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
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
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
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
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
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
Introducing New, More Flexible Plans
Highlights: New Proto Plan offers fixed fee for a single application Proto reduces term anxiety with a full year license to use All paid plans to provide flexible add-on features Customers can now tailor their plans to suit their exact needs Starting August 1st, SensiML is updating its service plans to bring more value and
Congratulations to Our Climate Change Challenge Winners!
About six months ago we, the folks at QuickLogic, and the Avnet Hackster.io online community announced our Challenge Climate Change contest. The idea was to encourage creative smart technology projects that improve awareness, change behavior, or optimize processes to impact climate change for the better. Towards that end, we opened up the contest to developers
SensiML & Microchip Technology Solution
SensiML has collaborated with Microchip Technology to deliver ultra-compact machine learning at the IoT edge combining SensiML Analytics Toolkit with the SAM-IoT WG evaluation kit, SAMD21 MCU, and MPLAB X IDE tool suite.
SensiML’s New Open Source Initiative: AI Transparency and Flexibility Supporting IoT Sensor Products for the Real-World
Today SensiML took a leadership position in AI/ML tools for the IoT edge by announcing our new Open Source Initiative. SensiML Open Source Embedded SDK (coming later this summer) – The full library of SensiML segmenters, transforms, features, and classifiers as implemented by the AutoML and Python-based SensiML Analytics Toolkit Notebook will become available in open source format.
SensiML Tutorial Series
Webinar tutorial series discussing a variety of topics related to embedded IoT development, TinyML and AI at the edge, sensor data processing, and the application of SensiML Analytics Toolkit.
SensiML & Silicon Labs Partner on Cutting-Edge AI for IoT: AutoML Smart Sensing Tools for the EFR32 / EFM32 Family of Low Energy MCUs
SensiML has collaborated with Silicon Labs to enable AutoML-based rapid development of optimized machine learning sensor models for Silicon Labs’ energy-friendly EFR32 and EFM32 microcontrollers (MCUs).