OpenPLC, Node-RED, BLRAT, and FUXA: A Complete Industrial Automation Workflow from Hardware Control to Visual Monitoring
The combination of OpenPLC, Node-RED, BLRAT, and FUXA enables a lightweight, open-source, end-to-end automation solution. It covers hardware control, logic orchestration, data processing, visualization, and remote maintenance—all without commercial software licensing. This makes the solution ideal for small and medium automation projects, remote operations, education, and secondary development.
Key Application Scenarios
1) EdgePLC Industrial Equipment Monitoring & Control
Goal: Real-time device monitoring, remote control, and automated alarms.
Use Cases: Conveyors, motors, temperature/humidity regulation, auxiliary machine control.
Workflow:
OpenPLC: Collects sensor data (temperature, current) and drives actuators (relays, VFDs).
Node-RED: Implements logic such as “If temperature exceeds limit → shut down device → trigger alarm.”
BLRAT: Provides secure remote access and maintenance.
FUXA: Displays real-time charts, device status, alarms, and manual control buttons.
2) ARMxy Smart Home / Laboratory Automation
Goal: Low-cost automation and environment control without commercial smart-home platforms.
Use Cases: Lighting control, HVAC, smart curtains, incubators, irrigation systems.
Workflow:
OpenPLC: Using ARMxy X23 (RS485), Y24 (relays), Y01 (DI/DO) to connect sensors and actuators.
Node-RED: Example logic: “Humidity < 40% → start humidifier” or “After 7 PM → open-door triggers auto-light.”
BLRAT: Remote device access.
FUXA: Mobile/PC interface for real-time values and manual control.
3) ARMxy Small-Scale Production Data Traceability
Goal: Capture production counts, runtime, and generate real-time and historical reports.
Use Cases: Packaging lines, small assembly machines, product counters.
Workflow:
OpenPLC: Reads count pulses and equipment runtime.
Node-RED: Stores data to MySQL/InfluxDB and calculates metrics (hourly output, failure rate).
BLRAT: Ensures remote maintenance.
FUXA: Displays daily/weekly trends and supports historical queries.
System Architecture
A standard three-layer structure ensures modularity, flexibility, and easy expansion.LayerComponentRoleProtocolsHardware ControlOpenPLCI/O control and sensor acquisitionModbus TCP, MQTTLogic LayerNode-REDAutomation logic, event handling, DB integrationMQTT, HTTP, DB connectorsVisualization LayerFUXAHMI dashboard, data display, manual control, reportingMQTT, WebSocketRemote MaintenanceBLRATSecure remote access for all modulesEncrypted tunnel
The combination of OpenPLC, Node-RED, BLRAT, and FUXA makes it ideal for small to medium-sized automation projects, remote operation, educat
How to install FUXA Web-based Visualization SCADA on ARMxy SBC BL410?
Step 1: Download Node.js 18
Visit the official Node.js website.
Click Download in the navigation bar.
In the selection box behind Get Node.js®, choose version v18.20.8 (LTS).
Select the Linux version for the binary package. Since the BL410 uses an ARM64 architecture, download the Standalone Binary (.xz) for node-v18.20.8-linux-arm64.
Step 2: Unzip and Install Node.js 18
Copy the downloaded node-v18.20.8-linux-arm64.tar.xz to the BL410 using a USB flash drive. The BL410 has a script that automatically mounts the USB drive. Use the command ls to verify the installation package is visible on the USB drive.
Create a directory named Node in the root directory: mkdir /Node.
Copy the Node.js installation package to the Node folder:cp node-v18.20.8-linux-arm64.tar.xz /Node/
Decompress the package:tar -xvJf /Node/node-v18.20.8-linux-arm64.tar.xzThis creates a folder named node-v18.20.8-linux-arm64 in the /Node directory.
Navigate to the bin folder:cd /Node/node-v18.20.8-linux-arm64/binYou should see four files: corepack, node, npm, and npx.
Create symbolic links to make Node.js and its tools accessible system-wide:ln -sf /Node/node-v18.20.8-linux-arm64/bin/node /usr/bin/ ln -sf /Node/node-v18.20.8-linux-arm64/bin/npm /usr/bin/ ln -sf /Node/node-v18.20.8-linux-arm64/bin/npx /usr/bin/
Step 3: Download the FUXA Installation Package
Visit the official FUXA website.
