Node Red

Node‑RED is a low‑code, flow‑based visual programming tool (built on Node.js) that lets you wire together hardware, APIs, databases and services to build event‑driven integrations and dashboards easily. It serves as a powerful tool for building Industrial Internet of Things (IIoT) applications, enabling easy integration of hardware, APIs, and cloud services. Node-Red supports key industrial protocols like MQTT, Modbus, and OPC UA for easy data exchange with PLCs, sensors, and machine control systems.

Node‑RED is open‑source under the Apache 2.0 licence and free to use even commercially. The Apache License 2.0 is a permissive open‑source software licence that lets you freely use, modify, distribute the code (even commercially) while requiring attribution, license text inclusion, and granting patent rights

Hands-on Industrial Automation & Control Engineering with Node-RED

A complete guide from simulation to SCADA dashboard

🎯 Target Audience

Engineering students, technicians, process engineers, and IT/OT professionals seeking practical skills in modern industrial automation using open-source tools.

✅ What You’ll Build

By the end of this tutorial, you’ll have:

  1. A simulated PLC controlling a temperature system
  2. Node-RED reading/writing via Modbus TCP
  3. An industrial dashboard with gauges, charts, and alarms
  4. MQTT integration for IIoT data flow
  5. A complete monitoring and control system

📋 Prerequisites

  • Basic understanding of automation concepts
  • Windows/macOS/Linux computer
  • Internet connection for downloads

🛠️ Part 1: Environment Setup

1.1 Install Node.js

  1. Download Node.js LTS from nodejs.org
  2. Verify installation:

bash

node -v  # Should show v18.x or higher
npm -v   # Should show 9.x or higher

1.2 Install Node-RED

bash

npm install -g --unsafe-perm node-red

Note: On Linux/macOS, you might need sudo

1.3 Start Node-RED

bash

node-red

Access the editor at: http://localhost:1880

🔧 Part 2: Your First Automation Flow

Simulating a Digital Sensor → Actuator Control

2.1 Build the Flow

  1. In Node-RED editor, drag these nodes from the palette:
    • Inject node (timestamp)
    • Function node (logic)
    • Debug node (output)
  2. Connect them: Inject → Function → Debug
  3. Double-click the Function node and paste:

javascript

// Simulate random sensor value (0 or 1)
let sensorValue = Math.random() > 0.5 ? 1 : 0;

// Control logic: If sensor detects something, turn actuator ON
let actuatorState = sensorValue === 1 ? "ACTUATOR ON" : "ACTUATOR OFF";

// Add timestamp
msg.payload = {
    timestamp: new Date().toISOString(),
    sensor: sensorValue,
    actuator: actuatorState
};

return msg;
  1. Click Deploy (top right)
  2. Click the inject node’s button – see output in Debug panel

This mimics basic PLC ladder logic!

🏭 Part 3: Industrial Protocols – Modbus TCP

3.1 Install Modbus Nodes

  1. In Node-RED: Menu → Manage Palette
  2. Go to Install tab, search for: node-red-contrib-modbus
  3. Click Install

3.2 Simulate a PLC with OpenPLC

  1. Install OpenPLC Editor from openplcproject.com
  2. Create simple ladder logic:
    • Input: %IX0.0 (simulated temperature high)
    • Output: %QX0.0 (cooling fan)
  3. Run in simulation mode

3.3 Node-RED Modbus Configuration

text

[Flow Configuration]
1. Modbus Read node → Read Holding Registers
2. Server: localhost:502 (OpenPLC default)
3. Address: 40001 (temperature register)
4. Interval: 2000ms

3.4 Test Modbus Connection

javascript

// Add function node after Modbus Read
msg.payload = {
    temperature: msg.payload[0],
    unit: "°C",
    timestamp: new Date()
};
return msg;

📊 Part 4: Build an Industrial Dashboard

4.1 Install Dashboard

bash

npm install node-red-dashboard

Restart Node-RED

4.2 Create HMI Elements

Temperature Gauge

text

Group: Process Monitoring
Tab: Control Room
Size: 1x1
Min: 0, Max: 100
Units: °C
Range colors:
  0-50: green
  50-80: yellow
  80-100: red

Motor Status LED

text

Label: Main Pump
Colors: On=green, Off=grey

Alarm History Table

Use ui_template node with:

html

<div style="max-height: 200px; overflow-y: auto;">
  <div ng-repeat="alarm in alarms | orderBy:'timestamp':true"
       style="padding: 5px; margin: 2px; 
              background-color: {{alarm.severity === 'HIGH' ? '#ffcccc' : '#fff3cd'}}">
    {{alarm.timestamp}} - {{alarm.message}}
  </div>
</div>

