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Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on StackChan is a cute, community-build, open-source AI desktop robot (Crowdfunding)

StackChan is a cute, community-build, open-source AI desktop robot (Crowdfunding)

M5Stack Stackchan

StackChan is an open-source AI desktop robot based on the M5Stack CoreS3 ESP32-S3 IoT controller that works as an AI Voice Assistant and can notably be used for Smart Home & IoT control. It features a 2-inch touchscreen display, a VGA camera, a dual microphone array and a 1W speaker for voice interaction, a few sensors, an infrared receiver, an infrared transmitter/blaster, two servos for horizontal and vertical movement, and a few buttons and LEDs. StackChan specifications: Core module – M5Stack CoreS3 IoT controller Wireless MCU – Espressif Systems ESP32-S3FN16R8 CPU – Dual-core 32-bit Xtensa LX7 microcontroller with AI vector instructions up to 240MHz, RISC-V ULP co-processor Memory – 512KB SRAM, 8MB PSRAM Storage – 16MB flash, Wirleess – 2.4GHz WiFi 4 (802.11b/g/n), Bluetooth 5.0 BLE + Mesh Antenna – Internal 3D antenna Storage – MicroSD card slot Display – 2-inch IPS display with 320×240 resolution, 65,536 colors via ILI9342C […]

Posted on by Kumpee Teeravech - No Comments on DFRobot HUSKYLENS 2 AI camera review – From built-in AI samples to training a custom model to detect elephants

DFRobot HUSKYLENS 2 AI camera review – From built-in AI samples to training a custom model to detect elephants

Huskylens 2 Ai camera review

Hello, today I am going to review the HUSKYLENS 2, released in October 2025. It is the next generation of HUSKYLENS, an AI vision sensor equipped with a Kendryte K230 dual-core RISC-V SoC with a 6 TOPS AI accelerator and a 2.4-inch IPS touchscreen. The device runs machine vision algorithms fully on-device, providing fast and low-latency performance, and includes more than 15 built-in AI models. HUSKYLENS 2 also supports deploying custom-trained models, including integration with Large Language Models (LLMs) via a Model Context Protocol (MCP) service. In addition, it is compatible with various microcontrollers, such as Arduino and Raspberry Pi, through UART or I2C communication interfaces. HUSKYLENS 2 unboxing The manufacturer sent the HUSKYLENS 2 module and the Microscope Lens separately. Both parcels were shipped from Chengdu, China, and arrived at my office in Chanthaburi, Thailand, in about one week. The parcels were packed in standard cardboard boxes and arrived […]

Posted on by Debashis Das - 2 Comments on Elecrow AI starter kit turns NVIDIA Jetson Orin Nano into a learning platform with 11.6-inch display, 30 electronics modules

Elecrow AI starter kit turns NVIDIA Jetson Orin Nano into a learning platform with 11.6-inch display, 30 electronics modules

Jetson Orin Nano AI learning kit

Elecrow AI Starter Kit for the NVIDIA Jetson Orin Nano turns the NVIDIA Jetson Orin Nano into a learning and educational kit for students, educators, and hardware enthusiasts looking for a rapid and powerful prototyping platform. The kit integrates an 11.6-inch IPS touchscreen, an 8MP servo-controlled gimbal camera, a voice interaction module, and 30 common electronics modules embedded in the kit. The company also provides 39 Python tutorials for sensor control, computer vision, and basic AI workflows. In addition to the display, camera, and audio features, the kit also includes expansion through I2C, UART, and GPIO. Jetson Orin Nano AI Starter Kit specifications: Main Board – NVIDIA Jetson Orin Nano (Not included in the kit) Display – 11.6-inch IPS touchscreen display with 1366 × 768 resolution Onboard modules Input modules Multimedia – 8MP IMX219-based camera with dual-servo gimbal (PTZ-style control) Sensors Temperature & humidity sensor Ultrasonic distance sensor PIR motion […]

Posted on by Debashis Das - No Comments on Cerelog ESP-EEG – A low-cost ESP32-based EEG acquisition board for brain computer interface (BCI) experiments

Cerelog ESP-EEG – A low-cost ESP32-based EEG acquisition board for brain computer interface (BCI) experiments

Cerelog ESP EEG ESP32 EEG acquisition board

The Cerelog ESP-EEG is an 8-channel, low-cost brain computer interface (BCI) circuit board built around the ESP32 MCU and designed for EEG data acquisition. The board supports 8-channel, 24-bit EEG data collection and connects to a host system over USB-C for both power and data. The board has an active noise-removal bias pin which reduces mains interference, along with onboard status LEDs, including a dedicated indicator for active data capture. It works with third-party or DIY EEG headsets using adapter boards, and STL files are provided for 3D printed mounts. Cerelog also offers various software tools and sample code to enable real-time EEG visualization, BCI experiments, neurofeedback, and custom brain-controlled applications. Cerelog ESP-EEG specifications: Wireless Module – ESP32-WROOM-32 SoC – ESP32 CPU – Dual-core processor @ 160 MHz Memory  – 520 KB SRAM Wireless WiFi 802.11 b/g/n, Bluetooth 4.2 Storage – 4 MB flash PCB antenna Analog Front-End (via TI’s […]

Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on CrowPi 3 AI Learning Kit is powered by a Raspberry Pi 5 SBC, works with Arduino Nano, BBC Micro:bit, and Raspberry Pi Pico boards

CrowPi 3 AI Learning Kit is powered by a Raspberry Pi 5 SBC, works with Arduino Nano, BBC Micro:bit, and Raspberry Pi Pico boards

CrowPi 3 AI Learning platform

Elecrow CrowPi 3 is the latest CrowPi learning and development kit featuring 41 built-in modules and over 150 lessons, and offering compatibility with Raspberry Pi 5, Arduino Nano, BBC Micro:bit, and Raspberry Pi Pico single board computers and development boards. It follows the CrowPi portable learning kit (Raspberry Pi 3B+/Zero), CrowPi 2 Raspberry Pi 4 electronics learning laptop, and CrowPi L laptop (Raspberry Pi 4 models), but the CrowPi 3 is the first to focus on Artificial Intelligence (AI) learning with a Raspberry Pi 5 and support for LLMs like DeepSeek, Google Gemini, and OpenAI chat besides courses about electronics and computer vision. CrowPi 3 specifications: Compatible boards Raspberry Pi 5 (required) – Broadcom BCM2712 quad-core Arm Cortex-A76, up to 2.4GHz, 4GB or 8GB RAM. OS: Raspberry Pi OS (Debian Linux) or others Optional via headers or slots Arduino Nano Raspberry Pi Pico 1/1 W/2/2 W  BBC micro:bit Display – […]

Posted on by Debashis Das - 4 Comments on ESP32-S3 AIoT Basic – A learning and prototyping kit with camera, audio, LCD, and sensors

ESP32-S3 AIoT Basic – A learning and prototyping kit with camera, audio, LCD, and sensors

ESP32 S3 AIoT Basic for beginners, classrooms, rapid prototy

The ESP32-S3 AIoT Basic is a low-cost, learning, and prototyping kit for the ESP32-S3. The board integrates common AIoT peripherals directly onto a single PCB, making the design part easy for beginners, classrooms, and rapid prototyping. Built around an ESP32-S3 board, the development platform integrates nine commonly used modules directly on the PCB, including a button, buzzer, LED indicator, light sensor, LCD, digital microphone, SD card slot, audio amplifier, and a camera. Most AI and IoT demos can be run without breadboards or jumper wires, while expansion is supported through standard pin headers and Grove connectors. The board supports 5V power via USB-C, and 6–12 V power input via Vin for driving additional devices. With various tutorials and sample projects, it is suitable for AIoT learning, STEM education, voice and vision demos, sensor-based projects, and quick proof-of-concept development. ESP32-S3 AIoT Basic Specifications: Main board – ESP32-S3 Core Board SoC – […]

Posted on by Debashis Das - 4 Comments on ESP32-P4 learning and prototyping kit features 7-inch touchscreen, comes with 16 modules and AI lessons

ESP32-P4 learning and prototyping kit features 7-inch touchscreen, comes with 16 modules and AI lessons

Elecrow ESP32 P4 learning and prototyping Kit

Elecrow’s “All-in-One Starter Kit for ESP32-P4” is an open-source learning and prototyping platform based on the ESP32-P4 processor, offering AI, multimedia, and embedded features in a single, self-contained kit designed for students, educational institutions, and developers for rapid prototyping. The open hardware kit integrates a 7-inch touchscreen display, a 2MP camera, and sixteen built-in electronic modules, supported by over 20 structured lessons that progressively cover I/Os, audio, LVGL GUI development, and basic AI use cases. Development is done in C using Espressif’s ESP-IDF framework, ready-to-build examples, and modular BSP drivers, making the kit suitable for learning embedded systems, IoT device control, human-machine interfaces, smart home concepts, and entry-level Edge AI applications. All-in-one Starter Kit for ESP32-P4 kit specifications: Wireless MCU – ESP32-P4NRW32 MCU Dual-core RISC-V microcontroller @ 400 MHz with AI instructions extension and single-precision FPU Single-RISC-V LP (Low-power) MCU core @ up to 40 MHz GPU – 2D Pixel […]

Posted on by Debashis Das - No Comments on tinySA is a low-cost handheld spectrum analyzer with built-in signal generator

tinySA is a low-cost handheld spectrum analyzer with built-in signal generator

tinySA Spectrum Analyzers and Signal Generators

The tinySA is a compact, low-cost handheld spectrum analyzer and RF signal generator designed for hobbyists, radio amateurs, educators, and engineers. It comes in three different variants and can be used for RF debugging, signal inspection, interference hunting, filter testing, antenna-related measurements, and basic RF education, both in the field and on the bench. The product line includes the tinySA Basic, tinySA Ultra, and tinySA Ultra+, which mainly differ in their supported frequency ranges and performance. The tinySA Basic supports 100 kHz to 350 MHz on its low input and up to about 960 MHz on the high input, while the Ultra and Ultra+ models can observe signals up to 12GHz. The devices run from an internal rechargeable battery with USB-C charging, support firmware updates, internal self-test and calibration routines, marker and peak detection, configurable frequency span and amplitude settings, and PC control over USB. Input protection limits are specified at +10 […]