Click Download to navigate to the download page and locate the Star FUXA repo button, which redirects to the FUXA GitHub repository.
On the GitHub page, scroll to the Install from source section.
Click Download the latest release and select the latest FUXA version (e.g., FUXA-1.2.5.tar.gz).
Copy the downloaded FUXA-1.2.5.tar.gz to the BL410 using a USB drive:cp FUXA-1.2.5.tar.gz /FUXA/
Step 4: Unzip the FUXA Installation Package
Decompress the FUXA package:tar -zxvf /FUXA/FUXA-1.2.5.tar.gz
Verify the decompressed files:ls
Step 5: Modify the Configuration File
Navigate to the server folder:cd server
Open the package.json file using the vi editor:vi package.json
Locate and delete the line referencing odbc.
Save and exit the file::wq!
Install the dependencies, which may take some time:npm install
Step 6: Start FUXA
Start the FUXA application:npm start
Step 7: Access FUXA
Open a web browser on a device connected to the same network as the BL410.
Enter the BL410’s IP address followed by port Device IP+1881
Press Enter to access the FUXA Web SCADA interface.
Notes
Ensure the BL410 is connected to a network and has a valid IP address before attempting to access FUXA.
The npm install step may take a while depending on the device’s performance and network conditions.
If you encounter issues, verify that all symbolic links for Node.js are correctly set and that the FUXA package is properly decompressed.
Building Cost-Effective Industrial Automation with Open Source SCADA Solutions
Introduction
Supervisory Control and Data Acquisition (SCADA) systems are the backbone of modern industrial automation, enabling real-time monitoring and control of complex processes in industries like manufacturing, energy, and water management. Traditionally, proprietary SCADA systems have dominated the market, but their high costs and vendor lock-in have driven industries to explore open source alternatives. Open source SCADA solutions offer a cost-effective, flexible, and customizable approach to industrial automation, making them an attractive choice for businesses of all sizes. This article explores how open source SCADA systems can reduce costs, enhance scalability, and empower industries to build robust automation solutions.
Why Choose Open Source SCADA?
Cost Efficiency
Proprietary SCADA systems often come with hefty licensing fees, maintenance costs, and expensive hardware requirements. Open source SCADA solutions, such as Scada-LTS, Rapid SCADA, and OpenSCADA, eliminate licensing costs, allowing businesses to allocate budgets to hardware, integration, or customization. For small and medium-sized enterprises (SMEs), this cost reduction can be a game-changer, enabling them to adopt advanced automation without breaking the bank.
Flexibility and Customization
Unlike proprietary systems, open source SCADA platforms provide access to their source code, allowing developers to tailor the system to specific industrial needs. Whether it’s integrating with existing IoT devices, customizing dashboards, or adding new protocols, open source solutions offer unparalleled flexibility. For example, PyScada, built on Django, allows developers to create web-based interfaces with minimal coding, adapting to unique workflows.
Community Support and Innovation
Open source SCADA systems benefit from vibrant communities of developers who contribute to continuous improvement, bug fixes, and security updates. Platforms like Scada-LTS and Rapid SCADA have active forums and documentation, ensuring users have access to resources and support. This collaborative environment fosters innovation, with new features and integrations often available faster than in proprietary systems.
Key Open Source SCADA Solutions
Scada-LTS
Scada-LTS is a web-based, open source SCADA platform designed for scalability and cross-platform compatibility. It supports a wide range of protocols, including Modbus and OPC UA, making it suitable for diverse industrial applications. Its modular architecture allows users to build custom dashboards and integrate with databases like MySQL or PostgreSQL, reducing deployment costs.
Rapid SCADA
Rapid SCADA is a lightweight, open source solution ideal for small to medium-scale automation projects. It offers real-time data visualization, alarm management, and reporting features. Its low hardware requirements make it a cost-effective choice for industries like water treatment or renewable energy, where budget constraints are common.
PyScada
PyScada leverages Python and Django to provide a flexible, web-based SCADA framework. It’s particularly suited for industries requiring custom data processing or integration with IoT devices. Its open source nature allows developers to extend functionality, such as adding support for new sensors or creating tailored analytics.
Emoncms
Emoncms is an open source SCADA platform focused on energy monitoring, particularly for solar and renewable energy systems. Its low-cost deployment and integration with low-power hardware like Raspberry Pi make it an excellent choice for cost-conscious projects. Emoncms also supports data logging and visualization, enabling real-time insights into energy consumption.
