From embedded sensors to advanced intelligence: Driving Industry 4.0 innovation with TinyML

Reading Time: 5 minutes Wevolver’s previous article about the Arduino Pro ecosystem outlined how embedded sensors play a key role in transforming machines and automation devices to Cyber Physical Production Systems (CPPS). Using CPPS systems, manufacturers and automation solution providers capture data from the shop floor and use it for optimizations in areas like production schedules, process control, and…… From embedded sensors to advanced intelligence: Driving Industry 4.0 innovation with TinyML weiterlesen

Instead of sensing the presence of metal, this tinyML device detects rock (music)

Reading Time: 2 minutes Arduino Team — January 29th, 2022 After learning about the basics of embedded ML, industrial designer and educator Phil Caridi had the idea to build a metal detector, but rather than using a coil of wire to sense eddy currents, his device would use a microphone to determine if metal music is playing nearby.  Caridi started…… Instead of sensing the presence of metal, this tinyML device detects rock (music) weiterlesen

This Arduino device can detect which language is being spoken using tinyML

Reading Time: 2 minutes Arduino Team — December 8th, 2021 Although smartphone users have had the ability to quickly translate spoken words into nearly any modern language for years now, this feat has been quite tough to accomplish on small, memory-constrained microcontrollers. In response to this challenge, Hackster.io user Enzo decided to create a proof-of-concept project that demonstrated how an embedded device…… This Arduino device can detect which language is being spoken using tinyML weiterlesen

This pocket-sized uses tinyML to analyze a COVID-19 patient’s health conditions

Reading Time: 2 minutes This pocket-sized uses tinyML to analyze a COVID-19 patient’s health conditions Arduino Team — June 21st, 2021 In light of the ongoing COVID-19 pandemic, being able to quickly determine a person’s current health status is very important. This is why Manivannan S wanted to build his very own COVID Patient Health Assessment Device that could take several data points…… This pocket-sized uses tinyML to analyze a COVID-19 patient’s health conditions weiterlesen

Edge Impulse and TinyML on Raspberry Pi

Reading Time: 8 minutes Raspberry Pi is probably the most affordable way to get started with embedded machine learning. The inferencing performance we see with Raspberry Pi 4 is comparable to or better than some of the new accelerator hardware, but your overall hardware cost is just that much lower. Raspberry Pi 4 Model B However, training custom models on…… Edge Impulse and TinyML on Raspberry Pi weiterlesen

Edge Impulse makes TinyML available to millions of Arduino developers

Reading Time: 4 minutes This post is written by Jan Jongboom and Dominic Pajak. Running machine learning (ML) on microcontrollers is one of the most exciting developments of the past years, allowing small battery-powered devices to detect complex motions, recognize sounds, or find anomalies in sensor data. To make building and deploying these models accessible to every embedded developer…… Edge Impulse makes TinyML available to millions of Arduino developers weiterlesen