Blog Posts

Software is becoming the new sensor. This shift in thinking opens the door to incorporating more complex, AI-based algorithms, rather than just simple condition thresholds.

As sensor and MCU costs decreased, an ever-increasing number of organizations have attempted to exploit this by adding sensor-driven embedded AI to their products.

The more sophisticated machine learning tools that are optimized for signal problems and embedded deployment can cut months, or even years, from an R&D cycle.

Relying only on high-level descriptive statistics rather than time and frequency domains will miss anomalies, fail to detect signatures and sacrifice value that an implementation could potentially deliver.

This post offers tips on collecting data from high-sample-rate sensors for use with machine learning.

Are you facing difficulties meeting functional safety requirements in your automotive system development? If so, I would like to introduce you to our functional safety system solution for xEV inverter applications that simplifies implementation and shortens the development time.

This blog describes how Renesas' automotive BMS application models & software can reduce development time for our customers.

Software for central gateway to realize connected vehicles

From 21-23 June, Renesas was one of the largest semiconductor manufacturers at Embedded World!

Introduction of Uptane, a software update security framework for securing automotive Over-the-Air (OTA) software updates, and Renesas automotive devices.