Implementing Open Source SCADA: A Step-by-Step Guide
1. Define Requirements
Start by identifying the specific needs of your industrial process. Consider factors like the number of data points, required protocols (e.g., Modbus, MQTT), and visualization needs. For example, a manufacturing plant may need real-time machine status updates, while a water treatment facility may prioritize historical data logging.
2. Select the Right Platform
Choose an open source SCADA system that aligns with your requirements. For instance, Scada-LTS is ideal for large-scale, multi-protocol systems, while Rapid SCADA suits smaller projects with simpler needs. Evaluate hardware compatibility, as many open source solutions run on low-cost devices like Raspberry Pi or Linux servers.
3. Install and Configure
Most open source SCADA systems provide detailed installation guides. For example, Rapid SCADA can be set up on a Windows or Linux server in under an hour. Configure communication protocols to connect with your PLCs, sensors, or IoT devices. Ensure network security by implementing firewalls and secure protocols like HTTPS.
4. Customize and Integrate
Leverage the open source nature of the platform to customize dashboards, alarms, or data processing logic. For instance, PyScada’s Python-based framework allows developers to add custom scripts for advanced analytics. Integrate with existing systems, such as ERP or MES, to streamline operations.
5. Test and Deploy
Conduct thorough testing to ensure data accuracy, system reliability, and responsiveness. Simulate real-world scenarios, such as sensor failures or network interruptions, to validate system performance. Once tested, deploy the system and monitor its performance using built-in diagnostic tools.
Case Study: Solar Plant Monitoring with Emoncms
A small solar energy company needed a cost-effective SCADA system to monitor its photovoltaic (PV) plant. Proprietary solutions were too expensive, so they turned to Emoncms. Using a ARMxy SBC BL410 series as the server, they integrated Emoncms with their PV inverters via Modbus. The system provided real-time power output data, historical trends, and alerts for underperforming panels. Total implementation costs were under $500, compared to $10,000 for a proprietary system, demonstrating the cost-effectiveness of open source SCADA.
Challenges and Considerations
While open source SCADA systems offer significant benefits, they come with challenges. Lack of formal vendor support may require in-house expertise or reliance on community forums. Security is another concern; since the source code is public, regular updates and robust cybersecurity practices are essential. Additionally, integrating open source SCADA with legacy systems may require custom development, which could increase initial setup time.
Conclusion
Open source SCADA solutions like Scada-LTS, Rapid SCADA, PyScada, and Emoncms provide a cost-effective alternative to proprietary systems, enabling businesses to achieve industrial automation without prohibitive costs. Their flexibility, community support, and compatibility with modern technologies make them ideal for a wide range of applications, from energy monitoring to manufacturing. By carefully selecting and implementing an open source SCADA platform, industries can build scalable, efficient, and budget-friendly automation systems that meet their unique needs.
References
Scada-LTS Official Documentation: https://scada-lts.org/
How to install N3uron Visualization Software Platform on ARM Edge Gateway?
Step 1: Download the N3uron Installation Package
Visit the official N3uron website.
Locate and click Download N3uron in the upper right corner to access the download page.
Select the Linux ARM32 version (or ARM64 if applicable).
Click DOWNLOAD SOFTWARE to download the installation package.
Step 2: Unzip and Install N3uron
Once the package is downloaded, transfer it to your BL330 device and follow these steps to install N3uron:
Copy the downloaded installation package to the BL330 device.
Open a terminal and decompress the package by entering:tar -zxvf n3uron-setup-linux-arm32-1.21.12-250219.1123.tar.gzThis extracts the files into the system.
Navigate to the extracted folder by entering:cd /n3uron/bin
Run the installation command:./n3uron install
Start the N3uron service with:systemctl start n3uron
Step 3: Run N3uron
After installation, access the N3uron interface through a web browser:
Open a browser and enter the device’s IP address followed by the appropriate port:
For HTTP, use port 8003 (e.g., http://:8003).
For HTTPS, use port 8443 (e.g., https://:8443).
Log in using the default credentials:
Username: admin
Password: n3uron
Once logged in, the installation is complete, and you can begin using N3uron.
Conclusion
By following these steps, you should have N3uron installed and running on your BL330 device. Ensure you use the correct version (ARM32 or ARM64) for your system and verify the IP address and port when accessing the platform. For further configuration or troubleshooting, refer to N3uron’s official documentation.
