Electromaker of the Month - June Winners Announced!

Another month has passed, so let's see what the Electromaker Community has been building and meet the Electromakers of the Month!

Throughout June, we've been inundated with fantastic Electromaker Community Projects. They've covered everything from AI to DIY tools and tutorials on common parts and protocols.

Our panel of judges found it tough to choose winners, but here are the three Electromaker of the Month winners for June!

1. Build A Litter Heatmap With A Blues Notecard & Edge Impulse 

Electromaker Community Member Nathanial F's prototype roadside litter detection system maps trash in cities using the Blues Wireless hardware platform and Edge Impulse - a machine learning platform for microcontrollers and other edge devices.

Our judges loved the practicality of this project - a tinyML proof of concept with a real potential to do good in the world. They were also impressed with the multiple sources of training data for the Edge impulse model training. 

Alongside the fantastic outcome, the documentation for this project is terrific too. So congratulations, Nathanial, you'll be winning the top Electromaker of the Month prize - a whole boatload of Nordic Semiconductor prototyping gear!

You'll also be getting a bunch of Electromaker Swag and a $50 Amazon gift voucher - don't forget to tag us in the picture of you in the shiny EM t-shirt!

2. Tic-tac-toe Game With Tinyml-based Digit Recognition

Tic Tac Toe is a classic game and a great beginner programming challenge. Electromaker Community member Rucksikaa Raajkumar took this concept and made it much smarter with the help of tinyML and an M5 Stack Core development kit.

Our judges were impressed with the integration of the M5 Core touch screen as an input device for a Python-based GUI, and the inventive use of the MNIST dataset to train a model using the Neuton platform before deploying it onto the ESP32.

3. Smart Shipment With Tinyml 

In third place this month is Timothy Malche's Smart Shipment project. It takes the concept of asset tracking and adds AI-assisted motion tracking to determine if a package in transit gets dropped, stored in the wrong orientation, or impacted in a way that may damage it.

Our judges loved the proof-of-concept here, taking an established idea and building on it in a way that could be developed into a commercial product. It's a great use of tinyML and a deserved third place!

Second and Third place wins a big bag of Nordic and Electromaker Swag!

Will You Be the Next Electromaker of the Month?

Every month we celebrate the inventive, curious, and resourceful nature of our Maker community. Any project published on the Electromaker website is eligible to win, and there's a whole host of great prizes!

To get started, register for a free Electromaker account, and upload your project!