The endpoint describes any Device that is physically at the end of any point in the network. While applying AI at the endpoint can have many benefits, securing it can be difficult. The fact that endpoints are considered the entrance to IoT systems, makes them very attractive targets for hackers. Thus, security principles have to be incorporated into the architectural design process of IoT systems.
Renesas RXv3 Core performance has exceeded 6.0 CoreMarks/MHz of EEMBC’s CoreMark®. I will introduce this wonderful achievement and Renesas CC-RX compiler’s contribution to the higher score.
The RZ/A3UL microprocessor (MPU) reduces the number of required components contributing to lower total cost, including PCB development man-hours and software development costs.
With flexible development software and scalable options based on Arm Cortex-M33, M23 and M4 cores, the RA MCU family is becoming the top choice on which to base your IoT designs in industrial and building automation, metering, healthcare, and home appliances.
The operating voltage of high-end microcontrollers have recently been reduced to a lower voltage. However, the new RX660 will support 5V power systems, which are increasingly popular in the consumer electronics and industrial fields.
Renesas has variety of products that will help in developing an efficient and reliable pure sine wave inverter.
This blog describes how Renesas' automotive BMS application models & software can reduce development time for our customers.
With the widely deployed cellular network in recent years, IoT devices can be easily implemented in any location. At the same time, battery-driven power supply is preferably adopted.
I will introduce the RX family solution that achieves low power consumption by combining the Cellular and FreeRTOS.
Functional safety has been in place for a long time and is wide and varied. Renesas Functional Safety solutions are IEC61508 certified to accelerate time to market and reduce total cost.
In order to collect meaningful data from the environment, sensors are now being used in many different applications. Using Sensor Fusion, real truth can be generated by combining multiple physical sensor data which would lead to reducing the uncertainty related to overall task performance. Through the application of deep learning for sensor fusion, intelligence and reliability among a wired range of industrial and consumer segments can be increased.