Smart Law Enforcement Solution

Smart Law Enforcement Solution

Real-Time Detection, No Violations Go Unnoticed

The Smart Law Enforcement Solution uses AI and IoT. It automatically detects traffic violations and generates real-time reports, helping agencies quickly identify issues and improve city management. It supports centralized deployments. All data is managed in one location. It also supports distributed deployments, where data is managed across multiple locations. The system connects via APIs. These interfaces let different software communicate with cloud platforms or control centers for real-time data, remote monitoring, and decision analytics.

The system boosts efficiency and accuracy by automating violation detection, data collection, evidence generation, and case handling. With both real-time and historical data, enforcement agencies can pinpoint hotspots. They can understand traffic patterns and make confident, strategic, data-driven decisions. This enhances urban management.

Solution Advantages

Smart Law Enforcement Solution

 

  • AI-Powered Video Recognition

    Automatically identifies vehicles, violations, and human activities using advanced AI technology, generating high-precision visual evidence and reducing manual workload.

  • Real-Time Violation Detection & Notification

    Instantly detects traffic violations and reports them through cloud or traffic control platforms, greatly improving enforcement responsiveness.

  • Automated Case Management

    Automates the workflow from violation record generation to case processing, improving efficiency and accuracy while minimizing human error.

  • Flexible Deployment & Scalability

    Supports centralized or distributed architectures, easily integrates with existing traffic control or cloud systems, and enables cross-regional data sharing and management.

Solution Diagram

Centralized Architecture

Field Side

In a centralized architecture, front-end cameras are responsible for capturing video, but do not perform any computation. All video streams are transmitted over the network to the central backend servers.

The field layer is responsible for:

  • Real-time video capture
  • Collecting license plate images and violation evidence
  • Uploading video streams to the data intelligence center
( NET WORK )

Data Center Side

All AI processing, violation detection, and evidence comparison are performed at the data center.

The data intelligence center is responsible for:

  • Centralized video analysis (AI violation detection)
  • License plate recognition and vehicle database matching
  • Violation event creation and evidence retention
  • Multi-intersection video management and long-term storage
  • Providing APIs to traffic control centers and cloud platforms
( API NETWORK)
Traffic Control Center
Cloud

Distributed / Edge Architecture

Field Side

In a distributed architecture, the field layer includes an Edge AI analysis device, allowing AI inference to be performed directly on-site, reducing bandwidth consumption.

The field layer is responsible for:

  • Real-time AI violation detection (processed on the Edge device)
  • License plate recognition
  • Capturing images/videos as evidence
  • Sending only “events + evidence” back to the center
( NET WORK )

Data Center Side

The center performs final event aggregation, auditing, and multi-intersection management.

The data intelligence center is responsible for:

  • Aggregating AI results from each intersection
  • Evidence storage and event management
  • Integration with police systems/traffic control centers
  • Unified management across multiple intersections and city-wide deployments
( API NETWORK )
Traffic Control Center
Cloud

 

Application Fields

Urban Roads & Main Arteries

Monitors and enforces traffic violations such as red-light running, speeding, and illegal parking, ensuring safer roads.

Traffic Hubs & Parking Management

Supervises parking compliance, supporting smart parking systems and vehicle flow control.

Campuses, Industrial Parks & Public Spaces

Prevents unauthorized entry, reckless driving, or illegal lane occupation, enhancing public and campus safety.

Intelligent Traffic Management

Integrates violation hotspot analysis and traffic flow statistics to support policy development and traffic improvement strategies.