Avnet has worked with Microchip to create an out-of-box demonstration showing how quickly and easily OEMs can connect Microchip product to a cloud service using Avnet's /IOTCONNECT™ solution acceleration software.
We make it easy:
- Device to Cloud onboarding in minutes
- No credit card required
- No prior Cloud experience needed
- Pre-compiled image, no additional software needed
- Demonstrate the hardware's unique functionality in the Cloud
- Enable users to build on their Quick Start journey and into development
/IOTCONNECT features elements that integrate into both endpoints and cloud platforms to create secure end-to-end connections with minimal configuration. In addition, /IOTCONNECT provides web-based dashboards that make it easy to interact with your IoT application from anywhere. With diverse connectivity options, strong data protection measures, and true scaling capabilities, /IOTCONNECT empowers organizations to leverage the full potential of IoT technology and accelerate digital transformation.
Sensor-to-Cloud via BLE Beacon and Gateway
SAMA7D65 Curiosity Kit (EV63J76A) + WBZ451HPE Curiosity Board (EV79Y91A)
- This demo was highlighted at Microchip Masters Beer Boat Regatta event.
- The demo uses the Microchip SAMA7D65 Curiosity Kit (EV63J76A) and WBZ451HPE Curiosity Board (EV79Y91A) to transmit onboard temperature telemetry as a BLE beacon to /IOTCONNECT™.
- The WBZ451HPE Curiosity Board (EV79Y91A) acts as the BLE beacon that broadcasts onboard sensor telemetry.
- The SAMA7D65 Curiosity Kit (EV63J76A) acts as a gateway that receives BLE telemetry and forwards it to the cloud.
- A live /IOTCONNECT™ dashboard displays onboard temperature readings in near real time.
Keyword Spotting - Edge MPU for Industrial AI Controls
SAMA7D65 Curiosity Kit (EV63J76A)
- This demo uses the Microchip SAMA7D65 Curiosity Kit (EV63J76A) to perform keyword spotting and publish inference results to /IOTCONNECT™.
- The SAMA7D65 MPU features a high-performance Arm® Cortex® A7 processor running up to 1 GHz.
- A TensorFlow Lite DS-CNN model performs voice command classification directly on the device.
- Audio is captured from a USB microphone and processed locally using MFCC feature extraction.
- Detected commands and confidence scores are streamed to /IOTCONNECT™ for monitoring and control.
FPGA-Enhanced ML Classification (PolarFire® SoC DK)
PolarFire® SoC Discovery Kit (MPFS-DISCO-KIT)
- This demo uses the PolarFire® SoC Discovery Kit (MPFS-DISCO-KIT) to perform machine learning classification and publish results to /IOTCONNECT™.
- The PolarFire SoC combines a multicore RISC-V® processor subsystem with low power FPGA fabric.
- A neural network classifier processes waveform data using software and FPGA accelerated inference paths.
- DMA based batch processing enables higher throughput for machine learning workloads running in FPGA fabric
- The PolarFire® SoC Discovery Kit supports secure onboarding, telemetry collection, and OTA updates for connected edge AI deployments.
FPGA-Accelerated Vision AI (PolarFire® Video Kit)
PolarFire® SoC Video Kit (MPFS250-VIDEO-KIT)
- This demo uses the PolarFire® SoC Video Kit (MPFS250-VIDEO-KIT) to accelerate AI inference at the edge and publish results to /IOTCONNECT™.
- The PolarFire SoC combines multicore RISC-V® processing with low power FPGA fabric on a single device.
- The platform is designed for embedded vision applications and supports dual 4K MIPI CSI-2 cameras, HDMI 2.0, PCIe®, and high speed networking interfaces.
- DMA based batch processing enables higher throughput for machine learning workloads running in FPGA fabric
- The Video Kit supports secure onboarding, telemetry collection, and OTA updates for connected edge AI deployments.
Scalable Edge Computing - Asymmetric Multiprocessing
PIC64GX Curiosity Kit (CURIOSITY-PIC64GX1000-KIT)
- This demo uses the PIC64GX1000 Curiosity Kit (CURIOSITY-PIC64GX1000-KIT) to showcase asymmetric multiprocessing and edge to cloud connectivity through /IOTCONNECT™.
- The Curiosity PIC64GX1000 Kit features a multicore 64 bit RISC-V® architecture designed for Linux and embedded processing applications.
- Linux and real time workloads run on separate processor cores to support parallel execution.
- Asymmetric multiprocessing enables workload isolation and scalable edge computing performance.
Multi-Protocol IoT Connectivity
- Avnet offers out-of-the-box connectivity demos that accelerate evaluation and cloud onboarding across multiple wireless technologies.
- These platforms include prebuilt examples, security features, and connectivity resources to help developers get started quickly.