N3uron is an Industrial IoT and visualization software platform. It is a modular platform designed for industrial applications, focusing on
Core Principles and Architecture of Soft Programmable Logic Controller
Introduction
A Soft PLC (Programmable Logic Controller) emulates the functionality of traditional hardware PLCs through software, enabling industrial automation control on general-purpose computers or embedded devices. By leveraging universal hardware and flexible software architectures, Soft PLCs reduce costs and enhance scalability, making them widely adopted in modern industrial applications. This article elaborates on the core principles, common software, system architecture, workflow, advantages, and challenges of Soft PLCs.
Core Principles
Soft PLCs achieve industrial control through the following key components:
1. Virtualized Control Logic
Soft PLCs simulate the control logic of hardware PLCs via software, adhering to the IEC 61131-3 standard and supporting multiple programming languages such as Ladder Diagram (LD), Function Block Diagram (FBD), and Structured Text (ST). User-written control programs are compiled into executable code, running in a logic execution engine to process input signals, perform logical operations, and control outputs.
2. Real-Time Task Scheduling
Real-time performance is critical for Soft PLCs. They rely on Real-Time Operating Systems (RTOS) or real-time extensions (e.g., RTX for Windows, PREEMPT_RT for Linux) to ensure deterministic task execution. A real-time scheduler manages periodic scanning of inputs, execution of control logic, and updating of outputs, meeting the stringent timing requirements of industrial control.
3. Input/Output (I/O) Processing
Soft PLCs interface with external devices through hardware interfaces (e.g., industrial I/O modules, communication buses, or standard PC interfaces) to collect sensor signals and drive actuators. I/O data is mapped to the Soft PLC’s memory via drivers or communication protocols (e.g., Modbus, OPC UA, EtherCAT) for processing by the control logic.
4. Runtime Engine
The runtime engine is the core component of a Soft PLC, responsible for parsing and executing user programs, managing I/O data, handling communications, and performing diagnostics. It includes a task manager, data storage area (for variables and states), and error-handling mechanisms to ensure stable operation.
5. Communication and Integration
Soft PLCs support various industrial communication protocols (e.g., Modbus TCP, PROFINET, Ethernet/IP), facilitating integration with HMIs, SCADA systems, or other control systems. Their open software architecture enables interaction with enterprise-level systems (e.g., MES, ERP) for data collection and remote monitoring.
Common Soft PLC Software
Soft PLCs rely on specialized software platforms. Below are several mainstream Soft PLC software solutions and their features:
CODESYS: A powerful Soft PLC development platform supporting the full range of IEC 61131-3 programming languages, offering extensive industrial protocol support and visualization tools, widely used in industrial automation projects.
OpenPLC: An open-source Soft PLC solution compatible with various hardware platforms (e.g., Raspberry Pi, Arduino), ideal for education, research, and small-scale industrial applications.
PLCnext: Developed by Phoenix Contact, it combines Soft PLC functionality with an open Linux platform, supporting hybrid development with high-level languages (e.g., C++, Python) and traditional PLC programming, suitable for complex applications. These software platforms provide development environments and runtime engines, enabling users to efficiently build and deploy control logic for diverse industrial needs.
System Architecture
The system architecture of a Soft PLC consists of three main components:
Development Environment: Provides programming and debugging tools, allowing users to design control logic and simulate operations.
Runtime Environment: The runtime software is deployed on target hardware, integrating with the operating system and I/O interfaces to execute real-time control tasks.
Hardware Platform: Typically an industrial PC, embedded device, or server, which must meet performance and environmental adaptability requirements.
Workflow
The operation of a Soft PLC follows these steps:
Initialization: Upon startup, the Soft PLC loads the user program and initializes I/O interfaces and communication modules.
Cyclic Scanning: At preset intervals (scan cycles), the Soft PLC reads input data, executes control logic, and updates output data.
Communication Processing: Handles communication requests from external devices, uploading status data or receiving control commands.
Exception Management: Monitors system status and manages errors or faults (e.g., I/O disconnections, program anomalies).
Flexibility: Supports integration of complex algorithms (e.g., AI, data analytics) and easy scalability.
Rapid Iteration: Software-based architecture facilitates development and upgrades, adapting to modern industrial demands.
