Dynamic Web Lab
AI-Powered Video Analytics — System Online

AI Video Intelligence for Dubai Smart Cities & UAE Retail

Real-time CCTV analysis for Dubai and the UAE. YOLOv8-powered theft detection, zone monitoring, and behavior analysis. Open source, edge-ready.

COCO
80+
Object Classes
YOLOv8 detection categories
Live
30 FPS
Real-Time Processing
Live video stream analysis
Fast
<50ms
Per-Frame Latency
Edge-optimized inference
Free
MIT
Open Source
Free for commercial use
Core Capabilities

Powerful Detection Capabilities

Six core modules powered by YOLOv8 and ByteTrack for comprehensive video intelligence.

Person Detection & Counting

Accurately detect and count people in real-time using YOLOv8. Monitor foot traffic, occupancy, and crowd density across zones.

Theft Detection

AI-driven theft detection identifies suspicious behaviors and missing items. Instant alerts to security personnel.

Zone Monitoring

Define custom zones and get real-time counts of people entering, exiting, or loitering in restricted areas.

Behavior Analysis

Pose estimation and action recognition to detect unusual behaviors like fighting, falling, or running.

Face Detection

Detect and recognize faces in video streams. Enable access control and person identification workflows.

Edge Deployment

Export models to ONNX for running on edge devices. Low-latency inference without GPU dependency.

Real-World Deployments

Built for Real-World Security

Deploy Rasd across industries to automate surveillance and improve response times.

Retail Security

Dubai Malls

Prevent shoplifting, monitor store layouts, and optimize product placement in Dubai malls and UAE retail outlets.

Smart Cities

Dubai & Abu Dhabi

Manage traffic flow, monitor public spaces, and enhance urban safety across Dubai and Abu Dhabi with AI-powered surveillance.

Public Safety

UAE Events

Detect crowd disturbances, unattended bags, and emergency situations at UAE exhibitions, events, and public venues.

Building Security

UAE Offices

Control access, detect intruders, and monitor restricted areas in Dubai office complexes, free zones, and facilities.

Architecture

Processing Pipeline

A modular architecture from video ingestion to real-time result delivery.

Video Ingestion
RTSP / MP4 / Webcam
YOLOv8 Detection
80+ Object Classes
ByteTrack
Multi-Object Tracking
Person Re-ID
Identity Matching
Theft Detection
Alert System
Zone Analytics
Entry/Exit Counting
Dashboard & API
Real-Time Results
30 FPS
Processing Speed
94.2%
Detection Accuracy
97%
Tracking Consistency
<50ms
Latency

Built With

Powered by industry-standard ML frameworks and production-grade infrastructure.

Python 3.12+YOLOv8FastAPISQLitePostgreSQLONNX
FAQ

Frequently Asked Questions

Everything you need to know about getting started with Rasd.

QWhat video formats does Rasd support?

Rasd supports RTSP streams, MP4 files, and any video format compatible with OpenCV. It can process live CCTV feeds via RTSP or uploaded video files.

QDo I need a GPU to run Rasd?

No. Rasd runs on CPU with YOLOv8n (nano model). For higher accuracy, a GPU with CUDA support is recommended but not required. Rasd also supports edge deployment via ONNX.

QCan Rasd integrate with existing CCTV systems in Dubai?

Yes. Rasd connects to any RTSP-compatible CCTV camera. It works with Hikvision, Dahua, Axis, and other brands commonly used in Dubai and UAE buildings.

QIs Rasd production-ready for UAE businesses?

Yes. Rasd is MIT licensed, production-ready, and deployed in retail and smart city environments. It includes a web dashboard, API, and database storage.

Free & Open Source — MIT License

Free & Open Source

Rasd is fully open source under the MIT license. Deploy it yourself at no cost, or get enterprise support for production environments.

UAE PDPL
SOC 2 Type II
GDPR
FTA Ready
CCPA