Connecting Infineon XENSIV™ Sensors Getting Started Box IoT to Medium One IoT Platform
The Infineon Technologies XENSIV™ Sensors - Getting Started Box IoT is an Internet of Things (IoT) development kit featuring sensors, microcontrollers, and security chips for prototyping and evaluating IoT applications. The development kit includes four microcontroller boards in different form factors and four types of sensors encompassing 3D magnetic sensing, pressure and temperature, electrical current, and sound. The sensors use a standardized Shield2Go form factor with solderless pins for easy plug-and-play assembly. An ESP32-based microcontroller board provides Wi-Fi and Bluetooth® Low Energy (BLE) connectivity allowing sensors to connect to the internet for data communications. An Arduino Uno form factor Infineon XMC™ Arm® Cortex®-M0 based microcontroller board allows the use of other types of Arduino-compatible boards. Additional adapter boards allow multiple mix-and-match combinations of microcontrollers, sensors, and Arduino-compatible boards for specific prototyping or evaluation use cases. The Getting Started Box IoT includes two OPTIGA™ Trust X security chip implementations for applications that need an advanced security controller with cryptographic support. The kit also includes a mechanical rotate knob and joystick for the 3D magnetic sensor that supports rotational, push button, and three-dimensional joystick use cases.
The Arduino Integrated Development Environment (IDE) supports software development for the XENSIV™ Sensors - Getting Started Box IoT. The Arduino IDE includes a compiler and linker along with software components and support packages for boards included in the Getting Started Box IoT. The Arduino ecosystem also offers many other software components. The boards and sensors included in the Getting Started Box IoT have software support libraries published on GitHub that can be downloaded and installed in the Arduino IDE for application development. The GitHub repositories also provide additional example programs illustrating how to control and use the various components.
The Medium One IoT Platform is a cloud-based platform designed to help 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:
You can also create custom workflow modules can be created using snippets of Python code. The web-based Workflow Studio, which provides a drag-and-drop visual programming environment, designs and builds end-to-end workflows. Workflow versioning and debugging tools support the development, test, and deployment lifecycle. Communications take place between IoT devices and the Medium One Cloud using 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 build simple mobile app dashboards that can communicate with your devices through the platform.
To use your own XENSIV™ Sensors - Getting Started Box IoT with the Medium One IoT Platform, check out our step-by-step 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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