Wi-Fi 4: WFI32E Curiosity (EV12F11A)
The WFI32E Curiosity Board (EV12F11A) is a standalone Wi-Fi® 4 platform that combines a Wi-Fi MCU, integrated secure element, and cloud-ready connectivity.
LTE-M: AVR-IoT Cellular Mini (EV70N78A)
The AVR-IoT Cellular Mini (EV70N78A) is a standalone LTE-M platform that combines cellular connectivity, security features, and rapid cloud integration.
Secure Cloud Wi-Fi: SAMA7D65 + RNWF11
SAMA7D65 Curiosity Kit (EV63J76A) + WiFi via UART: RNWF11 WiFi Add-on Board (EV12H55A)
- This demo provides step-by-step instructions to set up the Microchip SAMA7D65-Curiosity Kit (EV63J76A) with the RNWF11 Wi-Fi Add-on Board (connected to SAMA7D65 via UART) (EV12H55A) attached, and integrate it with /IOTCONNECT, Avnet's robust IoT platform.
- The RNWF11 Wi-Fi board communicates over UART using ASCII AT commands.
- The SAMA7D65 MPU is a high-performance ARM Cortex-A7 running up to 1GHz.
- This base setup enables any new application to be built using Wi-Fi enablement on the SAMA7D65.
- In this demo (optional) we are using a MikroE environmental ClickBoard to publish temperature, humidity, and pressure telemetry to the cloud.
Secure Current-Sensing to Cloud
PIC32CM LS60 Curiosity Pro Evaluation Kit (EV76R77A)
- This demo uses the PIC32CM LS60 Curiosity Pro (EV76R77A) to collect sensor data and publish telemetry to /IOTCONNECT™ over Wi-Fi.
- The PIC32CM LS60 features an Arm® Cortex®-M23 MCU with TrustZone® technology and an onboard ATECC608 secure element.
- The device authenticates using mutual TLS with factory provisioned X.509 certificates stored in the onboard ATECC608 secure element. The demo supports cloud monitoring and control with telemetry, sensor inputs, and remote device commands.
Cloud-Updatable ML Model on Zephyr
SAM E54 Xplained Pro (ATSAME54-XPRO)
- This demo uses the SAM E54 Xplained Pro (ATSAME54-XPRO) to update machine learning models from /IOTCONNECT™ without reflashing firmware.
- The SAM E54 features a high performance Arm® Cortex®-M4F MCU for real time edge intelligence applications.
- New models are validated, deployed, and activated on the device through cloud initiated commands.
- Model updates persist in nonvolatile memory and remain active across device reboots.
- The demo uses temperature and light sensor data to demonstrate multiple classification models with different behaviors.
SAMA5D27
EVAL Board, 32BIT MPU, ARM Cortex-A5
The Microchip SAMA5D27 SOM1 is a small single-sided System-On-Module (SOM) based on the high-performance System-in-Package 32-bit Arm® Cortex®-A5 processor-based MPU SAMA5D27 and 1Gb DDR2 SDRAM running up to 500 MHz. The SAMA5D27 SOM1 is built on a common set of proven Microchip components to reduce time to market by simplifying hardware design and software development.
Secure Telehealth and Medical Technology
Join Microchip for a discussion on new telehealth and medical device technology. This 50-minute on-demand presentation and demo includes some ways medical device designers can meet the demand for telehealth, remote patient monitoring, wearable, portable, connected drug delivery devices, and more.
Developing a Soil Moisture Sensor with the AVR-IoT Cellular Mini Board and Avnet's /IOTCONNECT
Join Microchip’s Wizard of Make for this webinar replay as he follows the path of taking an existing soil moisture sensor system based on LoRa RF technology and introduces an LTE-M based solution using the Microchip AVR-IoT Cellular Mini development board (EV70N78A) and the /IOTCONNECT Web service from Avnet. This session covers all aspects of the design from the initial requirement specification to the final implementation of the data dashboard on the web. 60 minutes.
Modernized Condition Monitoring With Next-Generation Sensors and IoT Platforms
This webinar highlights how TE Connectivity’s next-generation sensors enable condition monitoring and IoT-driven building management, featuring an HVAC airflow demonstration built with readily available hardware and the /IOTCONNECT™ platform. The demo uses a Microchip WFI32-IoT development board integrated with multiple TE Connectivity sensors, including differential pressure, temperature, humidity, and barometric sensors, to monitor airflow and environmental conditions and securely stream data to /IOTCONNECT™ for visualization, analytics, and predictive maintenance use cases.
Waveform Classification AI at the Edge featuring the Microchip PolarFire® SoC
Join Avnet and Microchip for a practical demonstration of edge AI with the PolarFire SoC Discovery Kit and /IOTCONNECT, highlighting secure device onboarding, real-time telemetry, and FPGA-accelerated machine learning at the edge. Attendees will learn how a template-correlation classifier can perform real-time signal classification while leveraging /IOTCONNECT for cloud monitoring, visualization, command and control, and performance benchmarking.
