This blog gives an overview of the security implementation on Cortex-M33 CPU based RA microcontrollers to understand the key concepts to consider, when implementing an application using TrustZone technology.
At Renesas, we put data security first in every new IIOT-enabled microcontroller we design
Secure handling of application cryptographic keys presents a significant challenge. Discover how the latest RA MCUs enable secure factory programming, by leveraging a Renesas-provided, simple and free of charge service.
Take advantage of the extensive Example Projects available from Renesas to help support your RA MCU design.
While building machine learning models on sensor and signal data, many customers hit a point where they're not getting the desired result. Here's a process we go through to find the best path forward.
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.
Reality AI Tools® includes functionality to monitor the status of data collection automatically, tracking consistency, quality, and coverage.
To get your machine learning model to the point where it’s ready for field testing, you’ll want to collect several thousand observations that cover a broad a range of the variation expected.
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.