ARM microcontroller

3 Articles

Recognising Bird Sounds With A Microcontroller

July 6, 2021 by 4 Comments

Machine learning is an incredible tool for conservation research, especially for scenarios like long term observation, and sifting through massive amounts of data. While the average Hackaday reader might not be able to take part in data gathering in an isolated wilderness somewhere, we are all surrounded by bird life. Using an Arduino Nano 33 BLE Sense and an online machine learning tool, a team made up of [Errol Joshua], [Ajith KJ], [Mahesh Nayak], and [Supriya Nickam] demonstrate how to set up an automated bird call classifier.

The Arduino Nano 33 BLE Sense  is a fully featured little dev board that features the very capable NRF52840 microcontroller with Bluetooth Low Energy, and a variety of onboard sensors, including a microphone. Training a machine learning model might seem daunting to many people, but online services like Edge Impulse makes the process very beginner-friendly. Once you start training your own models for specific applications, you quickly learn that building and maintaining a high quality dataset is often the most time-consuming part of machine learning. Fortunately for this use case, a massive online library of bird calls from all over the world is available on Xeno-Canto. This can be augmented with background noise from the area where the device will be deployed to reduce false-positives. Edge Impulse will train the model using the provided dataset, and generate a library that can be used on the Arduino with one of the provided sample sketches to log and send the collected data to a server. Then comes the never ending process of iteratively testing and improving the recognition model. Edge Impulse is also compatible with more powerful devices such as the Raspberry Pi and Jetson Nano if you want more intensive machine learning models.

We’ve also seen the exact same setup get used for smart baby monitor. If you want to learn more, be sure to watch at [Shawn Hymel]’s talk from the 2020 Remoticon about machine learning on microcontrollers. Continue reading “Recognising Bird Sounds With A Microcontroller” →

A New Kid On The Mini ARM Block

October 11, 2018 by 30 Comments

The breadboard microcontroller experimenter has a host of platforms to work with that can be had in the familiar DIP format. Old-school people can still find classic 8-bit platforms, the Ardunisti have their ATMegas, and PIC lovers have a pile of chips to choose from. But ARM experimenters? Out of luck, because as we have previously reported, popular past devices such as the LPC810 in a DIP8 package are now out of production.

News comes from China though of a tiny ARM Cortex M0 for pennies that may not be in a DIP8, but is in almost the next best thing. The Synwit SWM050 can be had in a TSOP8, which though it’s not quite as friendly as its larger SOIC8 cousin, is still easily solderable onto a DIP8 adaptor for breadboard use. Spec-wise it’s 5 V tolerant, has an 8 kB FLASH and 1 kB of RAM, 6 GPIOs, and can clock away at a not incosequential 36 MHz.

We have [Sjaak] to thank for the discovery of this device, and for doing a lot of work including getting some die shots taken to dig up and make sense of the Chinese documentation, and to provide some dev tools should anyone want to play with it.  There’s even a small breakout board for the experimenter unwilling to design their own.

Earlier this year we marked the passing of the DIP8 version of the LPC810 microcontroller, and for those mourning it we made an important point. It’s now normal to use one of the vast array of single board computers instead of a bare microcontroller, you might wish to ask yourself why you would do so.

Thanks [Ziew] for the tip.

New Part Day: ST’s 32-Bit 3D Printer Controller

July 19, 2016 by 57 Comments

There are a few 32-bit ARM-based 3D printer controller boards out there such as the Smoothieboard, the Azteeg X5 mini, [Traumflug]’s Gen5 electronics, whatever board is in the Monoprice MP Mini Select, and several others I will be criticized for not mentioning. All of these ARM boards provide smoother acceleration, better control, and ultimately better prints from whatever 3D printer they’re controlling. Now, out of the blue, there’s a new board. It’s an evaluation board from ST — much like those famous Discovery boards — that sells itself as a plug and play solution for 3D printers.

The heart of this board is an STM32F401 — not the king of the STM32 line or the fastest ARM microcontroller, but anything faster or more capable will add considerably more to the BOM for this board. This controller board features six of ST’s L6474 motor drivers with enough current for some beefy NEMA 23 stepper motors , a multi-zone heated bed, and connections for a WiFi module and external LCD and keypad. You can buy this board right now for $118. This board isn’t a game changer, but it is evidence the game has been changed.

As with all 3D printer controller boards, there are a few aspects that will leave users wanting more. This is a board meant for 12V heaters (except for the bed, which has a 24V, 20A output), and the stepper drivers can only go up to 16 microsteps. That said, there’s not much else to complain about. This offering comes with a 32-bit firmware called Marlin4ST. From a quick perusal, it looks like the familiar configuration.h is still there, and still does what it’s supposed to do.

This ST Discovery board is extremely capable, available now, and relatively cheap, but that’s not really the big story here. What this board represents is a reference design and working firmware for a 32-bit ARM-based printer controller. That’s the future, and with this board the future might come a little sooner.

Thanks [jagerboots] for sending this one in.