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With Node-RED 4.0 coming soon, I wanted to take a look at what users can expect to see with the new release, as well as some of the new features we're working on.

Practitioners using Node-RED often find themselves in a situation where a firewall is deployed in their organization. This network configuration is a fact of life and is generally not controlled by the same people using Node-RED. Given security reigns supreme in Industrial IoT (IIoT), and a firewall offers a lot of benefits, we anticipate it will be deployed more often in the future, and as such it’s good to understand how you can get the most out of Node-RED when deployed behind a firewall.

It's quite straightforward to pass plenty of useful data with each message (msg) in your flows. Not only can you store information in msg.payload, but you can also place information in any other named object, for instance, msg.store.

Have you ever wanted to integrate speech recognition and synthesis into your Node-RED project and thought it was too complex? Often it has required external services or APIs. However, in this guide, we show you how you can use speech recognition and synthesis in your Node-RED projects without needing an external service or API.

In addition, we make things more interesting by building a system that can listen to us and respond like humans using the Chat-GPT API. Let's get started!

Have you ever built a sentiment analysis system to extract insights from text content? If yes then I don’t think you'll need an explanation of how complex it is to build. In this guide, we will build a sentiment analysis system with Node-RED using Dashboard 2.0 in a few easy steps.

While cloud computing has revolutionized data access and analysis, not all data can be accessed from the cloud. In many scenarios, data collection from the edge – the location where data is generated – is essential for real-time decision-making or process observability.

When ChatGPT was first released, my expectations were quite low. I had grown accustomed to the usual industry buzz for AI and ML that often led to underwhelming solutions. Naturally, I approached ChatGPT with similar reservations. It wasn't until a few months after its announcement that I decided to give it a try. To my surprise, within just 10 minutes, I found myself so captivated that I decided to purchase the pro version.

As we continue to add features to the Node-RED Dashboard v2 one feature request that came in was to track which users had visited a Dashboard. Multi user support for the Dashboard is on the backlog but this could be solved with the parts that are currently available.

Manufacturing companies often struggle to choose between building custom MES solutions or buying ready-made software. Both options have their strengths, but they can fall short of providing the flexibility and control engineers need. A hybrid approach—combining the best of both worlds—is changing the game. In this article, we’ll explore how Node-RED and FlowFuse make it easier to create MES systems that are efficient, adaptable, and perfectly suited to your needs.

Vuetify is a library of UI components using Vue. This saves the developers of Dashboard 2.0 a lot of time, but it can also help you, the end-user. As Vuetify is now included, it can be used to include any of their components. So in this post we're going to use a few of these to teach you how to use any of them.

ChatGPT has the potential to have a significant impact on the Node-RED community. It is a powerful language model that can be used to generate flows, interpret them, and provide documentation, maybe soon even write the flow! The combination of ChatGPT, or generative AI at large, with Node-RED can significantly improve the developer experience with Node-RED. In this post we’ll review what the community has already built.

Industrial systems generate valuable data, but legacy protocols like Modbus or non-IIoT standards often make it hard to use. Bridging this gap is essential to connect traditional systems with the modern Industrial Internet of Things (IIoT).

Whether it’s Modbus registers, serial communication without a protocol, or standards like Siemens S7 and Mitsubishi MC-Protocol, the challenge lies in making sense of this raw information. With tools like Node-RED and the node-red-contrib-buffer-parser, you can turn complex, outdated data streams into usable formats that power IIoT innovation.

Using images in your Node-RED dashboards can significantly improve your users' experience. The most common method to add images to dashboards is to store them within the filesystem of an Node-RED instance but sometimes that's not an option. How can you easily use images when working in a containerized environment such as Docker, or Kubernetes? We will also explore latest feature from FlowFuse that makes this step super easy.