Neural Networks for Embedded Systems: How to Deploy AI Without the Cloud
MathWorks has launched a free webinar on building AI-based virtual sensors. It walks through the full cycle: training in MATLAB, formal verification of neural networks, compression to fit memory limits, and generating C code without libraries. The approach is relevant for IoT and edge computing on microcontrollers.
AI-processed from IEEE Spectrum AI; edited by Hamidun News
MathWorks has demonstrated a full development cycle for neural networks in embedded systems, which compute the values they need directly on the processor, with no cloud and no latency.
What is a neural-network virtual sensor?
It is a neural network that computes a target quantity from the data of other sensors. Examples include an air-quality sensor derived from pressure, humidity and CO₂, or an equipment failure prediction system that analyzes vibration and temperature.
Where are embedded AI sensors used?
In industry: in heating pipelines, hydraulic systems, and equipment monitoring systems for failure prediction.
Key Questions Answered
What is a neural-network virtual sensor?
It is a neural network that computes a target quantity from the data of other sensors. Examples include an air-quality sensor derived from pressure, humidity and CO₂, or an equipment failure prediction system that analyzes vibration and temperature.
Where are embedded AI sensors used?
In industry: in heating pipelines, hydraulic systems, and equipment monitoring systems for failure prediction.
Test Frontier LLMs & Autonomous Agents in One Workspace
Run Claude Opus 5.5, GPT-6, Gemini 3.1, and DeepSeek side-by-side in Nomad AI (nomadnet.ai) — unified model routing, deep research, and multimodal workflows under one subscription.
The AI world, distilled — once a week
Seven stories that actually mattered, hand-picked. No noise, no reposts, no press releases.
Done! Check your inbox for a confirmation.