With a focus on practicality and efficiency, Data Studio is intended to empower engineers and data scientists by offering an integrated solution that addresses the most time-consuming tasks in AI engineering projects - creating high-quality datasets for evaluating and developing ML models.
According to Cognilytica, the AI/ML consulting firm, approximately 80% of the total time for machine learning (ML) projects is allocated to data preparation. These tasks include data identification, aggregation, cleansing, labelling, and augmentation – all of which are supported in SensiML's collaborative development environment.
SensiML Data Studio looks to significantly improve productivity and simplify dataset management for anyone working on sensor data ML projects. With real-time connectivity, intuitive visualization tools, sensor data video synchronisation, and robust support for large-scale collaborative projects, it provides a seamless experience for developers on edge devices, gateways, PCs, and cloud platforms.
The primary features are highlighted below:
Data Capture and Import - Captures live sensor data, analyses it instantly, and labels any data for seamless insights.
Collaboratively Label Sensor Data - Employs flexible labelling methodologies for sensor data, including manual, AI-assisted, and custom – and sync video for complex labelling. Stores and analyses data locally on a computer or remotely.
Data Analysis and Model Evaluation - Visually compares ML models to filter, transform, and fuse sensor data – all with built-in tools and your own Python expertise.
Label and Data Versioning – Keeps track of labels and model results with versioned labels and can be easily exported to an open format.
"SensiML Data Studio makes sensor data management and analysis more accessible and efficient, empowering developers to build better, more impactful applications using sensor data across a wide range of industries," said Chris Knorowski, CTO of SensiML.
