Enterprise-Exclusive AI Productivity Solution

Manufacturing Solutions

Edge AI-powered intelligent monitoring gives safety production "eagle eyes."

Industry Pain Points

Three Key Challenges in Visual Recognition for Traditional Manufacturing

Traditional CV lightweight models, smart cameras, and network architectures exhibit significant limitations in complex manufacturing scenarios.

Limitations of Small-Scale CV Algorithms

  • Each task requires a dedicated algorithm, leading to a proliferation of models and difficult quality control management.
  • Difficult scenario migration; requires retraining for environmental changes; weak capability in recognizing complex actions.
  • High maintenance costs for models; lack of self-learning and adaptive capabilities.

Smart Camera: Costs and Limitations

  • High unit cost and construction costs for cameras, limited edge-side computing power
  • Each camera supports a limited set of algorithms, resulting in low application flexibility.
  • Algorithm upgrades require per-site operations, leading to high maintenance costs; disconnected from the management platform with poor compatibility.

Bottlenecks in Traditional Network Architecture

  • Traditional wired networks require multiple exchanges and cabling, leading to complex installation and high maintenance costs.
  • Short transmission distance and high signal attenuation make it difficult to support HD video and AI traffic.
  • Susceptible to electromagnetic interference; high packet loss in industrial environments. Each additional monitoring point requires rewiring, resulting in poor scalability.

Chuling AI Visual Intelligence Solutions

Build a closed-loop system spanning perception, cognition, decision-making, and execution.

Data Center

Visual AI Inference System
Visual foundation models + scenario-specific visual small model matrix: deployment and iteration
Intelligent Video Management System
Video Access and Management, Stream Media Governance, Task Orchestration and Algorithm Scheduling
Data Center
Data Dashboard, SEN Network Intelligent Operations & Maintenance, and Operations & Decision-Making

Multi-Terminal Access

IP Camera
PTZ/Box Camera
Drone
Inspection Robot
Sensor
Factory Equipment

Full-Scenario Coverage

Production Workshop
Boiler Room
High-visibility vest monitoring
Hard Hat Detection
Crowd Density Detection
Hot Work Zone Detection

Large Model + Small Model Collaborative Workflow

01

Video stream ingestion

Connect multiple cameras via RTSP/ONVIF protocols and manage them centrally with a unified computing-network appliance.

02

Video Detection and Feature Extraction

Detect and identify anomalous event data, then input it into a multimodal large model for key information analysis.

03

Collaborative inference of large and small models

Large models guide semantic understanding for precise detection by small models; small models perform a second confirmation to output results.

04

Closed-loop disposal and coordination

Trigger warning lights and horns, integrate with facial recognition access control, and complete the closed-loop response.

Use Cases

AI-powered security monitoring with "sharp eyes"

Personnel Safety

  • Hard Hat / Workwear Detection
  • Region Intrusion Detection
  • Person Fall Detection
  • Automatic Crowd Gathering Alert

Production Safety

  • Fire / Smoke Detection
  • Device Leak Detection
  • Safe Monitoring of Lifting Operations
  • High-Voltage Area Protection

Code of Conduct

  • Sleeping on Duty / Unattended Post Detection
  • Call Behavior Analysis
  • Forklift Operation Safety Recognition
  • SOP Compliance Monitoring

Data Analysis

  • Event Search & Network Playback
  • Trend Analysis and Statistical Reports
  • Multi-dimensional Alert Summary
  • Predictive Analytics and Decision Support

Solution Advantages

Foundation with Large Models, Deployment with Small: The Golden Balance

Edge Deployment vs. On-Device Deployment — Fully Ahead

Comparison Criteria
On-device deployment (within camera)
Edge-side deployment (computing-network integrated appliance)
Compute Scheduling / Complex Algorithm Hosting
Limited: Only lightweight models are supported; complex tasks are restricted.
Strong: GPU/NPU supports complex models and parallel algorithms.
Deployment Cost (at a certain scale)
High: High cost per camera
Low: Compatible with various cameras, flexible scaling
Maintenance & Upgrades
Challenge: Firmware must be upgraded manually one by one.
Convenient: Unified OTA remote updates with full releases in minutes.
Scalability and Flexibility
Weak: Rigid functionality, difficult to add new algorithms
Strong: Containerized deployment with dynamic resource scheduling
Multi-device collaboration
Unable to complete
Support: Multi-camera, drone, and robot collaboration

Deep Understanding + Precise Execution

Collaborative synergy between large models for semantic understanding and small models for real-time detection creates a complete "identify issues → resolve issues" loop, surpassing simple alerts to empower decision-making.

