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Industrial

Household Smoke Detector Development Board

This solution uses a highly integrated RAA239101 low power analog front end (AFE) IC and includes all necessary peripherals and features required for a photoelectric smoke detector system, mainly focused on residential smoke detector designs. It is implemented using two key components, the RL78/G12 low power microcontroller and the RAA239101 photoelectric smoke detector AFE IC.

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Battery Management System

The RAJ240090/100 Evaluation Kit includes an Evaluation Module (EVM), a USB System Management Bus (SMBus), and an interface adapter. It enables users to evaluate their battery management system using the Renesas RAJ240090 and/or RAJ240100GFP Li-ion Battery Fuel Gauge ICs (FGICs).

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240W DC to DC USB-C PD 3.2

RTK-G015-EPRSinkCharger-240W is a USB PD 3.2 EPR evaluation board supporting up to 48V/240W input. It charges 6–12 cell batteries and supports both Sink (charging) and Source (power bank) modes. Key components include R9A02G0151 (TCPM), RAA489400 (TCPC), RAA489300 (Buck), and RAA489118 (charger).

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IoT

HMI Household Appliances

This integrated solution provides an efficient, low-power, and flexible platform for touch-based user interfaces in home appliances such as microwave ovens, water purifiers, induction cooktops, and air fryers.

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Power and Energy

Single Phase Energy Meter

Users can set various AC input and load conditions to measure the error % with Smart DLMS based 1-phase energy meter solution, where communication with meter through DLMS can also be observed.

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Automotive

Low-cost TFT instrument cluster with telematics

High-end automotive microcontrollers supporting basic or low-level 2D drawings are included on this board for the instrument cluster

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Power and Energy

High Voltage Battery Management System

This solution is designed for a 20 – 28cells battery management system with Daisy Chaining, aimed at domestic battery-powered generators.

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IoT

Voice User Demonstration Kit

The VOICE-RA6E1 is an edge voice recognition platform designed for developing and evaluating voice user interface (VUI) applications. It leverages the Renesas RA6E1 MCU (Arm Cortex-M33, 200 MHz) with DSP and floating-point support, making it capable of real-time audio processing, beamforming, and lightweight machine learning. It integrates multi-channel voice capture for improved accuracy in noisy or multi-speaker environments, along with on-chip ADC/DAC and DSP functions for seamless audio input/output handling.

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Artificial Intelligence , Microcontrollers and Microprocessors , Edge AI

RZ/V2N Based Edge AI Development Platform For Robotic Arm

The RZ/V2N from Renesas is a high-performance vision AI microprocessor (MPU) designed for edge applications that demand both advanced AI inference and low power consumption. Powered by Renesas’ proprietary DRP-AI3 accelerator delivering up to 15 TOPS, it is optimized for real-time vision processing in compact, energy-efficient systems. The key board features include: CPU Architecture: Quad Arm® Cortex®-A55 (1.8 GHz) + Arm® Cortex®-M33 (200 MHz). Image Processing: Integrated ISP with dual-channel MIPI® CSI-2® interfaces for dual-camera support. Connectivity: High-speed PCIe® and USB 3.2 for device expansion and system integration. Power Efficiency: Optimized for low power consumption, making it suitable for edge devices.

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