FireBeetle 2 Board ESP32-S3 (N16R8) AIoT Microcontroller with Camera (Wi-Fi & Bluetooth on Board)

FireBeetle 2 ESP32-S3 is a high-performance main controller built around the ESP32-S3-WROOM-1-N16R8 module. ESP32-S3-WROOM-1-N16R8 comes with 16MB Flash and 8MB PSRAM for storing more data. The acceleration for neural network computing and signal processing workloads provided by the ESP32-S3 chip makes the module an ideal choice for a wide variety of applications, such as speech recognition, image recognition, and so on.FireBeetle 2 ESP32-S3 offers an onboard camera interface for easy connection with a camera. Also, an independent camera power supply circuit is designed, which helps reduce interference from other signals to the camera. The board comes with an OV2640 camera that offers 2 megapixels, 68° FOV, and up to 1600*1200 resolution. Besides, its onboard, easy-to-connect GDI greatly saves the trouble of wiring for using with a screen. Meanwhile, the controller integrates a power management function, which allows users to charge a Li-ion battery and turn the hardware on/off.In addition, FireBeetle 2 ESP32-S3 supports WiFi and Bluetooth 5 (LE) dual-mode communication, which reduces the difficulty of networking. Meanwhile, both Bluetooth Mesh protocol and Espressif WiFi Mesh are supported for more stable communication and a larger coverage area. With the support of Matter protocol, the microcontroller can be used to develop industrial standard smart home devices for a wider range of IoT and AIoT (Artificial Intelligence of Things)scenarios.FireBeetle 2 ESP32-S3 can be programmed by Arduino IDE, ESP-IDF, and MicroPython. Both C and Python are supported.Image recognitionVideo picture transmissionComparison Table FireBeetle 2 Board ESP32-S3 (N16R8) AIoT Microcontroller FireBeetle 2 Board ESP32-S3-U (N16R8) AIoT Microcontroller WiFi Soldered on the board Routed through a cable Bluetooth Soldered on the board Routed through a cable Features Cohesive design, more visually appealing Better signal qualityFeaturesESP32-S3 module with AI Acceleration16MB Flash & 8MB PSRAM, more storage spaceOnboard camera interface & independent camera power supply, easy to connect and strong anti-interferencePower management integrated, support Li-ion battery charging and hardware On/OFF controllingOnboard GDI for easy connection with screensWi-Fi and Bluetooth 5 dual-mode communicationApplicationsAIoT-related projectsSpeech recognitionImage recognitionSpecificationBasic ParametersOperating Voltage: 3.3VType-C Input Voltage: 5V DCVCC Input Voltage: 5V DCMax Charging Current: 1AOperating Temperature: -20 to 70°CDimension: 25.4x60mm/1×2.36”Hardware InformationProcessor: Xtensa® dual-core 32-bit LX7 microprocessorMain Frequency: 240 MHzSRAM: 512KBROM: 384KBFlash: 16MBPSRAM: 8MBRTC SRAM: 16KBUSB: USB 2.0 OTG full-speedWIFIWIFI Protocol: IEEE 802.11b/g/nBandwidth: Support 20 MHz and 40 MHz at 2.4 GHz bandWIFI Mode: Station, SoftAP, SoftAP Station combined modeWIFI Frequency: 2.4GHzFrame Aggregation: TX/RX A-MPDU, TX/RX A-MSDUBluetoothBluetooth Protocol: Bluetooth 5, Bluetooth meshBluetooth Frequency: 125 Kbps, 500 Kbps, 1 Mbps, 2 MbpsPortsDigital I/O x26LED PWM Controller 8 ChannelsSPI x4UART x3I2C x2I2S x2IR Transceiver: transmit channel x5, receive channel x52×12-bit SAR ADC, 20 ChannelsDMA Controller: transmit channel x5, receive channel x5ProjectsProject: DIY a plant growth recorder with ESP32 S3Introduction: I plan to create a DIY plant growth recorder that will allow me to monitor the entire growth process of my plants from seedling to maturity, while tracking environmental conditions throughout.ESP32 S3 Project – DIY a plant growth recorder with ESP32 S3Documents