Flexible and scalable

Tightly coupled metrics with modular plugins for smooth evolution, enabling agile cloud-edge-end collaboration to rapidly respond to diverse business needs.

Efficient, low-cost, and easy to integrate

Support for multiple camera brands, flexible edge unit expansion, TCO reduced by 50%, and resource utilization increased by 40%.

Fully independent and controllable across the board

Full-stack independent R&D, from hardware infrastructure to upper-layer application modules, fully compatible with domestic computing and Xinchuang environments.

All-optical intelligent computing networking

10G/50G slice-based backbone fiber ring network + POF+POE optical cables, featuring low latency, high bandwidth, and industrial-grade reliability

Upgrade effortlessly for the future

SEN Enterprise Network Intelligence + SD-WAN Cross-Domain Intelligent Network, continuously enabling a smooth evolution toward enterprise intelligent computing networks.

Implementation Results

Quantifiable results you can see

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Reduced accident rate

Risk prediction + real-time alerts: from reactive response to proactive defense

↓

Lower compliance costs

Automatically detect violations to reduce manual inspections and compliance review efforts.

↑

Exception Response Speed

AI-powered detection in milliseconds, alerts delivered in seconds—replacing traditional manual inspections.

↓

Reduced manual workload

AI replaces repetitive monitoring tasks, freeing up human resources to focus on value-driven decision-making.

SEN Network Intelligent Operations and Maintenance

Intranet data leakage riskReduce by 90%
Resource UtilizationBoost by 40%
Lower TCOReduce by 30%
MTTR: Incident ResolutionDown to the minute

Intelligent Supervision Across the Entire Plant

Monitoring CoverageZero blind spots across the entire facility
Recognition AccuracyDual verification by large and small models
Collaborative Disposal EfficiencyBoost by 30%+
Algorithm upgrade timeOTA full update in minutes

Case Studies

Successfully implemented

Transportation & Logistics

Deshan Freight Ship 3D Inspection

Integrate comprehensive data on vessels, crew, and enterprises to build an intelligent regulatory hub. Leverage shore-based CCTV, drones, and other smart sensing devices to capture real-time vessel movements. The built-in "Smart Violation Detection" module automatically identifies infractions such as expired certificates and understaffing.

1,000+ cases/year
Check for violations
Boost by 30%+
Collaborative disposal efficiency
Three Transformations
Manual → Intelligent | Isolated → Collaborative | Regulated → Co-governed
Energy Manufacturing

Intelligent End-to-End EHS + SOP Control for Energy Plants

As the group's first EHS intelligent pilot, this initiative integrates edge AI with lean manufacturing principles to establish a benchmark for "Smart Safety + Lean Production." It covers full-scenario applications including lifting operation safety detection, high-voltage test area protection, forklift operation safety monitoring, and open flame/smoke hazard identification.

Full-Scenario Coverage
EHS Safety + SOP Quality
Closed-loop management
Risk Identification → Process Control → Compliance Traceability
Copyable Solution
Global Expansion of the Group
Chemical Manufacturing

Shenma Group Smart Inspection Project

Achieve high-speed network coverage across all areas using an integrated computing-network appliance with full-optical networking technology. The FTTR master gateway features a built-in high-performance GPU to support advanced AI video algorithms, significantly reducing data transmission latency and enhancing video-based fire detection capabilities. Enables wide-area fire monitoring, intrusion alerts, and unmanned inspections.

Fiber-to-the-Home Networking
High-speed network coverage
GPU Edge Deployment
Edge computing deployment in production environments
Unmanned Inspection
Mobile Video Surveillance + Real-Time AI Analytics

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