Real-Time Suspicious Activity Detection
Highly trained Vision-AI models for suspicious activity detection
Experience Visionify's Real-time, Precise, and Proactive Detection of Suspicious Activities:
- Flawless Integration that blends into your current security system
- Instant Activity Recognition: that pinpoints suspicious activities, irregularities, and unusual behavioral cues
- Comprehensive Crowd Surveillance for crowd dynamics, identifying any anomalies, risks, or compliance breach
- Maintain real-time surveillance and receive immediate alerts upon the detection of suspicious activities
Key Features
Empower Workplace Safety through Seamless Deployment, Continuous Intelligence, Customized Models, and Intuitive Tools
Ready to Deploy Models
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
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.
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.
Use Cases
Suspicious Activity Detection for Firearm/Knife
The firearm Detection model identifies the presence of firearms and knives. Upon weapon identification, the system triggers alarms and notifies security personnel and authorities about the incident.
Suspicious Activity Detection for Loitering
Visionify’s Loitering Detection model generates alerts based on the movement of objects and persons. It can count loiters, detect line crossing, identify suspicions, resolve queues, etc.
Suspicious Activity Detection for Aggressive Behavior
Our analytics software detects sound patterns related to compulsion, anger, verbal aggression, or fear and alerts the security personnel so the physical or verbal aggression can be prevented.
Suspicious Activity Detection for Solicitation
Identify solicitation activities that give undue advantage to other competitors. Our solicitation detection model integrated with your cameras can ensure minimal solicitation and distribution.
Suspicious Activity Detection for identifying Theft
Make your workplace or stores theft-proof by installing surveillance cameras equipped with smart sensors and connected with AI-analytics. Get real-time alerts in case of theft detection.
Suspicious Activity Detection for Vandalism
Identify people involved in workplace vandalism through our Vision-AI solution. Penalize workers/people involved, take suitable actions, and recover losses, based on available footage.
FAQs
Learn more about
VisionAl Platform
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.
