Acoustic Event Detection
Custom Smart IoT ML Sensor Algorithms
with SensiML Knowledge Packs
Learn More See Examples Get StartedAccurate AI Sensor Algorithms For the Smallest IoT Devices
Activity Recognition
Anomaly Detection
Gesture Recognition
Keyword Spotting
Vibration Classification
The SensiML Endpoint AI Workflow
SensiML Analytics Toolkit suite automates each step of the process for creating optimized AI IoT sensor recognition code. The overall workflow uses a growing library of advanced ML and AI algorithms to generate code that can learn from new data either the development phase or once deployed.
How to Ensure Success Implementing TinyML Solutions
Join SensiML and Silicon Labs on August 22nd, at 10am or 11pm US CDT to hear CTO Chris Knorowski present practical guidance and invaluable insights into the challenges and common pitfalls often encountered when developing sensor-based machine learning (ML) inference models.
Register To Attend
Rapid prototyping with SensiML and M5StickC-PLUS
SensiML now supports the M5Stack Stick series devices based on the Espressif ESP32 MCU with built in WiFi, a color LCD display, IMU, microphone, and a range of modular extensions. SensiML's open-source reference firmware allows users to connect to SensiML Data Capture Lab and start generating train/test datasets within minutes. Learn how to get started with this powerful, low-cost prototyping device.
See Documentation
Top 5 New SensiML Dataset Management Features
SensiML Data Capture Lab (DCL) was already a leading tool for managing supervised ML datasets for edge IoT sensor applications. Now DCL boasts a variety of new features making it easier than ever before for users to create and manage their AI/ML projects and visualize their datasets in insightful new ways. This blog explores the top 5 new dataset management and visualization features added to DCL.
See Blog Article
