Case Study
AI Threat Detection and Escalation
Real-time threat detection system across 20+ camera feeds, escalating critical threats via SMS and email alerts. Optimized backend with PostgreSQL and Redis caching, improving system throughput by 40%.
AI security surveillance
Project Snapshot
Role: Full-stack developer — backend optimization, threat logic, and dashboard development.
Tech stack details are outlined below.
Overview
Executed a real-time threat detection system across 20+ camera feeds, escalating critical threats via SMS and email alerts. The system features a Next.js dashboard for live visualizations and automated deployments via Kubernetes.
Technical highlight: Automated deployment using Docker and Kubernetes, reducing deployment errors by 50%.
The Result
Reduced response time by 25% for security personnel and established a robust, scalable surveillance pipeline.
The Problem
High-throughput video processing and low-latency escalation were required for real-time security across multiple feeds.
The Solution
Integrated YOLOv8 for detection and optimized the backend with Redis caching and PostgreSQL, achieving a 40% throughput improvement.
Tech Stack
Key Features
- Real-time detection across 20+ camera feeds.
- Automated SMS and email escalation for critical threats.
- Next.js dashboard for live visualization.