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2025-10-10 12:32:54 Kirti: added Table content
Projects/Face Recognation/Document.md ..
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# Document
+ **Table of Contents**
+ 1. Introduction
+ 2. System Overview
+ 3. Architecture Design
+ 4. Component Design
+ 5. Data Flow
+ 6. Database Design
+ 7. API Design
+ 8. Security Architecture
+ 9. Integration Points
+ 10. Scalability & Performance
+ 11. Deployment Architecture
+ 12. Monitoring & Logging
+ 13. Disaster Recovery
+ 14. Technology Stack
+ 15. Non-Functional Requirements
+ 16. Risks & Mitigations
+ 17. Future Enhancements
+
+
+
+ ### 1.Introduction
+ **1.1 Purpose**<br>
+ This document provides a high-level design for a Multi-Tenant Face Recognition System that enables
+
+ businesses to integrate face recognition capabilities into their operations through a P2P (Peer-to-Peer)
+ architecture. The system allows multiple businesses to register, manage users, configure cameras, and receive
+ real-time recognition events.<br>
+ **1.2 Scope**<br>
+ The system covers:
+ Multi-tenant business management
+ User registration with multiple face images
+ Camera configuration and monitoring
+ Real-time face recognition and event processing
+ Unknown person detection and tracking
+ Access log management
+ API-based integration with external systems
+ Webhook-based event notifications
+ Security and authentication mechanisms<br>
+ **1.3 Definitions and Acronyms**<br>
+ Term Definition
+ P2P Peer-to-Peer - Decentralized architecture where businesses interact directly
+ API Application Programming Interface
+ RTSP Real-Time Streaming Protocol
+ RTMP Real-Time Messaging Protocol
+ UUID Universally Unique Identifier
+ HMAC Hash-based Message Authentication Code
+ ML Machine Learning
+ RPS Requests Per Second
+ SLA Service Level Agreement<br>
+
+ **1.4 References**<br>
+ Original System Diagram Document (Face Recognition.docx)
+ Database ERD and Schema
+ Industry standards for face recognition (NIST FRVT)
+ GDPR and data privacy regulations
+
+ #### 2. System Overview
+ **2.1 Business Context**
+
+ The system provides face recognition as a service to multiple businesses, allowing them to:
+ Register employees/users with facial biometric data
+ Monitor access through camera-enabled locations
+ Receive real-time alerts on recognition events
+ Track unknown persons for security
+ Generate access reports and analytics<br>
+ **2.2 Key Stakeholders**<br>
+ Stakeholder Role Interests
+ Business Administrators Configure system, manage users Easy integration, reliable service
+ Security Personnel Monitor unknown persons Real-time alerts, accurate detection
+ Employees/Users Subjects of recognition Privacy, accuracy
+ System Administrators Maintain infrastructure Stability, performance
+ API Consumers External system integration API reliability, documentation<br>
+
+ **2.3 High-Level Requirements**<br>
+ Functional Requirements
+ FR-001: Support multiple independent businesses (multi-tenancy)
+ FR-002: Allow users to register with 3-5 face images
+ FR-003: Support IP camera integration via RTSP/RTMP
+ FR-004: Perform real-time face detection and recognition
+ FR-005: Track and store unknown persons
+ FR-006: Generate access logs with timestamps
+ FR-007: Provide REST API for external integration
+ FR-008: Send webhooks for real-time event notifications
+ FR-009: Support role-based access control
+ FR-010: Provide camera status monitoring
+ Non-Functional Requirements
+ NFR-001: Process recognition events within 500ms
+ NFR-002: Support 99.5% uptime SLA
+ NFR-003: Handle 1000+ cameras per business
+ NFR-004: Scale to 100+ concurrent businesses
+ NFR-005: Maintain recognition accuracy > 95%
+ NFR-006: Store data with encryption at rest
+
+ NFR-007: Provide audit trails for all operations
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