reComputer R1000 Walk Through
The reComputer R1000 edge IoT controller, powered by Raspberry Pi CM4, features a quad-core A72 processor, dual Ethernet, and multiple RS485 channels supporting BACnet, Modbus RTU, and Modbus TCP/IP. With versatile wireless options including 4G, LoRa®, and Wi-Fi/BLE, it ensures robust IoT network communication. Ideal for remote device and energy management, the R1000 is perfect for smart building applications.
reComputer R1000 Application
Guides for First Look
| reComputer R1000 Getting Started | reComputer R1000 Raspbian OS to eMMC |
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| This article focuses on providing an overview of the reComputer R1000, detailing its hardware interfaces and optional hardware components. It highlights the features and capabilities that make the R1000 suitable for various IoT applications. | The reComputer R1000 comes with a preloaded image of Raspbian. If you need to reinstall it, this guide will show you how to install Raspbian again. |
| reComputer R1000 Assembly Guide | How to use rs485 and modbus rtu with reComputer R1000 | reComputer R1000 use bacnet MS/TP |
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| This Wiki will show you how to Assemble and Disassemble the unit to install peripherals components, as well as the option for mounting | This article mainly introduces how to use the RS485 communication function of reComputer R1000, and tests the RS485 and Modbus communication functions. | This article mainly introduces how to perform functional testing of bacnet MS/TP protocol on reComputer R1000.We simulated a bacnet MS/TP server on reComputer R1000, and then used YABE on the W10 PC to check whether the device is present. |
Industrial Edge
Node-RED| reComputer R1000 Getting Started with Node-Red | reComputer R1000 with Node Red and MQTT | reComputer R1000 with Node Red and Modbus TCP |
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| Discover how to install and configure Node-RED on reComputer R1000, transforming it into a versatile tool for connecting hardware, APIs, and online services. Utilize the intuitive browser-based flow editor to seamlessly integrate various components using a rich palette of nodes. | Explore the installation of the Mosquitto broker and learn how to work with Node-RED to subscribe and publish MQTT topics in this wiki. Ideal for IoT applications, MQTT enables efficient, real-time data exchange with low bandwidth over unreliable networks. | Learn how to work with Modbus TCP on reComputer R1000 using Node-RED in this wiki. Discover how Modbus TCP extends the protocol to Ethernet networks, enabling faster communication speeds and seamless integration with modern IT infrastructure. |
| reComputer R1000 with Node Red and BACnet TCP | reComputer R1000 with Node Red and InfluxDB | reComputer R1000 with Grafana |
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| Discover the advantages of BACnet IP in Building Management Systems (BMS) with this wiki, focusing on Node-RED integration. Learn how to achieve improved scalability, easier installation and maintenance, and leverage existing network infrastructure using Node-RED and BACnet IP. | Deploy InfluxDB on an reComputer R1000, a Raspberry Pi-powered edge controller, for robust time-series data collection and analysis at the network edge. This guide details the steps to install, configure, and use InfluxDB, enabling efficient management and real-time insights for IoT applications. | Learn how to install Grafana on a Raspberry Pi-powered reComputer R1000 in this wiki, transforming your data into insightful visualizations. Connect Grafana to an existing InfluxDB database and create an illustrative dashboard to enhance system performance, streamline troubleshooting, and make informed decisions with powerful monitoring tools. |
| reComputer R1000 with Node Red and OPC UA server with Node-RED | Connecting Siemens PLCs Using the S7 Protocol with reComputer R1000 | reComputer R1000 with FlowFuse |
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| This wiki will guide you through creating an OPC UA server in the Node-RED environment, integrating various protocols for improved interoperability across the automation hierarchy. | This article explains how to use Node-RED, a flow-based development tool, on a Raspberry Pi-powered reComputer to communicate with Siemens PLCs via the S7 Protocol. | FlowFuse extends Node-RED with tools for collaborative development, remote deployments, and DevOps pipelines, making it easier to manage and deliver Node-RED applications. This wiki will explore how FlowFuse streamlines these processes for development teams. |
| reComputer R1000 with N3uron | reComputer R1000 Connect AWS IoT Core with N3uron |
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| Easily create bidirectional data pipelines between OT and IT systems with N3uron, consolidating and visualizing operational data in a single source. Learn to install and access N3uron using reComputer R1000 | In this tutorial, we will delve into the intricacies of interfacing between the N3uron Edge IIoT platform and AWS IoT Core. |
| Connect N3uron with BACnet on reComputer R1000 | Publishing Industrial Data to AWS Cloud Using N3uron, MQTT, and Modbus |
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| Discover the power of BACnet in Building Management Systems with N3uron, enhancing data acquisition and management for seamless interoperability. Utilize BACnet TCP with the YABE Room Simulator to visualize and test BACnet devices, ensuring robust and flexible BMS solutions. | Enhance plant management with reComputer R1000 and N3uron Duo, leveraging robust connectivity and data manipulation capabilities. This Wiki guides you through connecting with Modbus TCP and MQTT for seamless industrial integration. |
| reComputer R1000 with FUXA to use Modbus RTU/TCP | reComputer R1000 with FUXA to use MQTT client | reComputer R1000 with FUXA to use OPC-UA |
