
DFRobot FireBeetle 2 ESP32-P4 AI Vision Board
ESP32-P4 dual-core RISC-V AI vision board at 360MHz with hardware H.264/JPEG encoding, MIPI CSI/DSI interfaces, ESP32-C6 WiFi 6 coprocessor, 32MB PSRAM, 16MB flash, PDM microphone, TF card slot, and 24 GPIO pins in a compact 25.4x60mm form factor.
$11.90
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Specifications
Components
Espressif ESP32-P4 with dual-core RISC-V at 360MHz, FPU, AI extensions, hardware H.264/JPEG encoding at 1080p, ISP, PPA, 768KB L2 cache.
Companion ESP32-C6 providing WiFi 6 (802.11ax) and Bluetooth 5 LE connectivity, offloading wireless from the P4 processor.
Built-in PDM microphone for audio capture, voice recognition, and speech processing.
Overview
The DFRobot FireBeetle 2 ESP32-P4 AI Vision Board (SKU: DFR1172) is the standalone board version of DFRobot's ESP32-P4 platform, priced at $11.90 without the IO expansion board included in the DFR1237 kit. It packs Espressif's most capable MCU -- the ESP32-P4 with dual-core RISC-V at 360MHz, single-precision FPU, and AI extensions -- into the familiar FireBeetle 2 form factor at 25.4 x 60mm.
The board's standout feature is its integrated media pipeline: hardware-accelerated H.264 and JPEG encoding capable of 1080p output, a built-in Image Signal Processor (ISP), and PPA graphics accelerator. MIPI CSI (2-lane) and MIPI DSI (2-lane) connectors use Raspberry Pi-compatible interfaces, allowing direct connection of standard RPi cameras and displays. An onboard PDM microphone enables voice and audio applications.
Wireless connectivity is handled by a companion ESP32-C6 coprocessor providing WiFi 6 (802.11ax at 2.4GHz) and Bluetooth 5 LE, leaving the P4's dual cores fully available for media processing and AI inference. The board exposes 24 digital I/O pins with rich peripheral multiplexing: 5 UARTs, 2 I2C, 3 I2S, 2 SPI, 7-channel 12-bit ADC, 4 touch channels, 8 PWM channels, and IR transmit/receive. A TF card slot provides expandable storage for video recording and data logging.
Use Cases
6Computer Vision
Image recognition, object detection, and ML inference using embedded cameras and AI-capable processors.
Video Streaming
Capturing and streaming video over WiFi or network, including IP camera feeds and real-time monitoring.
Voice Assistant
Offline and cloud-connected voice assistant, wake-word detection, and speech recognition projects.
Security Camera
WiFi-connected camera for surveillance, motion detection, and remote video monitoring.
IoT Dashboard
Display real-time IoT sensor data on an embedded screen for local monitoring.
Media Player
Building custom media playback devices for audio, video, or digital signage using DVI/HDMI output.
Resources
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