Edge Computing Solutions

High-performance edge platforms supporting AI inference and real-time processing for intelligent networks.

Design Philosophy

Distributed Architecture

Distributed edge nodes process data locally to reduce network latency and bandwidth consumption.

Intelligent Processing

Integrated AI inference engines support local decision-making, reducing cloud dependency.

Cloud-Edge Collaboration

Seamless coordination between cloud and edge for local processing and cloud-based training.

Secure & Reliable

Built-in multi-layered security mechanisms and encrypted transmission ensure a safe environment.

Edge Platform Solutions

Specialized hardware for high-concurrency edge analytics and intelligent decision making.

TP-EDGE Specialized Node

Designed for heavy data throughput and complex AI model local execution, significantly reducing cloud dependency and improving system responsiveness.

High-performance AI inference modules supporting TensorFlow, PyTorch frameworks.

Integrated 5G/4G, WiFi6, and redundant Gigabit Ethernet for multi-network fusion.

Rich industrial I/O: USB 3.0, HDMI, Isolated Serial ports, and High-speed GPIO.

Supports containerized deployment (Docker/Kubernetes) for simplified management.

Wide operating temp (-40°C~+70°C) and IP65 ruggedized protection.

Edge Node Unit
Edge Optimized

Success Stories

Proven results in transforming industrial networks with intelligent edge systems.

East China · 5 Production Workshops

Smart Factory Predictive Maintenance

Challenge

High latency in centralized cloud processing prevented real-time control and accurate failure prediction.

Custom Solution

Customized industrial edge hosts with AI modules and fanless design supporting wide temp operation.

Measurable Results

Data latency reduced by 90%
Failure prediction accuracy reached 95%
Production efficiency increased by 40%
Maintenance costs reduced by 50%
Smart Factory Predictive Maintenance
South China · 2 Million Square Meters

Smart Campus Edge Computing Platform

Challenge

Bandwidth bottlenecks due to massive IoT device density and high cloud storage costs.

Custom Solution

Distributed edge nodes with 5G connectivity and multi-protocol support for various IoT sensors.

Measurable Results

Network bandwidth saved by 70%
Response time reduced to milliseconds
Operational costs reduced by 40%
Energy efficiency optimized by 30%
Smart Campus Edge Computing Platform

Core Edge Advantages

Ultra-low Latency

Millisecond response times to meet strict real-time requirements of industrial applications.

Local Processing

Proximity data handling reduces traffic and improves overall processing efficiency.

AI Acceleration

Hardware-level AI engines for local deployment and inference of deep learning models.

Expert Support

Dedicated edge computing engineering team providing full technical lifecycle support.

Technical Specifications

Designed to industry standards for high-reliability industrial deployment.

Computing Power

  • CPU: Intel Core i7/i5 or ARM Cortex-A78
  • GPU: NVIDIA RTX or Integrated AI Accel
  • Memory: 8GB-64GB Industrial DDR4
  • Storage: 256GB-2TB NVMe SSD

Connectivity

  • Ethernet: 2-8x Gigabit LAN (POE opt)
  • Wireless: 5G NR / WiFi 6 / BT 5.2
  • I/O: USB 3.2, HDMI 2.0, Isolated Serial
  • Expansion: PCIe, M.2 Expansion slots

Industrial Design

  • -40°C ~ +70°C Operating Temperature
  • IP65 Rated Protection Level
  • IEC 60068-2-6 Vibration Resistant
  • DC 12V-48V Wide Voltage Input

Ready for the Edge Revolution?

Join 500+ global enterprises optimizing their systems with our specialized edge hardware.