Wait! Before You Go…
Let Aviox Technologies give your idea the edge it deserves — with a free:
- 🚀 Smart Project Blueprint
- 💰 Accurate Cost & Resource Estimate
- 📅 Launch Timeline Strategy
Aftom-Ai is an intelligent surveillance automation platform designed to detect violations captured through CCTV cameras using machine learning and real-time data streaming.
Client
Aftom-AI
Industry
Streaming
Project Overview
Aftom-Ai is an intelligent surveillance automation platform designed to detect violations captured through CCTV cameras using machine learning and real-time data streaming. The system identifies abnormal or rule-breaking activities (such as unauthorized access, restricted zone entry, safety violations, etc.) and instantly notifies the respective CCTV system owner.
The solution leverages machine learning for object and behavior detection, while real-time communication is facilitated through Apache Kafka and WebSockets. This enables immediate event alerts and live monitoring with near-zero latency.
Objective
- Automate surveillance monitoring to reduce manual intervention.
- Detect and classify violations in real-time using ML models.
- Send instant alerts to CCTV camera owners for quick response.
- Provide a scalable microservice architecture to handle multiple camera feeds efficiently.
Development Approach
- Implemented microservices to ensure each module is independently scalable.
- Used Kafka as a distributed event streaming platform for high throughput.
- Real-time client updates handled through WebSockets.
- Deployed services on AWS with containerization for flexible scaling.
Project Approaches
Our team built effective solution for Aftom AI
Violation Detection Using ML Models: Machine learning models analyze live CCTV feeds. Detects behavior and event patterns indicating violations. Supports multiple camera inputs simultaneously.
Real-Time Notification System: Uses Apache Kafka for streaming event data between services. WebSockets enable live push notifications to users. Alerts include violation type, snapshot, timestamp, and camera ID.
Owner Dashboard: Live camera feed preview and event timeline. View logs of past violations with searchable and filterable UI. Real-time alerts displayed instantly without page refresh.
Scalable Microservice Architecture: Each processing stage (detection, analytics, notification) runs as an independent service. Deployment-ready with Docker and compatible with AWS cloud infrastructure.
Solution Aviox Built for Aftom AI
This approach focused on keeping things simple, reliable, and ready to grow with Aftom AI needs.
Technologies
Tech Stack
React JS
Front End
Python, Django
Back End
Firebase
Data Storage
Kafka
Message Broker
AWS
Cloud & Oops
Impact & Results
Automated Surveillance Monitoring
Reduced manual workload by automating the review of surveillance footage.
Faster Incident Response
Improved reaction time with real-time violation detection and instant alert notifications.
Centralized Security Oversight
Enhanced visibility and control through an integrated web-based monitoring dashboard.
Scalable and High-Performance System
Designed to efficiently manage large-scale camera networks and high data volumes.