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The Microchip AVR128DA48 Curiosity Nano Evaluation Kit provides a flexible development board for evaluating features of the AVR128DA48 microcontroller and prototyping Internet of Things (IoT) applications. The onboard AVR128DA48 microcontroller uses the Microchip AVR® CPU with hardware multiplier, running up to 24MHz. It has 128KB flash memory, 16KB SRAM, and 512 bytes of electrically erasable programmable read-only memory (EEPROM) for use by application programs.
The microcontroller features a wide range of peripherals, including five USART, two Serial Peripheral Interface (SPI), two Two-Wire Interface (TWI)/I2C, 1 ADC with 18 channels, one digital-to-analog converter (DAC), three analog comparators, two zero-cross detectors, multiple timers/counters, a peripheral touch controller, and 41 general-purpose in/out pins. The Curiosity Nano board adds a user-programmable LED and push button, an onboard debugger interface for programming and debugging, two logic analyzer channels (Debug General Purpose Input/Output), a virtual serial port Communication Device Class (CDC), and can be powered via USB or an external power source. The microcontroller target voltage is adjustable between 1.8V and 5.1V via a voltage regulator controlled by the onboard debugger. Two sets of 28-pin headers provide easy access to microcontroller signal pins that connect peripherals or expansion adapters such as the Curiosity Nano Base for Click boards™.
A choice of Integrated Development Environments (IDEs)—including Microchip Atmel Studio, Microchip MPLAB® X, and IAR Embedded Workbench® for AVR®—supports software development for the AVR128DA48 Curiosity Nano Evaluation Kit. Microchip's Atmel START and MPLAB® Code Configurator tools provide graphical user interfaces for configuring microcontroller peripherals and functions specific to your application. A collection of pre-written software libraries and example projects jump-start development. GitHub publishes code examples. Additional Microchip tools for data visualization allow you to examine real-time data generated by the Curiosity Nano board through serial port or on-board debugger interfaces.
The Medium One IoT Platform cloud-based platform helps early-stage developers prototype their IoT project or connect their existing hardware to the cloud. An IoT Data Intelligence platform enables customers to build IoT applications with less effort quickly. Programmable workflows quickly build processing logic without having to create your own complex software stack. A graphical workflow builder and run-time engine processes 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, MQTT, SMS text messaging, and integration with Twitter, Salesforce, and Zendesk. Snippets of Python code create custom workflow modules. 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. REST APIs or MQ Telemetry Transport (MQTT) protocol handle communications between IoT devices and the Medium One cloud. Visualize application data and view real-time data in various formats with configurable dashboards. Dashboard widgets for tabular data, charts, geopoint maps, gauges, and user inputs are also included. Medium One’s iOS and Android apps build simple mobile app dashboards that can communicate with your devices through the platform.
To use your own AVR128DA48 Curiosity Nano with the Medium One IoT Platform, check out our step-by-step article that walks you through the entire process of:
Here, 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 extending and adapting 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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