RK3576 AI Substation Inspection Device ODM Case Study

Project Overview

As power infrastructure becomes increasingly digitalized, substations require more intelligent and automated inspection solutions. Traditional manual inspection can be time-consuming and may not provide continuous monitoring of critical equipment.

KICKPI developed a custom RK3576-based AI substation inspection terminal designed for intelligent visual inspection in power substations.

The system integrates multi-camera image acquisition, infrared imaging, edge AI inference, PTZ control, temperature monitoring, meter recognition, local storage, and 4G/5G/Ethernet communication into a compact industrial platform.

The solution is designed for demanding environments where continuous operation, real-time AI processing, and reliable communication are essential.

Customer Requirements

The customer required an embedded AI platform capable of supporting multiple inspection functions:

• Visible-light camera
• Infrared camera
• Wide-angle camera
• PTZ control
• AI-based object and equipment recognition
• Meter and pointer recognition
• Temperature monitoring
• Abnormal condition detection
• Local video storage
• 4G/5G and Gigabit Ethernet communication
• Long-term stable operation

The main challenge was not simply deploying an RK3576 processor, but creating a complete platform that could reliably combine camera processing, AI inference, thermal imaging, communication, storage, and industrial thermal management.

RK3576 Multi-Camera AI Architecture

The inspection terminal uses the Rockchip RK3576 as the core computing platform.

Multiple image sources are connected to the system, including visible-light, infrared, and wide-angle cameras.

The general processing pipeline is:

Camera → ISP → Image Preprocessing → RK3576 NPU → AI Model → Result Analysis → Alarm

The system needs to handle multiple camera interfaces, image formats, ISP processing, video encoding, camera switching, and AI inference.

This architecture allows AI analysis to be performed directly on the inspection terminal instead of continuously transmitting raw video to the cloud.

As a result, the system can reduce network bandwidth requirements while providing faster local responses to detected events.

Edge AI for Substation Inspection

One of the key functions of the system is local AI inference.

The RK3576 NPU can be used to accelerate AI models for applications such as:

• Equipment status recognition
• Personnel detection
• Smoke and fire detection
• Meter recognition
• Pointer recognition
• Abnormal equipment detection
• Visual inspection analysis

By processing inspection data locally, the device can identify potential abnormalities and generate alerts without depending entirely on cloud processing.

This is particularly useful for substations where network conditions, response time, and data transmission costs need to be considered.

Infrared & Day/Night Vision

Substation inspection requires reliable image acquisition under different lighting conditions.

To support both daytime and nighttime operation, the system integrates:

• Visible-light camera
• Infrared camera
• IR-CUT
• IR illumination
• Automatic day/night switching
• ISP exposure control
• White balance optimization
• Low-light image enhancement

The image-processing pipeline combines camera input with ISP processing and AI inference to maintain stable image quality across changing environmental conditions.

For applications involving thermal monitoring or infrared inspection, the infrared imaging system can also provide additional information that may not be visible through conventional cameras.

Thermal Design for 24/7 AI Operation

Continuous AI inspection places significant computational load on the embedded platform.

During operation, CPU, GPU, NPU, and ISP may work simultaneously, generating substantial heat.

Therefore, thermal design was treated as an important part of the ODM development process.

The platform incorporates:

• Customized heatsink design
• Thermal pads
• Active or passive cooling options
• System temperature monitoring
• CPU DVFS
• NPU thermal protection
• Long-duration stress testing

The system was tested under sustained workloads to verify stable operation during extended AI inference and video processing.

Communication & Local Storage

For remote monitoring and data transmission, the platform supports multiple communication options, including:

4G / 5G / Ethernet

The system also supports local storage for inspection images and video.

Communication reliability and automatic reconnection were considered during system development to ensure that temporary network interruptions would not easily affect long-term operation.

Testing & Validation

For industrial power applications, hardware performance is only one part of the evaluation.

The inspection platform was tested across multiple dimensions:

These tests helped verify the platform’s stability for continuous AI inspection applications.

Project Results

The project resulted in an integrated RK3576 AI inspection platform combining:

Multi-Camera + Edge AI + Infrared Vision + PTZ Control + Local Storage + Remote Communication

The key ODM value was not simply bringing up the RK3576 processor.

Instead, the project required integrated engineering across:

Camera → ISP → NPU → AI Algorithm → Thermal Design → Communication → Storage → Industrial Reliability

This makes the platform suitable as a hardware foundation for AI substation inspection, power equipment monitoring, industrial vision, and other edge AI applications.

Looking for a Custom RK3576 AI Platform?

KICKPI provides custom embedded board and ODM development services based on Rockchip platforms, including hardware design, peripheral integration, camera interfaces, AI acceleration, thermal optimization, Linux/Android adaptation, and production support.

If you are developing an AI inspection terminal, industrial vision device, smart power equipment, or other RK3576-based product, contact KICKPI to discuss your hardware requirements and ODM project.