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| This article primarily explains how to use FUXA for Modbus RTU/TCP communication. It covers the basics of Modbus and demonstrates its applications in various scenarios. | This article mainly introduces how to use FUXA for mqtt communication on reComputerR1000. This article uses mosquitto as the MQTT server agent, FUXA and node-red as the MQTT client, and introduces a ModbusTCP slave as the source of data published by FUXA. | This article mainly introduces how to use FUXA for OPC-UA communication.We run Prosys OPC UA Simulation Server on W10 PC, and then read the data of the simulator on reComputer R1000. |
| reComputer R1000 with FUXA to use WebAPI | reComputer R1000 with FUXA to achieve SCADA |
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| This article mainly introduces how to use FUXA for WebAPI communication.At this stage, FUXA only supports the GET function, and the data packet is in Json format.We will use FUXA's GET function to obtain the datagram of postman. | This article mainly introduces how to use FUXA to achieve SCADA. In the article, FUXA receives data from node-red and OPC UA Simulator, and displays it using chart and Circular Gauge; at the same time, it draws a series of patterns to simulate industrial processes. |
| How to install CODESYS for reComputer R1000 | How to use CODESYS to configure the Modbus RTU function of R1000 |
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| CODESYS, developed by 3S-Smart Software Solutions, is a widely used automation software platform for industrial control systems. This article focuses on how to download, install CODESYS, and deploy a project to the reComputer R1000. | This article mainly introduces how to use the modbus rtu function of reComputer R1000 based on CODESYS. We will use the two rs485 ports of reComputer R1000, one port is used for Modbus master and the other port is used for Modbus slave. |
| reComputer R1000 install FIN | reComputer R1000 with FIN to use modbus TCP/RTU | reComputer R1000 with FIN Logic Builder |
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| FIN Framework (FIN) is a software framework with application suites that can integrate, control, manage, analyze, visualize and connect. Its capabilities can be integrated by OEMs into a range of products and services.This article mainly introduces how to install Fin on reComputer R1000. | This article introduces how to use the Modbus Connector of FIN Framwork, the use of Modbus TCP/RTU in FIN Framwork was explained in detail. | This article will show you how to use the Logic Builder of FIN Framwork, and to implement an alarm using the Logic Builder.We monitor the value of a Modbus device. When the value exceeds the critical value, FIN will alarm. |
| reComputer R1000 with FIN to create a Top Level Graphic | reComputer R1000 with FIN to create a Site Graphic | reComputer R1000 with FIN to create a Floor Graphic |
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| This article will show you how to use the Graphics Builder of FIN Framwork, and to create a Top Level Graphic using the Graphics Builder. | This article will show you how to use the Graphics Builder of FIN Framwork, and to create a Site Graphic using the Graphics Builder. | This article will show you how to use the Graphics Builder of FIN Framwork, and to create a Floor Graphic using the Graphics Builder. |
Fleet Management
| reComputer R1000 balena OS Setup |
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| Balena: IoT platform for developers to deploy and manage applications across device fleets. Supports diverse architectures, enabling easy updates and secure, reliable device operation in the field. |
Cloud Solutions
| AWS IoT Core Intergate With reComputer R1000 |
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| Learn how to connect your reComputer R1000 to the AWS IoT cloud in this comprehensive guide. Leverage AWS IoT Core for secure device management and seamless communication, enabling the development of smart, connected applications within the AWS ecosystem. |
Computer Vision
| YOLOv8 Object Detection on reComputer R1000 with Hailo-8L | YOLOv8 Pose Estimation on reComputer R1000 with Hailo-8L |
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| This wiki demonstrates object detection using YOLOv8 on reComputer R1000 with and without Raspberry-pi-AI-kit acceleration. The Raspberry Pi AI Kit enhances the performance of the Raspberry Pi and unlock its potential in artificial intelligence and machine learning applications | This wiki demonstrates pose estimation using YOLOv8 on reComputer R1000 with and without Raspberry-pi-AI-kit acceleration. The Raspberry Pi AI Kit enhances the performance of the Raspberry Pi and unlock its potential in artificial intelligence and machine learning applications |
| Benchmark on RPi5 and CM4 running yolov8s with rpi ai kit | Install M.2 Coral to Raspberry Pi 5 |
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| This wiki showcases benchmarking of YOLOv8s for pose estimation and object detection on Raspberry Pi 5 and Raspberry Pi Compute Module 4. All tests utilize the same model (YOLOv8s), quantized to int8, with an input size of 640x640 resolution, batch size set to 1, and input from the same video at 240 FPS. | This wiki we will show you how to install Coral M.2 Accelerator to Raspberry Pi 5 and finally we will test Coral M.2 Accelerator. |
| Convert Model to Edge TPU TFlite Format for Google Coral | Pose-Based Light Control with Node-Red and Raspberry Pi with AIkit | Tutorial of AI Kit with Raspberry Pi 5 about YOLOv8n object detection |
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| This wiki article will guide you through the process of compiling a model and running it on the Google Coral TPU, enabling you to leverage its capabilities for high-performance machine learning applications. | his wiki will guide you on how to run YOLOv8 using an AI kit, use YOLOv8 to monitor your posture, and ultimately control your lights based on your posture. | This wiki will guide you on how to use YOLOv8n for object detection with AI Kit on Raspberry Pi 5, from training to deployment. |
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