🚨 Part 5: Alarm System Implementation

5.1 Alarm Logic Flow

text

[Temperature Sensor] → [Function: Check Limits] → [Alarm Trigger]
                                                     ↓
                                      [High Temp Alarm] → [Dashboard] → [Log File]
                                                     ↓
                                            [Email Alert] (optional)

5.2 Alarm Configuration Node

javascript

// Check temperature limits
let temp = msg.payload;
let alarm = null;

if (temp > 85) {
    alarm = {
        severity: "HIGH",
        message: `CRITICAL: Temperature ${temp}°C exceeds limit`,
        timestamp: new Date().toISOString(),
        acknowledged: false
    };
} else if (temp > 70) {
    alarm = {
        severity: "MEDIUM",
        message: `Warning: Temperature ${temp}°C approaching limit`,
        timestamp: new Date().toISOString(),
        acknowledged: false
    };
}

if (alarm) {
    // Send to dashboard
    node.send([{payload: alarm}, null]);
    
    // Send to log file
    let logMsg = {...msg};
    logMsg.payload = JSON.stringify(alarm);
    node.send([null, logMsg]);
}

🔄 Part 6: MQTT Integration for IIoT

6.1 Install Mosquitto MQTT Broker

bash

# Ubuntu/Debian
sudo apt install mosquitto mosquitto-clients

# Windows
# Download from https://mosquitto.org/download/

6.2 MQTT Flow in Node-RED

text

[Modbus Data] → [MQTT Publish node]
Topic: factory/line1/temperature
QoS: 1 (at least once)
Retain: true

6.3 Subscribe to Commands

text

[MQTT Subscribe node] → [Command Processor]
Topic: factory/line1/commands/+

6.4 Test with MQTT Client

bash

# Subscribe to temperature
mosquitto_sub -h localhost -t "factory/line1/temperature"

# Send command
mosquitto_pub -h localhost -t "factory/line1/commands/fan" -m "ON"

🧪 Part 7: Complete Lab Project

Temperature Control System with SCADA

7.1 System Architecture

text

[OpenPLC Simulator]
        ↓ (Modbus TCP)
   [Node-RED Edge]
        ├── [Dashboard HMI]
        ├── [Alarm Manager]
        ├── [Data Logger]
        └── [MQTT Bridge → Cloud]

7.2 Complete Flow JSON

Download from: [GitHub Gist Link – See Appendix]

7.3 Step-by-Step Implementation

  1. PLC Simulation Setup
    • OpenPLC: Create temperature control program
    • Set Modbus mapping:text40001: Temperature (0-100°C) 40002: Setpoint (70°C) 40003: Fan Status (0/1)
  2. Node-RED Main Flow

json

[{"id":"modbus-read","type":"modbus-read","z":"main","name":"Read Temperature","topic":"","showStatusActivities":true,"showErrors":true,"unitid":"1","dataType":"HoldingRegister","adr":"0","quantity":"1","rate":"2000","rateUnit":"ms","delayOnStart":false,"startDelayTime":"","server":"server1","useIOFile":false,"ioFile":"","useIOForPayload":false,"x":200,"y":100,"wires":[["alarm-check","temp-gauge"]]}]
  1. Dashboard Layout
    • Tab 1: Process Overview
    • Tab 2: Alarms & Events
    • Tab 3: Historical Trends
  2. Data Persistence

javascript

// Add to file node for logging
const fs = require('fs');
const path = './logs/temperature.csv';

// Create CSV if doesn't exist
if (!fs.existsSync(path)) {
    fs.writeFileSync(path, 'timestamp,temperature,setpoint,fan_status\n');
}

// Append data
const data = `${msg.timestamp},${msg.temp},${msg.setpoint},${msg.fan}\n`;
fs.appendFileSync(path, data, 'utf8');

⚙️ Part 8: Industrial Best Practices

8.1 Reliability Patterns

  • Watchdog Timer: Implement heartbeat monitoring

javascript

// Watchdog function - reset every 30 seconds
let lastHeartbeat = Date.now();
setInterval(() => {
    if (Date.now() - lastHeartbeat > 60000) {
        // Restart flow or send alert
        node.error("Watchdog timeout - system unresponsive");
    }
}, 30000);
  • Data Validation: Always validate industrial data

javascript

function validateIndustrialData(data) {
    // Check range
    if (data.temperature < -50 || data.temperature > 200) {
        return {valid: false, reason: "Temperature out of physical range"};
    }
    
