BL310 + Node-RED + MQTT: Building a Lightweight Industrial IoT Data Flow Architecture

In the era of Industry 4.0, factories are rapidly evolving toward data-driven operations. However, many industrial environments still face challenges such as protocol fragmentation, complex system integration, and high deployment costs.

A modern solution is emerging: combining an NXP I.MX6ULL ARM-based edge computer like BL310, with Node-RED for low-code orchestration, and MQTT for efficient data transmission.

This architecture delivers a simple, scalable, and cost-effective way to enable industrial data flow from field devices to the cloud.

System Architecture Overview

The architecture can be divided into four layers:

Device Layer

This layer includes:

• Sensors (temperature, pressure, flow)

• PLCs, meters, inverters

• Communication protocols such as Modbus RTU/TCP, CAN

Edge Layer (BL310)

At the core is the BL310 industrial ARM-based embedded computer:

• Connects to field devices via RS485, Ethernet, or CAN

• Runs Node-RED locally

• Performs data acquisition, preprocessing, and logic control

Communication Layer (MQTT)

MQTT acts as the bridge between edge and cloud:

• Lightweight publish/subscribe protocol

• Low bandwidth usage

• Supports TLS encryption for secure transmission

• Works over Ethernet, WiFi, or 4G

Cloud / Platform Layer

Typical platforms include:

• AWS IoT, Azure IoT Hub, EMQX, ThingsBoard

• Functions: data storage, visualization, analytics, and alerts

Why BL310 + Node-RED + MQTT?

Low-Code Development with Node-RED

Node-RED enables engineers to:

• Build data flows using drag-and-drop nodes

• Rapidly deploy without complex programming

• Integrate multiple protocols easily

This significantly reduces development time and engineering effort.

Edge Computing for Real-Time Intelligence

Running logic directly on BL310 provides:

• Local data filtering and aggregation

• Real-time decision-making (e.g., alarms)

• Data buffering during network outages

Benefits:

• Reduced cloud workload

• Lower latency

• Improved system reliability

MQTT for Efficient Data Transmission

MQTT is ideal for industrial IoT because:

• It uses a publish/subscribe model

• Minimizes network overhead

• Scales to thousands of devices

Protocol Decoupling and Scalability

With Node-RED, you can easily convert:

• Modbus → MQTT

• CAN → MQTT

• OPC UA → MQTT

This decouples field protocols from cloud applications, making the system highly flexible and future-proof.

Typical Node-RED Data Flow

A typical workflow includes:

Data Acquisition

• Use Modbus nodes to read PLC or sensor data

Data Processing

• Apply logic using Function nodes

• Format data into JSON

Data Publishing

• Send data via MQTT Out node

• Topic: factory/line1/data

Application Scenarios

Smart Manufacturing

• Equipment monitoring

• OEE data collection

• Production optimization

Energy Management Systems (EMS)

• Power meter integration

• Energy consumption analysis

• Demand optimization

EV Charging Infrastructure

• Real-time charging data monitoring

• Remote diagnostics

• Fault alerts

Smart Buildings / HVAC

• BACnet and Modbus integration

• Centralized building management

• Energy efficiency optimization

Key Advantages of BL310

Industrial-Grade Reliability

• Wide temperature range

• Fanless design

• Strong anti-interference

Rich Interfaces

• RS485 / RS232

• Dual Ethernet

• Optional 4G / WiFi

Open Software Ecosystem

• Linux-based system

• Supports Node-RED, Docker

• Compatible with Python, C, Java

Future-Ready Edge Intelligence

• AI inference (lightweight vision or prediction)

• Local rule engines

• Advanced data analytics

Conclusion

The combination of BL310 + Node-RED + MQTT represents a powerful yet lightweight architecture for industrial IoT:

• Simple: Low-code deployment

• Efficient: Edge computing + MQTT

• Flexible: Protocol decoupling

• Scalable: Ready for future expansion

For enterprises looking to modernize their industrial systems, this solution provides a fast, reliable, and cost-effective path toward digital transformation.