Document

Table of Contents

Introduction
System Overview
Architecture Design
Component Design
Data Flow
Database Design
API Design
Security Architecture
Integration Points
Scalability & Performance
Deployment Architecture
Monitoring & Logging
Disaster Recovery
Technology Stack
Non-Functional Requirements
Risks & Mitigations
Future Enhancements

1.Introduction

1.1 Purpose
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.
1.2 Scope
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
1.3 Definitions and Acronyms
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

1.4 References
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
2.2 Key Stakeholders
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

2.3 High-Level Requirements
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