    // Check rate of change (prevent spikes)
    if (Math.abs(data.temperature - previousTemp) > 10) {
        return {valid: false, reason: "Rate of change too high"};
    }
    
    return {valid: true};
}

8.2 Basic Cybersecurity

  1. Change default passwords
  2. Use Node-RED projects for version control
  3. Enable HTTPS in settings.js:

javascript

module.exports = {
    https: {
        key: require("fs").readFileSync('privkey.pem'),
        cert: require("fs").readFileSync('cert.pem')
    }
}

8.3 Documentation Standards

  • Use consistent tag naming: PLANT.AREA.DEVICE.SENSOR
  • Add comments to complex function nodes
  • Maintain flow documentation in README

📈 Real-World Applications

Application 1: Energy Monitoring

text

Flow: [Power Meter] → [Modbus] → [Energy Calculator] → [Dashboard]
                                                      → [Peak Alert]
                                                      → [CSV Export]

Application 2: OEE Tracking

javascript

// Overall Equipment Effectiveness
function calculateOEE(availableTime, runtime, goodParts, totalParts) {
    const availability = runtime / availableTime;
    const performance = (idealCycleTime * totalParts) / runtime;
    const quality = goodParts / totalParts;
    
    return {
        oee: (availability * performance * quality) * 100,
        availability: availability * 100,
        performance: performance * 100,
        quality: quality * 100
    };
}

🚀 Next Steps & Advanced Topics

Level Up Your Skills:

  1. Containerization: Run Node-RED in DockerdockerfileFROM nodered/node-red:latest COPY flows.json /data/flows.json
  2. OPC UA Integration: node-red-contrib-opcua
  3. Time-Series Database: Connect to InfluxDBjavascript// Write to InfluxDB const point = new InfluxDB.Point(‘temperature’) .tag(‘machine’, ‘press-1’) .floatField(‘value’, msg.temp);
  4. Cloud Integration: AWS IoT / Azure IoT Hub
  5. Advanced Visualization: Grafana with Node-RED

⚠️ Safety & Limitations

Critical Notes:

  1. Node-RED is NOT a safety system
    • Never use for safety-critical functions (E-stop, safety interlocks)
    • Always use certified safety PLCs for personnel protection
  2. Performance limits
    • Typical scan time: 100ms-1s
    • Not suitable for high-speed control (<50ms)
  3. Best used for:
    • Monitoring and visualization
    • Data acquisition
    • Non-critical control loops
    • Protocol translation
    • Alarm notification

📚 Learning Resources

Free Resources:

  1. Node-RED Official: nodered.org/docs
  2. OpenPLC Documentation: openplcproject.com/docs
  3. Industrial IoT GitHub: github.com/industrial-iot

Recommended Books:

  • “Industrial Automation from Scratch” by P. Obakpolo
  • “Node-RED Guide” by A. Sharpe

🎓 Final Project Challenge

Build a complete system that:

  1. Simulates 3 temperature sensors
  2. Controls 2 cooling fans based on average temperature
  3. Implements high/low alarms with acknowledgment
  4. Logs data to CSV daily
  5. Displays on a professional dashboard
  6. Sends MQTT data to a cloud service (optional)

Success criteria: System runs for 24 hours without crashes, maintains data integrity, and provides clear operator interface.

📝 Appendix: Quick Reference Commands

Node-RED Useful Commands

bash

# Start with settings file
node-red -s settings.js

# List installed nodes
npm list --depth=0

# Backup flows
cp ~/.node-red/flows.json ./backup/

Modbus Testing Tools

bash

# Install modbus-cli
npm install -g modbus-cli

# Read register
modbus read -a 1 -t holding -c 1 localhost 40001

🆘 Troubleshooting Common Issues

ProblemSolution
Modbus connection failedCheck firewall, verify PLC IP
Dashboard not loadingClear browser cache, restart Node-RED
High CPU usageCheck for infinite loops, reduce polling rate
Memory leaksMonitor with node-red-admin log

📄 License & Attribution

This tutorial is open-source under MIT License. Always verify designs with certified engineers before industrial deployment.

Ready to automate? Deploy your first industrial flow today!

🔧 Ready-to-Use Resources:

Note: Replace # with actual links in published version

Our Expert Engineer could be contacted globally anytime.