HACKSTER.IO PRESENTS

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Throughout the next year, we'll host monthly activities for you to take your skills to the edge with the Edge Impulse platform. Train a board, create a dataset or perform a task - show off your skills for a chance to win prizes!


Silicon Labs' Smart Sensor Systems

When deploying smart devices in certain environments your available space and power requirements may be limited. The Silicon Labs xG24 Developer Kit is a sensor-rich platform for prototyping AIoT devices, able to run TinyML models on just a coin-cell battery. With a dedicated AI accelerator, 6 onboard sensors, BLE, and a compact board about the size of two postage stamps, the xG24 can fit in tight places and capture a wealth of environmental information.

January Activity

To better understand the Silicon Labs xG24 Developer Kit and it’s capabilities, we're highlighting two example resources that make great use of Edge Impulse running on the board. Review the resources below, then take a short quiz about what you learned to be entered for a chance at winning an xG24 in  January's prize bundle!

Step 1

Join the Edge Impulse community at hackster.io/EdgeImpulse.

Step 2

Step 3

Review the two resources below & complete the quiz.

Resource #1

Resource #2

Project: Occupancy Sensing - SiLabs EFR32MG24

Tutorial: Object detection - SiLabs xG24 Dev Kit

Quiz closes January 29, 2023 at 11:59PM PT.

January Prize

Edge Impulse will be giving away three prize bundles to eligible activity submissions. 

Winners will be announced February 6, 2023.

Edge Impulse Swag

Additional Resources

Use the resources below to learn more about the Silicon Labs xG24 Dev Kit and how to get started collecting data, building and training tiny machine learning models, and deploying these models to the xG24 Dev Kit directly from the Edge Impulse Studio.

Documentation

Announcing Official Support for the Silicon Labs xG24 Dev Kit

Getting Started with SiLabs xG24 Dev Kit

Setting up your EFR32xG24 Kit

xG24 Dev Kit User's Guide

MG24 Demo

Learn more about Silicon Labs' cost-effective, feature-rich, prototype and development

platform based on the EFR32™ Wireless Gecko System-on-Chip in the official xG24 Dev Kit User's Guide.

Other Project Tutorials

Explore more projects making use of Silicon Labs hardware including the xG24’s very-capable predecessor, the Thunderboard Sense 2.

Take an existing Edge Impulse model built for the Thunderboard Sense 2, and prepare it for use on the SiLabs xG24 board.

Use Edge Impulse to train a model for detecting gestures with the onboard accelerometer.

Edge Impulse based TinyML model using Audio data acquisition to predict the vehicle failures like faulty drive shaft, Brake pad noises.

Find more projects featuring Edge Impulse on Hackster.io.

Sign Up for Monthly Activity Reminders

Get Started with Edge Impulse

You must be registered on Edge Impulse to be eligible to win Take It to the Edge Activities. 

Past Featured Technology

Click on the links below for details, learning resources and winner announcements from our past activities and featured technologies. 

Keyword spotting, otherwise known as wake word detection, is a form of voice recognition that allows computers to listen for and respond to specific words. In keyword spotting, a device listens for a keyword or phrase and triggers an action based on what is spoken. Review the resources below to gain a better understanding of this popular technology and learn how to train a device to recognize your own keyword or phrase. 

The Raspberry Pi Pico is a low-cost development board that use a microcontroller (Cortex-M) processor. The Pico (and brand-new Pico W) are low-power, small devices that have more modest capabilities than a regular Raspberry Pi, but excel when it comes to size, battery life, and ease of prototyping. With 264kB on-chip SRAM and 2MB on-board flash, the Pico can even run lightweight tinyML models for basic sensor-driven AI workloads.

TinyML on the Arduino Nano 33 BLE Sense

The Arduino Nano 33 BLE Sense is one of the most feature-packed Arduino boards, with a built-in temperature sensor, accelerometer, gyroscope, and microphone (and more). This makes it a great platform for building monitoring and sensing projects and devices. You'll be able to sample raw data, build models, and deploy trained machine learning models directly from the Edge Impulse Studio.

The Extremely Extensible ESP32

The ESP32 is a small, low cost microcontroller with bluetooth and WiFi connectivity, making it ideal for IoT products and applications. It's dual-core processor is strong enough to run TinyML models, opening up endless possibilities for building smart sensors, wearables / health devices, basic vision applications, and more.

The Espressif ESP-EYE development board based on Espressif's ESP32 chip is fully supported by Edge Impulse. The ESP-EYE is equipped with a 2-Megapixel camera and a microphone making it perfect for image recognition and audio processing applications.

Diving Into Data

In most cases, data is the most important factor in creating a successful TinyML project. Sure, hardware selection, power, and connectivity matter too, but without good training data, your model likely won’t be accurate enough to perform it’s intended function out in the world!

Super Sony Spresense

The team at Sony has created a small but powerful microcontroller board that is ready to run Edge Impulse machine learning models. With 6 Arm Cortex-M4 cores, 1.5 mb of RAM, GPS, camera input, onboard audio, and plenty of expansion options for sensors, WiFi, cellular and more, the Spresense can be used in a wide variety of projects.


Classification and Cloud Connectivity

Many times, we focus on performing machine learning locally on-device, with no need for internet connectivity. This reduces latency, simplifies projects, and can sometimes reduce costs. However, some projects do require connectivity to the cloud in order to set a status, update a dashboard, log an activity or event, or allow a user to interact with a device.   

Looking for more inspiration?

Find tutorials featuring Edge Impulse on Hackster.io.

FAQ

Who is eligible to participate?

How do I enter the giveaway?

How do I know if I won?

  1. Be a Hackster community member & join the Edge Impulse platform hub.
  2. Sign up for an Edge Impulse account.
  3. Complete the activity and fill out the form above.

Everyone is eligible to complete activities and learn about Edge Impulse. However, you are only eligible to win or be awarded prizes if:

  • You are at least 13 years of age
  • You are not a resident of Belarus, Cuba, Iran, North Korea, Sudan, Syria, Russia or Ukraine.
  • You are not involved in the execution of "Take it to the Edge."
  • You are not an immediate family member or household member of a Hackster, Avnet or Edge Impulse employee. 

Winners will be announced on this page within 5 business days after a quiz is closed. Winners will also be contacted via the email used when submitting their quiz. 

I won a prize! When will I receive it?

Do I need to pay taxes/customs fees on my prize shipment?

The prize fulfillment process will take up to 8 weeks after winners have been announced. You will receive an email when your prize is shipped. If you need to make any changes to your address during that time, please contact us at events@hackster.io.

No, Hackster will ship all the prizes and will cover the taxes/customs fees associated with shipment.

Other questions?

If you have any questions regarding this giveaway, please contact us at events@hackster.io.

Find upcoming events, workshops, and more! 

hackster.io/events

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