Benefits of Running Soft PLC on ARM-Based Industrial PCs ARMxy series
Deploying Soft PLCs on ARM-based industrial PCs ARMxy series offers the following advantages:
Low Power Consumption: ARM processors are known for high energy efficiency, ideal for long-term operation in industrial settings, reducing energy costs.
High Integration: ARM industrial PCs ARMxy series typically feature rich peripheral interfaces (e.g., GPIO, CAN, Ethernet, RS485/RS232), simplifying connections with industrial devices.
Cost Efficiency: ARM hardware is cost-competitive, and when paired with Soft PLC software, it significantly lowers overall system costs.
Compact Design: The small form factor of ARM industrial PCs ARMxy series suits space-constrained industrial environments.
Open-Source Ecosystem: ARM platforms are compatible with various open-source Soft PLC software (e.g., OpenPLC), facilitating customization and development. These characteristics make ARM-based industrial PCs ARMxy series an excellent choice for small to medium-scale industrial automation projects.
Recommended Models：ARMxy Series RS3568J 4*A55 Architecture BL410 series, RK3576 4*A72 Architecture BL440 series and RK3588 4*A76 Architecture BL450 series
Challenges
Real-Time Performance: General-purpose hardware and operating systems require optimization to meet industrial control’s deterministic requirements.
Reliability: General-purpose hardware may lack the robustness of dedicated PLCs, necessitating redundancy or protective measures.
Security: Soft PLCs operating in networked environments must defend against cyberattacks and data breaches.
Conclusion
Soft PLCs replicate the functionality of traditional PLCs through software, leveraging general-purpose wortware and flexible architectures to provide cost-effective, scalable solutions for industrial automation. Mainstream Soft PLC software, such as CODESYS and OpenPLC, simplifies development and deployment. Running Soft PLCs on ARM-based industrial PCs capitalizes on low power consumption, high integration, and cost efficiency, making them ideal for modern industrial applications. However, challenges in real-time performance, reliability, and security require ongoing optimization. As Industry 4.0 advances, Soft PLCs will play an increasingly vital role in smart manufacturing.
ARMxy SBC is a series ARM Based SBC, ARM Embedded Industrial Computers and providing ARM Based Solutions , with flexible SoM and I/O, it is
How to install Node-Red on Linux ARM based SBC ARMxy？
Download the environment from Node.js
Enter the node.js official website
Click Download in the navigation bar to download the node.js version we need.
Click the selection box behind Get Node.js® and select the version we need to download. Here we choose v20.19.1 (LTS)
We install it through the binary package. We select the Linux version below the instruction installation box. Because BL410 is the ARM64 version, we select the corresponding version and click Standalone Binary (.xz) to download the binary package.
Unzip the environment package
Use a USB flash drive to copy the installation package to the device. There is a script in BL410 that automatically mounts the USB flash drive. We use ls to view the installation package in the USB flash drive.
create a Node folder in the root directory in advance, and use cp node-v20.19.1-linux-arm64.tar.xz /Node/ to copy the node.js installation package to the Node folder
Enter tar -xvJf node-v20.19.1-linux-arm64.tar.xz to decompress the installation package.
Link operating environment
The unzipped installation package will generate a node-v20.19.1-linux-arm64 folder in the /Node folder
Enter cd node-v20.19.1-linux-arm64/bin to enter the bin folder. At this time, we can see four files, namely corepack node npm npx
Use ln -sf to create link files ln -sf /Node/node-v20.19.1-linux-arm64/bin/node /usr/bin/ and ln -sf /Node/node-v20.19.1-linux-arm64/bin/npx /usr/bin/ and ln -sf /Node/node-v20.19.1-linux-arm64/bin/npx /usr/bin/
Enter node -v and npm -v to verify whether the node.js and npm package management tools are installed successfully. The version number indicates that the installation is complete.
Install Node-Red
Use the command npm install -g --unsafe-perm node-red to install node-red.
Run Node-Red
After node-red is installed, enter ls and we can view the node-red file
Use ln -sf /Node/node-v20.19.1-linux-arm64/bin/node-red /usr/bin/ to create a link
Enter node-red to verify the software installation environment.
Using node-red
Open the browser and enter the device IP + 1880 in the browser address bar to access
When the browser now opens Node-red, the installation is complete.
