City Police Department Intelligent Video Analytics System

📋 Project Overview

We developed an AWS cloud architecture-based police body camera intelligent analysis system for a city police department, aimed at automating the processing of massive law enforcement videos and achieving efficient privacy protection and evidence management. The system adopts an event-driven serverless architecture, combining Amazon Rekognition AI vision services and OpenCV image processing technology to achieve fully automated workflow from video upload to privacy processing. Through multi-step workflows orchestrated by AWS Step Functions, the system can precisely identify faces in videos and perform blurring processing, protecting citizen privacy while maintaining the evidentiary value of law enforcement videos, providing innovative technical solutions for public safety digital transformation.

🚀 Key Features

Core Implementation

• Event-Driven Automated Processing: Serverless architecture based on AWS S3 event triggers, automatically monitoring and processing newly uploaded law enforcement videos
• Amazon Rekognition Face Detection: Utilized enterprise-grade AI vision services for high-precision face recognition and position marking
• OpenCV Privacy Protection Processing: Intelligent blurring of detected faces through computer vision technology, ensuring privacy compliance
• AWS Step Functions Workflow: Orchestrated complex multi-step processing workflows, supporting state management and exception handling
• Docker Containerized Lambda: Supported serverless computing with large dependency packages, ensuring image processing performance and stability

Technical Highlights

• AWS CDK Infrastructure as Code: Achieved version control and consistent deployment of cloud resources, supporting rapid replication across multiple environments
• Multi-format Video Support: Compatible with .mp4, .mov and other mainstream video formats, adapting to output standards of different law enforcement devices
• Real-time Status Tracking: Complete processing status monitoring and logging, ensuring traceability of each video's processing trajectory
• Scalable Cloud Architecture: Elastic architecture based on AWS managed services, supporting large-scale video processing requirements

💻 Project Detail

Our intelligent video analysis system is based on AWS cloud-native architecture, achieving automated privacy protection processing of law enforcement videos:

1. Event-Driven Trigger Mechanism:

2. Police body camera videos automatically uploaded to designated Amazon S3 storage buckets

3. S3 event notifications trigger AWS Step Functions state machine to start processing workflow

4. Supported both batch processing and single file processing modes, adapting to different business scenarios

5. Intelligent Face Detection Analysis:

6. StartFaceDetect Lambda Function: Called Amazon Rekognition StartFaceDetection API to begin asynchronous face detection tasks

7. Supported deep analysis of high-resolution videos, accurately identifying faces under various angles and lighting conditions

8. Automatically generated JobId for subsequent status queries and result retrieval

9. Status Monitoring and Management:

10. CheckStatus Lambda Function: Periodically checked Rekognition task execution status

11. AWS Step Functions Wait state implemented intelligent waiting, avoiding unnecessary API calls

12. Supported timeout handling and retry mechanisms, ensuring reliable task completion

13. Precise Timestamp Extraction:

14. GetTimestamps Lambda Function: Extracted precise timestamps and position coordinates of face appearances from Rekognition results

15. Handled complex situations with multiple faces, ensuring all sensitive information was marked

16. Generated structured face data, providing accurate input for subsequent processing

17. OpenCV Privacy Protection Processing:

18. BlurFaces Lambda Function: Used OpenCV library to perform Gaussian blur processing on detected face regions

19. Docker containerized deployment supported large image processing libraries like OpenCV
20. Maintained overall video quality and usability, precisely blurring only face regions

21. Output privacy-protected videos compliant with court evidence requirements

22. Cloud Architecture Infrastructure:

23. Used AWS CDK (Python) to implement Infrastructure as Code, ensuring deployment consistency and repeatability
24. Precise IAM permission control, ensuring secure access between services
25. CloudWatch monitoring and logging, providing complete system observability

📊 Project Impact

Revolutionary Law Enforcement Efficiency Enhancement:

• Automated video review work that traditionally required manual hours, saving hundreds of processing hours monthly for the police department
• Achieved 24/7 uninterrupted video processing capability, significantly improving processing speed and responsiveness of law enforcement videos
• Standardized privacy protection processes ensured all law enforcement videos underwent consistent compliance processing

Technical Innovation and Compliance Assurance:

• Successfully deployed to production environment and operated stably, handling actual law enforcement video processing tasks
• Received coverage from local news media, demonstrating positive application of AI technology in public safety
• Provided technical demonstration for police department digital transformation, promoting modernization of law enforcement processes

Cloud Architecture Scalability Validation:

• Serverless architecture achieved on-demand scaling, effectively handling fluctuations in video processing volume
• Adoption of AWS managed services reduced system maintenance costs and technical complexity
• Event-driven processing model improved resource utilization efficiency and cost-effectiveness

Social Value and Public Interest:

• Protected citizen privacy while maintaining evidentiary value of law enforcement videos
• Provided replicable technical solutions for similar needs of other law enforcement departments
• Promoted construction of law enforcement transparency and public trust

🛠️ Technology Stack

AI & Computer Vision:
  - Amazon Rekognition (Enterprise Face Detection)
  - OpenCV (Computer Vision Processing)
  - Face Detection API (Face Recognition Algorithm)
  - Image Processing (Image Processing Technology)

Cloud Infrastructure:
  - AWS CDK Python (Infrastructure as Code)
  - AWS Step Functions (Workflow Orchestration)
  - AWS Lambda (Serverless Computing)
  - Amazon S3 (Video Storage Service)

Serverless Computing:
  - AWS Lambda Python 3.7 (Function Computing)
  - Docker Lambda Layers (Containerized Deployment)
  - Event-driven Architecture (Event-driven Architecture)
  - Asynchronous Processing (Asynchronous Processing)

Video Processing:
  - Multi-format Support (.mp4/.mov video formats)
  - High-resolution Processing (High-resolution Video Processing)
  - Frame-by-frame Analysis (Frame-by-frame Analysis)
  - Privacy Blurring (Privacy Blurring)

Workflow Management:
  - State Machine (State Machine Management)
  - Error Handling (Error Handling Mechanism)
  - Retry Logic (Retry Logic)
  - Status Tracking (Status Tracking)

Security & Compliance:
  - AWS IAM (Identity Access Management)
  - Privacy Protection (Privacy Protection)
  - CloudWatch Monitoring (Monitoring Logs)
  - Audit Trail (Audit Trail)

Development & Deployment:
  - Infrastructure as Code (Infrastructure as Code)
  - Multi-environment Support (Multi-environment Support)
  - Automated Deployment (Automated Deployment)
  - Version Control (Version Control)

This project demonstrates innovative application of cloud-native architecture combined with AI vision technology in public safety, providing scalable enterprise-grade solutions for law enforcement digital transformation and privacy protection compliance.