data analysis

Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains. Data mining is a particular data analysis…

Read More

SensiML’s New Open Source Initiative:

AI Transparency and Flexibility Supporting IoT Sensor Products for the Real-World

SensiML Open Source Initiative Logo

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.

Read More

SensiML & Silicon Labs Partner on Cutting-Edge AI for IoT:

AutoML Smart Sensing Tools for the EFR32 / EFM32 Family of Low Energy MCUs

Silicon Labs Thunderboard Sense 2

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).

Read More

SensiML Adds Arduino Nano 33 BLE Sense Support with PlatformIO

nano33 BLE Sense board

This month SensiML is pleased to announce SensiML Analytics Toolkit now provides native support for STMicroelectronics’ SensorTile.Box Development Kit for wireless IoT and wearable sensor applications. SensiML’s support for SensorTile.Box includes our most sophisticated MQTT-based device data collection firmware yet made available in open source for customers to extend and modify as necessary to suit their particular application needs.

Read More

SensiML Adds Support for STMicroelectronics’ SensorTile.Box

This month SensiML is pleased to announce SensiML Analytics Toolkit now provides native support for STMicroelectronics’ SensorTile.Box Development Kit for wireless IoT and wearable sensor applications. SensiML’s support for SensorTile.Box includes our most sophisticated MQTT-based device data collection firmware yet made available in open source for customers to extend and modify as necessary to suit their particular application needs.

Read More

SensiML Adds Support for QuickLogic’s QuickFeather IoT Dev Kit

QuickLogic QuickFeather - IoT EVB with low-power MCU + embedded FPGA

This week SensiML added support for the Quicklogic QuickFeather Development Kit. Noteworthy for its inclusion of Arm Cortex-M4 MCU, FPGA, and an array of sensors in a fully open-source HDK using the popular Adafruit Feather form factor, the QuickFeather makes a great IoT development platform for developers of consumer, wearable, and industrial products.

Read More

SensiML’s Response to the Coronavirus Pandemic

SensiML's COVID-19 Response

SensiML announces two COVID-19 initiatives:
1) SensiML Toolkit Starter Edition is now available for a limited time at $99 for a 90-day license.
2) SensiML to open-source a COVID-19 AI dataset for rapid virus screening from cough sounds. Learn how you can contribute to this project yourself.

Read More

SensiML Broadens Ecosystem for AI-Based IoT Endpoints – Now Supports NXP i.MX RT Crossover MCUs

NXP i.MX RT1050 Eval Kit

Today we announced that our SensiML Analytics Toolkit supports NXP’s i.MXT RT portfolio of crossover microcontrollers and their associated i.MX RT1050 Evaluation Kit. This announcement is significant as it gives users of those devices a complete AI-based sensor algorithm development solution for IoT endpoints. With this, NXP customers using the i.MX RT crossover MCUs can…

Read More

The Case for AI at the Edge

Artificial Intelligence (AI) is becoming increasingly commonplace as organizations seek to bring effective decision making and operational efficiencies to business in ways that transform how humans and machines work together. As this transformation takes shape, the advantages of edge-based AI implementations over centralized or cloud-based models is changing how AI tools are being deployed and…

Read More
1 2