Node-RED used for the development of IoT and event-driven applications. It allows users to create automated processes by dragging and droppi
Six Technology Trends Shaping Industrial Automation
Industrial automation is entering its most transformative phase since the introduction of PLCs and SCADA in the 1970s. Driven by advancements in connectivity, artificial intelligence, and digital engineering, automation is evolving from programmed control to predictive, adaptive, and autonomous systems. Over the next five years (2025–2030), six core technology trends will reshape the operations, scale, and adaptability of factories, warehouses, utilities, and processing plants. This article explores these trends and their implications for OEMs, system integrators, and industrial product developers, with a focus on the role of ARM-based industrial PCs in enabling these advancements.
Edge AI and Machine Learning for Predictive Control
What’s Happening: Artificial Intelligence (AI) has shifted from cloud-based systems to edge devices, enabling real-time processing of sensor data on embedded platforms like ARM-based industrial PCs.
Key Benefits:
Reduced latency for time-critical decisions.
Predictive maintenance using behavioral models.
Enhanced resilience by minimizing reliance on cloud infrastructure.
Real-World Applications:
Anomaly detection in rotating equipment using vibration sensors and machine learning (ML) models.
Predictive quality control on production lines with computer vision.
Adaptive process optimization in chemical and food manufacturing.
Technology Enablers:
ARM-based industrial PCs (e.g., those powered by NXP i.MX 9, Rockchip RK3588J, or NVIDIA Jetson) provide energy-efficient, high-performance platforms for edge AI.
Frameworks like Edge Impulse and TensorFlow Lite for microcontrollers.
Integration of Real-Time Operating Systems (RTOS) with model inference pipelines.
Outlook (2025–2030): Factory equipment will increasingly become AI-native, leveraging ARM industrial PCs for on-device model retr --
ARMxy BL450 series Rockchip RK3588J supports 6Tops NPU to promote the development of Edge AI
System: aining via federated learning or MLOps practices, enabling continuous improvement and adaptation at the edge.
Interoperability Through Unified Industrial Protocols
The Challenge: Traditional systems rely on proprietary fieldbuses, vendor-specific integrations, and siloed architectures, limiting scalability.
Trend: Open, vendor-neutral communication protocols are gaining traction:
OPC UA over TSN for deterministic communication.
MQTT + Sparkplug B for lightweight messaging.
EtherCAT + Ethernet-APL for real-time, deterministic Ethernet.
Benefits:
Plug-and-play device integration.
Cross-vendor communication in brownfield and greenfield environments.
Simplified migration to Industry 4.0 and digital twin ecosystems.
Key Development: Adoption of IEC 61499 for event-driven automation logic, interoperating with cloud APIs for remote control and monitoring.
Role of ARM Industrial PCs: ARM-based industrial PCs, with their support for modern networking stacks and low-power, high-throughput processing, serve as gateways or controllers to bridge legacy and modern protocols, enabling seamless interoperability.
BLIoTLink supports multiple industrial protocols, such as Modbus, MQTT, OPC UA, etc., and can be adapted to ARMxy series industrial computers and other ARM architecture hardware devices for data acquisition and protocol conversion.
Digital Twins and Model-Based Engineering
Concept: Digital twins are real-time virtual representations of physical systems, used for simulation, monitoring, and optimization.
Why It’s Growing:
Enables remote debugging and system tuning.
Supports predictive diagnostics and process optimization.
Simplifies training, testing, and certification.
Enabling Technologies:
3D CAD and simulation tools (e.g., ANSYS Twin Builder, Siemens NX).
IoT platforms for real-time data synchronization.
Open standards like Functional Mock-up Interface (FMI).
Trends to Watch:
Integration of PLC code and physics-based models in unified runtimes.
Digital twin ecosystems across OEMs, integrators, and end-users.
Coupling digital twins with AI models for next-generation control systems.
Role of ARM Industrial PCs: ARM-based industrial PCs provide the computational power and connectivity needed to host digital twin runtimes locally, ensuring low-latency synchronization with physical systems.
Challenges: Ensuring data quality, sensor integration, real-time synchronization, and model maintenance as systems evolve.
Collaborative Robots (Cobots) and Autonomous Systems
Shift: Unlike traditional caged industrial robots, collaborative robots (cobots) and Autonomous Mobile Robots (AMRs) operate in shared spaces with human workers.
Key Advancements:
Safety path planning using 3D sensors and AI.
