Node-RED is an open source visual programming platform initially developed by IBM in 2013, designed to connect hardware devices, APIs and online services in a simple and intuitive way in data flows. Node-RED's ease of use, with its drag-and-drop interface, allows users to create applications without the need to code, making it accessible to developers of all levels. Node-RED stands out for its flexibility thanks to its extensible palette system, allowing users to enrich the environment with new protocols and nodes. This modularity opens up vast horizons for the integration of diverse technologies, facilitating the addition of tailor-made functionalities and the expansion of the platform's capabilities to meet specific needs.
Node-RED and LoRaWAN: A Synergy at the Heart of IoT
The relationship between Node-RED and LoRaWAN is particularly relevant in the context of IoT. LoRaWAN is a communication protocol for low-power wide-area networks, ideal for IoT applications requiring long range and low power consumption, such as environmental monitoring, energy management, and smart agriculture. Node-RED, with its low-code approach, allows easy and fast integration of LoRaWAN devices, providing a platform for creating data streams that process and analyze the information collected by these devices. This combination paves the way for innovative IoT solutions, allowing professionals to implement complex IoT applications without requiring deep programming expertise.
Node-RED and LoRaWAN: Simplification and Customization of IoT Projects with our Gateways
Our LoRaWAN gateways UG56, UG65 And UG67 allow you to use Node-RED efficiently and allow you to have a simple network diagram of your projects.
Let's take the following example, we have two products, one AM103 which is a detector (CO2, temperature and humidity), as well as a WS558 which is a smart lighting controller. With Node-RED we can filter the LoRaWAN data that we receive by specifying the EUI of our two products, the latter then pass into decoders to be able to interpret the data, once processed, the data can be converted to CSV format then sent in FTP as in the case of the AM103 or converted with a function that allows the lighting to be activated or not and then written in BACnet (if you do not know what BACnet is I invite you to look at our article on it as well as possible use cases here).
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