Connecting the SiLabs XBee3 LTE-M Expansion Kit to Medium One IoT Cloud
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The Silicon Labs XBee3® LTE-M Expansion Kit contains a pre-certified LTE-M modem from DIGI International that provides cellular internet connectivity to the cloud. When combined with the EFM32™ Giant Gecko 11 Starter Kit, it offers a flexible Internet of Things (IoT) development platform for sensing, processing, and control applications that communicate wirelessly over LTE-M cellular networks. The LTE-M Expansion Kit includes a GNSS receiver, LTE-M patch antenna, and global SIM card supporting multiple carriers. LTE-M modem control is performed using AT commands, API frames, or built-in MicroPython programmability for custom scripting directly on the modem. A header connector on the board connects to an EFM32 Giant Gecko GG11 board running user applications. The Giant Gecko GG11 contains a SiLabs EFM32 microcontroller with 2MB flash and 512KB RAM. Onboard peripherals provide a range of input/output options including color LCD display, two push buttons, two LEDs, a capacitive touch slider, temperature and humidity sensor, hall-event and inductive LC sensors, dual microphones, 32MB Quad-SPI flash memory, micro-SD card slot, RJ-45 Ethernet jack, and breakout pads for easy access to I/O pins. A USB cable or a coin cell battery powers the board and the onboard Advanced Energy Monitor system allows for precise current tracking. An integrated Segger J-Link debugger supports programming and debugging without needing to purchase additional debugger dongles.
Silicon Lab’s Simplicity Studio Integrated Development Environment (IDE) supports software development for the Giant Gecko GG11. The Simplicity Studio environment includes a compiler, debugger, and linker along with configurable software components and support packages for the Giant Gecko and other SiLabs boards and components. Software Development Kits (SDKs), example programs, and API documentation support the development of new applications involving input/output, signal and data processing, and network communications. Simplicity Studio works with the onboard debugger built into EFM32 development boards for debugging and troubleshooting application code.
The Medium One IoT Platform cloud-based platform helps early-stage developers prototype their IoT project or connect their existing hardware to the cloud. It offers an IoT Data Intelligence platform enabling customers to quickly build IoT applications with less effort. Programmable workflows allow you to quickly build processing logic without having to create your own complex software stack. A graphical workflow builder and run-time engine let you process IoT data as it arrives and route or transform it as needed for your application. Workflow library modules are available for data analytics, charting, geolocation, weather data, MQ Telemetry Transport (MQTT), SMS text messaging, and integration with Twitter, Salesforce, and Zendesk. Custom workflow modules can be created using snippets of Python code. End-to-end workflows are designed and built using the web-based Workflow Studio, which provides a drag-and-drop visual programming environment. Workflow versioning and debugging tools support the development, test, and deployment lifecycle. Communications between IoT devices and the Medium One cloud are done through REST APIs or MQTT protocol. Configurable dashboards allow you to visualize application data and view real-time data in a variety of formats. Dashboard widgets are included for tabular data, charts, geopoint maps, gauges, and user inputs. Medium One’s iOS and Android apps allow you to also build simple mobile app dashboards that can communicate with your devices through the platform.
To use your own SiLabs XBee3 LTE-M Expansion Kit and EFM32 Giant Gecko GG11 Starter Kit with the Medium One IoT Platform, check out our step-by-step Connecting the SiLabs XBee3 LTE-M Expansion Kit to Medium One IoT Cloud article that walks you through the entire process of:
In this article, we also show you how to observe the published data on a real-time dashboard created in the Medium One environment. A set of next steps gives suggestions for how to extend and adapt the application for different IoT prototyping scenarios or to learn more.
Greg is an architect, engineer and consultant with more than 30 years experience in sensors, embedded systems, IoT, telecommunications, enterprise systems, cloud computing, data analytics, and hardware/software/firmware development. He has a BS in Electrical Engineering from the Univ. of Notre Dame and a MS in Computer Engineering from the Univ. of Southern California.
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