👁️ Sentin-AI: Intelligent Microservices Surveillance System

Sentin-AI is a cloud-native, polyglot microservices architecture designed for intelligent surveillance. It leverages Python for computer vision (Object Detection) and Node.js for real-time alerting and orchestration. The system is containerized using Docker and designed for scalable deployment on Kubernetes or Serverless platforms like IBM Code Engine.

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🏗️ Architecture

The system follows a distributed microservices pattern, separating heavy computational tasks from high-concurrency I/O operations.

1. Sentin-Eye (Python/Flask):

   • Role: The "Brain" (Compute Bound).
   • Function: Processes image feeds/URLs using Computer Vision logic (OpenCV/TensorFlow).
   • Output: Returns JSON analysis of detected anomalies, objects, or threats.

2. Sentin-Alert (Node.js/Express):

   • Role: The "Messenger" (I/O Bound).
   • Function: Consumes analysis data, triggers logic-based alerts (simulated email/SMS), and manages WebSocket connections.
   • Performance: Handles high-throughput notification requests asynchronously.

3. Frontend Dashboard:

   • Role: The "View".
   • Function: Visualizes the live status and logs incoming alerts.

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🚀 Key Features

• Polyglot Design: Demonstrates the ability to integrate distinct languages (Python & Node.js) in a single ecosystem.
• Containerized: Fully Dockerized services ensuring consistency across Development and Production environments.
• Restful Communication: Services communicate via standard HTTP/JSON APIs.
• Scalable Architecture: Stateless design ready for horizontal scaling on Kubernetes (K8s) or IBM Code Engine.

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🛠️ Tech Stack

Component	Technology	Description
Service A	Python 3.9+ / Flask	Backend for AI Logic & Image Processing.
Service B	Node.js 18 / Express	Backend for Alert Orchestration & Real-time I/O.
Frontend	HTML5 / JavaScript	Simple

2. Run with Docker Compose

We use Docker Compose to spin up the entire ecosystem (Python Service + Node Service) locally with a single command.

docker-compose up --build

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3. Access the Services

Once the containers are running, you can access them at:

• Python AI Service: http://localhost:5000
• Node.js Alert Service: http://localhost:3000
• Dashboard: http://localhost:8080 (If configured)

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📡 API Endpoints

🧠 Service A: Sentin-Eye (Python)

POST /analyze

Description:
Analyzes an image for threats.

Input:

{
  "image_url": "http://example.com/cam1.jpg"
}

Output:

{
  "threat_level": "High",
  "objects": ["person", "unattended_bag"]
}

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🚨 Service B: Sentin-Alert (Node.js)

GET /status

Description:
Health check to ensure the alert system is active.

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POST /trigger

Description:
Receives analysis data from the Python service and logs alerts.

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🗺️ Project Roadmap (Milestones)

The project is divided into 5 strategic milestones:

• MS1: Foundation – Project Architecture, Git Repository, and Folder Structure setup
• MS2: The Eye (Python) – Implement Flask server and Computer Vision logic
• MS3: The Alert (Node.js) – Implement Express server and notification logic
• MS4: Containerization – Create Dockerfiles and Docker Compose orchestration
• MS5: Cloud Deployment – Deploy services to IBM Cloud Code Engine and test public endpoints

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👤 Author

Hammad Ibrahim
Software Engineer | DevOps Enthusiast | Python Backend Developer

Building scalable, automated, and intelligent backend systems.

🔗 LinkedIn Profile | GitHub Profile

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📜 License

This project is licensed under the MIT License — see the LICENSE file for details.