ESP32-S31NR16V Integrated Circuit Chip High-Performance Dual-Core 32-Bit RISC-V SoC

ESP32-S31NR16V is a high-performance dual-core 32-bit RISC-V SoC that integrates multi-protocol connectivity and advanced HMI capabilities, with a clock speed of up to 320 MHz. Designed for comprehensive multi-protocol connectivity, it is specifically tailored for advanced Internet of Things (IoT) applications requiring comprehensive connectivity and rich human-machine interfaces.

ESP32-S31NR16V provides 60 GPIO pins, demonstrating exceptional flexibility in complex designs that simultaneously support multiple wireless protocols, various display interfaces and a wide range of peripherals.

• Dual-core 32-bit RISC-V processor with a maximum clock speed of 320 MHz, supporting MMU and featuring integrated SIMD acceleration units for parallel processing
• Built-in 512 KB SRAM, supporting 250 MHz 8-bit DDR PSRAM and Octal SPI, enabling flexible external memory expansion
• Peripheral interfaces include: 61 GPIOs, DVP camera interface (8-16-bit), RGB LCD interface (8-24-bit), 14 touch channels, USB OTG, SPI, I2S, UART, I2C, LED PWM and TWAI (CAN 2.0)
• Security features include: secure boot, Flash/PSRAM encryption, ECDSA digital signatures, RAM-based PUF, and hardware encryption acceleration
• Employs robust hardware protection mechanisms to provide comprehensive security capabilities that meet stringent industry requirements
• Includes built-in secure boot, Flash and PSRAM encryption, a hardware random number generator, and hardware acceleration for encryption algorithms such as AES-128/256, RSA, ECDSA, and ECC
• The ECDSA-based digital signature peripheral prevents software access to private keys and provides protection against side-channel attacks and power glitch interference
• The chip also incorporates a Trusted Execution Environment (TEE) and Access Policy Management (APM), enabling software isolation and supporting secure multi-application deployment

• ESP32-S31NR16V is particularly well-suited for edge AI and machine learning workloads, including neural network inference, advanced signal processing, computer vision and intelligent audio applications, whilst maintaining the high efficiency characteristics of an embedded platform.

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