Flexible reprogramming for dynamic tasks.
Real-time integration with Manufacturing Execution Systems (MES) and Warehouse Management Systems (WMS).
Applications:
Bin picking and assembly on hybrid production lines.
Autonomous material transport in smart warehouses.
Inspection and maintenance in hazardous areas.
Technology Drivers:
ROS 2 and MoveIt for motion planning and control.
EtherCAT-based motion control systems.
AI-enhanced vision and grasping libraries.
Role of ARMxy Industrial PCs: ARM-based industrial PCs power the control and AI processing for cobots and AMRs, offering compact, energy-efficient platforms for real-time decision-making and sensor integration.
Outlook: Cobots will evolve to learn and adapt through reinforcement learning and shared datasets, with ARM industrial PCs enabling scalable, on-device intelligence.
Cybersecurity and Regulatory Compliance in Industrial Environments
Why It Matters: The growing connectivity of industrial systems increases vulnerability to cyberattacks, as seen in incidents targeting water utilities, pipelines, and factories.
Key Regulatory Frameworks:
IEC 62443 (Industrial Cybersecurity).
NIST 800-82.
ISO/SAE 21434 (for automotive applications).
EU Cyber Resilience Act (effective 2025+).
Emerging Strategies:
Security-by-design at the chip and firmware levels.
Zero-trust architectures with identity-based access.
Secure boot, over-the-air (OTA) updates, and encrypted logging.
Role of ARM Industrial PCs: ARM-based industrial PCs, with built-in security features like TrustZone and secure boot, provide robust platforms for implementing cybersecurity measures at the edge, ensuring compliance and protection.
Outlook: Cybersecurity will become an embedded product feature, integrated into PLCs, drives, HMIs, and sensor nodes, with ARM industrial PCs serving as secure hubs.
Edge-to-Cloud Integration for Closed-Loop Industrial Intelligence
Trend: As edge devices like ARM-based industrial PCs become smarter, seamless, secure, and real-time data flow between edge and cloud is critical, representing the convergence of Operational Technology (OT) and Information Technology (IT).
Key Developments:
Data preprocessing at the edge to reduce cloud payloads and costs.
Cloud-native microservices for SCADA/PLC integration.
Real-time feedback loops between factory sensors and cloud-based AI engines.
Use Cases:
Cloud-to-edge synchronization for production planning and quality control.
Dynamic model deployment from cloud AI platforms to edge accelerators.
Visualization dashboards powered by Azure IoT, AWS Greengrass, or private Kubernetes clusters.
Benefits:
Agile production systems.
Unified data lakes for analytics.
Reduced latency for mission-critical control.
Role of ARM Industrial PCs: ARM-based industrial PCs act as edge gateways, performing preprocessing, local analytics, and secure communication with cloud platforms, enabling efficient closed-loop systems.
Adoption Challenges: Managing latency, ensuring cybersecurity, and addressing data model fragmentation.
Final Thoughts: From Automation to Autonomy
The next five years will redefine industrial automation by integrating real-time control with AI, connectivity with cybersecurity, and physical systems with digital twins. ARM-based industrial PCs will play a pivotal role as versatile, power-efficient platforms that enable edge computing, interoperability, and secure, scalable automation.
OEMs, system designers, and technology providers that embrace these trends early will build more adaptive, scalable, and future-ready platforms. Let’s shape the future of automation together.
ARM-based industrial PCs will play a pivotal role as versatile, power-efficient platforms that enable edge computing, interoperability, and
From Traditional PLC to ARM Industrial PC: An Intelligent Leap in Industrial Control Systems
The transition from traditional PLCs (Programmable Logic Controllers) to ARM-based industrial PCs represents an intelligent leap in industrial control systems, reflecting the evolution of industrial automation from specialized hardware to universal, flexible, and high-performance computing platforms. Below is a concise analysis of this transformation, covering its background, characteristics, advantages, and challenges:
Background: The Evolving Needs of Industrial Control Systems
Limitations of Traditional PLCs: PLCs have long dominated industrial control due to their high reliability, real-time performance, and specialization. However, their complex programming, limited scalability, and inability to handle complex algorithms or big data make them less suited for the flexibility and intelligence demands of Industry 4.0 and smart manufacturing.
