Automated Software Lets Users Add AI to Their IoT Projects

SensiML’s web-based tool suite helps users implement AI into endpoint IoT applications.

SensiML Analytics Studio. (Image courtesy of SensiML.)

SensiML Analytics Studio. (Image courtesy of SensiML.)

SensiML has revealed that its Analytics Studio, part of the company’s flagship Analytics Toolkit Suite, has a new ability in its arsenal: a web-based Automated Machine Learning (AutoML) tool that helps users implement AI into their endpoint IoT applications.

SensiML Analytics Studio is a stand-alone application designed for users without data science expertise. Since it is a browser-based tool, there is no need to download or install software locally. The software features UI-driven AutoML capability with improved controls, enabling users to make individual configurations of the software and obtain quick results, tune and iterate. New visualization and reporting features also help provide clear feedback.

For more advanced users, the company also has a separate version of the tool with a Python language interface. This version, called SensiML Analytics Studio Notebook, gives programmatic access to SensiML Cloud and all of its associated functionality to build ML sensor algorithms for consumer, industrial, automotive and IoT applications.

“The SensiML Analytics Toolkit was designed to simplify developing AI for IoT applications—making it possible for a single user or small development team to implement a complete AI-based solution for IoT endpoints,” stated Chris Rogers, SensiML CEO. “The new browser-based Analytics Studio improves the user experience through a sophisticated yet simple-to-use interface, so building intelligent sensor algorithms is easier than ever.”

Both versions of Analytics Studio continue to integrate functionality with the broader SensiML Analytics Toolkit Suite, including the ability for raw signal capture, data insight labeling, algorithm generation, firmware code generation and test/validation, and support.

For a free trial of SensiML’s Analytics Studio, click here.