Part 4: Profiling the performance of the AI-accelerated EFR32MG24 model
Creating a Smarthome Device That Is Truly Smart
Building an Acoustic Aware Door Lock Using Silicon Labs' AI Accelerated xG24 Dev Kit
Creating a Smarthome Device That Is Truly Smart
Building an Acoustic Aware Door Lock Using Silicon Labs' AI Accelerated xG24 Dev Kit
Part 3: Generating a working smart door lock model for the SiLabs xG24 Dev Kit
Creating a Smarthome Device That Is Truly Smart
Building an Acoustic Aware Door Lock Using Silicon Labs' AI Accelerated xG24 Dev Kit
Part 2: Collecting smart door lock raw acoustic sensor data and labeling it using SensiML Toolkit
Creating a Smarthome Device That Is Truly Smart
Building an Acoustic Aware Door Lock Using Silicon Labs' AI Accelerated xG24 Dev Kit
Part 1: Using Silicon Labs xG24 Dev Kit and SensiML Analytics Toolkit, we’ll transform a connected door lock into an innovative enhanced security smart lock.
SensiML and Infineon Team Up to Add AI for PSoC™ 6 MCUs
Our SensiML Analytics Toolkit can now work together with the Infineon ModusToolbox™
We just announced that SensiML has teamed up with Infineon Technologies AG to deliver a complete AI/ML solution for the Infineon PSoC™ 6 family of microcontrollers (MCUs) and XENSIV™ sensors. This is great news for Infineon customers as they can now use SensiML’s tools to easily create intelligent IoT endpoints using the ultra-low power and
Breeze Environmental Platform
Challenge Climate Change : Line Powered Project
Making Monitoring Environmental Conditions a Breeze Our third-place winner (line-powered category) in the Challenge Climate Change contest was Attila Tőkés, who created an extremely versatile environmental sensor platform he calls “Breeze.” This platform features a carrier board which can connect multiple sensor boards, a communications module, the QuickLogic QuickFeather board, and a solar panel/charging system along
Forest Guardian
Challenge Climate Change : Battery Powered Project
The Forest Guardian won the first place in the battery-operated category of our “Combat Climate Change” contest. We at SensiML thought it was a very creative way to help combat climate change by detecting and reporting on instances of illegal logging. Specifically, the Forest Guardian application works by using a solar-charged battery to power a
HVAC Performance Optimization
Challenge Climate Change : Line Powered Project
For our Challenge Climate Change contest (done in collaboration with QuickLogic and hackster.io) we had two primary categories: battery powered applications and line powered applications. Previously we discussed the battery powered winners, now it’s time to take a look at the clever line powered application winners. Our first place finisher in the line powered category was Ralph
Protecting the Peatlands
Challenge Climate Change : Battery Powered Project
The Protecting the Peatlands Project won the second place in the battery-operated category of our “Combat Climate Change Challenge” contest. Peatlands are a special type of wetlands which are particularly valuable for preserving global biodiversity, sequestering carbon, and filtering water. Unfortunately, a good percentage of the earth’s peatlands have already been eliminated or significantly damaged,
Illegal Logging Detector
Challenge Climate Change : Battery Powered Project
For Alejandro, helping to solve this problem really hit home as it’s a big issue in his native country of Mexico. In his words, “The environmental effects of illegal logging include deforestation, the loss of biodiversity and the emission of greenhouse gases. Illegal logging has contributed to conflicts with indigenous and local populations, violence, human rights
Bird Buddy
A Climate Change Challenge Winning Project
We’ve discussed many of the other top applications submitted for our Challenge Climate Change contest (a collaboration between us, QuickLogic, and hackster.io). Next we’d like to discuss one called “BirdBuddy” – a really interesting project and a 2nd place finisher in the contest. Due to climate change, birds are migrating earlier each year. Different species in
Smart Manufacturing with SensiML
Applying AI at the IoT Edge to Injection Molding Processes
Opportunities to improve manufacturing processes by adding machine learning sensors at the IoT edge are rapidly emerging. Thanks to a combination of Powerful microcontrollers and multi-core SoCs like the EOS S3 on QuickLogic’s QuickAI HDK High-resolution, low-cost MEMS sensors and microphones Powerful AutoML-based AI tools like SensiML Analytics Toolkit it is possible to bring sophisticated