Rise of ARM Industrial PCs: The ARM architecture, known for low power consumption, high performance, versatility, and a rich ecosystem, is increasingly penetrating the industrial control sector. ARM industrial PCs, combining embedded systems with industrial-grade design, offer higher computing power, more flexible software ecosystems, and lower costs.
Core Characteristics of ARM Industrial PC vs. PLC
FeatureTraditional PLCARM Industrial PCHardware ArchitectureSpecialized hardware, fixed-function modulesUniversal ARM architecture, highly customizableComputing PowerSuitable for simple logic control, limited for complex algorithmsSupports complex algorithms, AI, and data processingProgrammingLadder logic, structured text, etc.Supports general-purpose languages like C/C++, PythonScalabilityModular expansion, high costRich interfaces (USB, Ethernet, GPIO, etc.)Real-Time PerformanceHard real-time, high determinismSoft/hard real-time, requires optimized RTOSCostHigh, due to specialized hardware and software licensesLower, with general-purpose hardware and open-source softwareNetworkingLimited, requires gateways for IoTNative support for IoT and edge computing
Core Advantages of the Intelligent Leap
High Performance and Intelligence: ARM industrial PCs support AI algorithms (e.g., machine vision, predictive maintenance), enabling edge computing, reducing cloud dependency, and enhancing real-time decision-making.
Flexibility and Openness: They support Linux, RTOS, and other operating systems, allowing developers to leverage rich open-source tools and frameworks for rapid, customized application development.
Low Power and Compact Design: ARM’s low-power architecture is ideal for long-term operation and compact industrial settings, reducing energy and space costs.
IoT and Interconnectivity: ARM industrial PCs are naturally suited for Industrial IoT (IIoT), supporting protocols like MQTT and OPC UA, and easily integrating with cloud platforms and other devices.
Cost Efficiency: Compared to PLCs, ARM industrial PCs have lower hardware costs, and software development benefits from open-source ecosystems, reducing licensing fees.
Challenges and Solutions
Real-Time Performance and Reliability: PLCs excel in hard real-time and industrial-grade reliability. ARM industrial PCs need real-time operating systems (RTOS, e.g., FreeRTOS, Zephyr) and redundant designs to bridge this gap.
Development Complexity: The versatility of ARM industrial PCs increases development freedom but also programming and debugging complexity, requiring more skilled development teams.
Industrial Environment Adaptability: Harsh industrial environments (e.g., high temperatures, vibrations) demand ruggedized hardware designs and certifications (e.g., IP65, EMC) for ARM industrial PCs.
Ecosystem Compatibility: PLCs benefit from mature industrial standards and vendor ecosystems. ARM industrial PCs need to enhance compatibility with traditional industrial protocols and devices.
Applications and Future Trends
Typical Applications:
Smart Manufacturing: Data acquisition, analysis, and optimization on production lines.
Edge Computing: Running AI models at the device level to reduce latency.
Robot Control: Supporting complex motion control and sensor fusion.
Energy Management: Real-time monitoring and optimization of energy consumption.
Future Trends:
AIoT Integration: ARM industrial PCs will deeply integrate AI and IoT, promoting “device-edge-cloud” collaboration.
Modularity and Standardization: They will adopt PLC-like modular designs, offering more standardized industrial solutions.
Enhanced Security: As connectivity grows, ARM industrial PCs will need stronger cybersecurity and data protection (e.g., hardware encryption, OTA updates).
RISC-V Competition: The open-source RISC-V architecture may challenge ARM’s dominance in the industrial sector.
ARMxy industrial PC is an ARM-based SBC with flexible ARM SoM and I/O ports. It has more than 1,000 application options, supports Python and C language programming, can install soft PLC software for programming, and supports the installation of protocol conversion software and edge computing functions. It is very suitable for industrial automation and other application solutions.
Conclusion
The transition from PLC to ARM industrial PC is not only a change in hardware architecture, but also a step for industrial control systems to move towards higher intelligence, openness and flexibility. With high performance, low cost and an open ecosystem, ARM industrial PC is reshaping industrial automation. However, to fully replace PLCs, they must continue to improve real-time performance, reliability, and compatibility with industrial standards. Looking ahead, as Industry 4.0 and AIoT advance, ARM industrial PCs are poised to become the core platform for intelligent industrial control.
ARMxy SBC is a series ARM-Based Solutions with flexible SoM and I/O Ports, ideal choice for Industrial IoT, Edge Computing, Industrial Visua
