Suspicious Activity
Detection
Detect firearms, loitering, aggressive behavior, fence violation, maritime violations, etc., in real-time
Detect firearms, loitering, aggressive behavior, fence violation, maritime violations, etc., in real-time
Surveillance cameras have replaced physical monitoring methods in most places (schools, hospitals, government infrastructure, etc.). However, these systems cannot detect suspicions, abnormalities, and patterns based on available visual data. To prevent suspicious activities from causing any danger, there is a need to equip security cameras with ML-powered surveillance models.
Become lightning-fast and proactive in suspicion detection with our highly trained computer vision models
Our trained models can recognize objects with a TPR of 95% and FPR of up to 0.2%
Our ultra-fast processing gives lightning-fast real-time inferences and feedback (~30 frames per second).
Analyze images from video captures in a quick frame-by-frame manner without any distortion.
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I’m a paragraph. Click here to add your own text and edit me. It’s easy.I’m a paragraph. Click here to add your own text and edit me. It’s easy. Just click “Edit Text” or double click me to add your own content and make changes to the font.I’m a paragraph. Click here to add your own text and edit me. It’s easy.
I’m a paragraph. Click here to add your own text and edit me. It’s easy. Just click “Edit Text” or double click me to add your own content and make changes to the font.
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In your Azure marketplace portal subscription, deploy the hub service or CV solution you’re looking for and fill in the required details like; IoT hub name, Resource Group, and Azure subscription details.
Create and deploy the Azure Resource Manager (ARM) template, which is the interface for managing and organizing cloud resources, deployment manifest and install cameras.
After the deployment manifest is complete, execute the deployment on the host computer.
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Activity recognition systems are trained on a vast data set for each scenario. Based on movement in a particular area or a specific manner, these ML-powered solutions are capable of notifying security staff of possible abnormalities, risks, suspicions, and violations.
Our Azure web app lets you easily connect your surveillance camera and access activity detection scenarios as needed. We will deploy our code to your infrastructure with the help of the Azure Resource Manager template.
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.
Our ready-to-deploy models can be installed on your system with the help of ARM templates. After this, you can add and customize camera settings per the scenarios. Since our solution works with most consumer and commercial-grade cameras, you’ll likely not have difficulty using our services.
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.
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.
Our engineers work on various algorithms such as CNN, Yolo v5, Faster R-CNN, Mask-RCNN, Deepsort, etc.
We used multiple tools and frameworks, including Pytorch, Yolov5, Tensorflow, and many more, as per the project requirement.
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