.

How it works

Streamlined Implementation and Real-Time EHS
Monitoring for Enhanced Workplace Safety

Use your existing cameras

You can augment your existing camera infrastructure. No new Installation needed. Our solutions easily integrate with existing camera infrastructure providing an efficient and cost-effective approach.

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Pick and Choose from 60 Prebuilt VisionAi apps

Choose from our extensive library of over 60 prebuilt Vision AI apps to suit your unique safety needs. Each app can be effortlessly added to your existing camera infrastructure, providing immediate enhanced safety capabilities.

Manage Your Workplace with Real-Time Alerts and Notifications

Configure alerts and notifications through our web-app and stay in the loop with real-time notifications of events. Our cloud-based platform ensures  easy access to video feeds, enabling seamless incident management and efficient response times.

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Use Cases

PPE Detection for Construction Sites

Real-time Monitoring to ensure workers are wearing appropriate safety gear, such as hard hats, safety glasses, and high-visibility vests.
Slip and Fall detection at construction sites.
PPE detection for working at heights.

PPE Detection for Working at Heights

Detect usage of Personal Fall Arrest System is used (PFAS) like a full body harness for wok-sites that are situated at heights along with other anti-fall protective gear.

PPE Detection for Manufacturing Plants and Factories

Monitor PPE compliance in factory workers. Detect usage of safety gear along with other wearables like hair-nets, face masks, etc, that keep factory products contaminant-free.
PPE Detection for manufacturing plants
PPE Detection for Hospitals

PPE Detection for Hospitals and bio-labs Hospitals

Detect and Monitor usage of gloves, gowns, masks, respirators, hazmat and PPE suits for medical staff, biochemists and lab workers.

PPE Detection for Public Places

Detect usage of face masks in Public Transportation, Malls, Offices and other retail places to maintain a safe environment in public spaces.
PPE Detection in working places.
Enhanced safety with PPE detection

Custom Use-Cases

Do you have special requirements when it comes to PPE and safety gear detection? If yes then get in touch with our team to create a custom solution.

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Test our VisionAI system quickly PyPI package.
On-prem installation available through Azure ARC Managed App

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Learn more about
VisionAI Platform

How accurate is the PPE (Personal Protective Equipment) detection model in identifying whether individuals wear the required safety gear?

Our PPE detection model in the VisionAI toolkit is designed to deliver high accuracy. Through the use of advanced computer vision algorithms, the system not only detects and recognizes specific PPE items such as hard hats, reflective vests, safety goggles, utility gloves and safety masks but also incorporates person identification and tracking capabilities. This integration prevents the system from generating multiple notifications for the same person in different scenarios. Extensive training and testing have been conducted to ensure reliable performance, resulting in accurate identification of PPE usage with a high degree of precision.

What underlying technology is used in your VisionAI toolkit for workplace safety applications?

Our VisionAI toolkit for workplace safety applications is built on state-of-the-art computer vision and deep learning technologies. It leverages several advanced deep neural network architectures as backbone and performs conventional ML applications such as Object Detection/Recognition, Keypoint detection, image segmentation, activity prediction and recognition. This enables our toolkit to accurately analyze video feeds in real-time, send out alerts and provide actionable  insights for all scenarios.

What deployment options do you provide for integrating the VisionAI toolkit into existing workplace safety systems?

We offer flexible deployment options to integrate the VisionAI toolkit into existing workplace safety systems. Our toolkit can be deployed on-premises, leveraging the computational power of local servers or can be embedded at the edge (in-camera). Alternatively, it can be deployed on Azure, taking advantage of the scalability and accessibility offered by Microsoft’s cloud platform.

Does Visionify offer activity detection analytics?

With Visionify, it is easy to set up the defined area and predetermine what and how users receive alerts. As a result, you will get a detailed insight into various KPIs on your mobile app.

Can your solutions be customized or tailored to specific industries or unique safety requirements?

The pre-trained apps available in the VisionAI toolkit generally work out of the box. However, we also offer customized solutions tailored to your specific needs, provided as a consulting service through Azure Marketplace. Our team of experts can closely collaborate with you to tailor our VisionAI applications to address your unique requirements.

Does the VisionAI toolkit support integration with existing safety monitoring systems?

Yes, our VisionAI toolkit is designed to support seamless integration with existing surveillance camera systems. Our toolkit can communicate and trigger actions based on detected events or anomalies by leveraging APIs and standard protocols. This allows instantaneous responses like sending notifications via email or phone to relevant stakeholders.

Which activity detection solutions do you offer currently?

At Visionify, we offer multiple solutions which find their application in several industries. Early fire detection, Leakage detection, Exclusion zone detection, Mobile phone detection, PPE detection, Slip and Fall detection, Smoking and vaping detection are some of the popular solutions organizations across industries implement.

Can the VisionAI toolkit be deployed in large-scale environments?

Yes, the VisionAI toolkit is designed to be scalable and can be deployed in large-scale environments like industrial or manufacturing facilities where a high volume of data and many cameras or devices are involved. It can handle simultaneous processing from multiple cameras and support distributed architectures.

What is the computational resource requirement for running the VisionAI toolkit, and does it support real-time processing?

The computational resource requirement for running the VisionAI toolkit depends on various factors such as the number of cameras, video resolution, desired frame rate, and the specific applications in use. Our toolkit is optimized for efficient resource utilization, enabling real-time processing on capable hardware configurations. We provide detailed system requirements and guidance to ensure that your infrastructure meets the necessary specifications for seamless real-time processing and optimal performance.

What are the key components of your object detection solution?

Our object detection solution has three main components i.e., dual properties (object classification and localization), speed for real-time detection, and multiple spatial scales and aspect ratios.

Which object detection algorithms do you work with?

Our engineers work on various algorithms such as CNN, Yolo v5, Faster R-CNN, Mask-RCNN, Deepsort, etc.

Which tools or frameworks do you leverage to build your working model?

We used multiple tools and frameworks, including Pytorch, Yolov5, Tensorflow, and many more, as per the project requirement.