T-Watch-Keyboard-C3 with ESP32 “watch”, ESP32-C3 keyboard looks like a miniature PC replica

LILYGO Watch Keyboard C3

T-Watch-Keyboard-C3 is a device that looks like a miniature PC replica comprised of an ESP32-C3 powered keyboard, and the TTGO T-Watch ESP32 programmable device with a 1.54-inch touchscreen display. The LilyGo TTGO T-Watch ESP32 programmable touchscreen display has been around for a while, and the company used to provide an accessory keyboard based on Microchip ATSAM20 Cortex-M0+ microcontroller that has now been replaced with ESP32-C3 WiFi and Bluetooth RISC-V microcontroller to create the T-Watch-Keyboard-C3 devices pictured below.   T-Watch-Keyboard-C3 specifications: TTGO T-Watch MCU – ESP32-D0WDQ6 dual-core microcontroller @ 240 MHz with WiFi 4 and Bluetooth 4.x with 520KB SRAM Memory – 8MB PSRAM Storage – 16MB QSPI flash Display – 1.54-inch LCD screen USB – 1x USB Type-C port for power and programming via CP2104 USB to TTL chip Sensor – 3-axis accelerometer Misc – Power button, RTC Dimensions – 40 x 38 x 20 mm Weight – 43.19 grams […]

Makerfabs 3.5-inch TFT touchscreen display features ESP32-S3 SoC

Makerfabs 3.5-inch wireless parallel TFT display with Touch

Makerfabs has launched a 3.5-inch TFT touchscreen display with built-in WiFi and Bluetooth connectivity through an ESP32-S3 dual-core Tensilica LX7 microcontroller clocked at 240 MHz with vector instructions for AI acceleration. This display offers a 320×480 resolution through the ILI9488 LCD driver, uses a 16-bit parallel interface for communication with ESP32-S3 clocked at up to 20 Mhz making it suitable for smooth graphics user interface, and the company also claims it is smooth enough for video displays, but more on that later. Specifications: Wireless module – ESP32-S3-WROOM-1-N16R2 with Espressif Systems ESP32-S3 dual-core Tensilica LX7 @ up to 240 MHz with vector instructions for AI acceleration, 512KB RAM, 2.4 GHz WiFi 4 and Bluetooth 5.0 LE with support for long-range, up to 2Mbps data rate, mesh networking 16MB QSPI flash 2MB PSRAM PCB antenna Storage – MicroSD card socket Display – 3.5-inch color TFT LCD with 480×320 resolution, 16-bit parallel interface […]

Arduino IDE 2.0 is now officially released

Arduino IDE 2.0.0

The first stable release of Arduino IDE 2.0 is now out. Based on the Eclipse Theia framework, the new IDE provides a more modern and user-friendly user interface, faster compilation time, and more features we’ll discuss in this post. Arduino initially introduced the Arduino IDE 2.0 beta in March 2021 with a live debugger with breakpoints support, a revamped user interface with features such as autocompletion of variables and functions. After 18 months of debugging with the help of members of the community such as Paul Stoffregen (the maker of the Teensy boards), the Arduino IDE 2.0 is not an experimental software anymore, and it’s the first version you’d see in the download page. The Arduino IDE 2.0 is available for Windows 10 64-bit and newer, Linux X86-64, and macOS 10.14 “Mojave” or newer. If you’ve already installed Arduino 1.x, it will inform you of updates for your installed libraries […]

Sensirion SCD40 CO2 sensor units for makers: M5Stack UNIT CO2 and TeHyBug ESP8285 device

M5Stack UNIT CO2

We just wrote about the Infineon XENSIV PAS CO2 Shield2Go board to measure carbon dioxide (CO2) levels last week, but I’ve just come across two more hardware with a CO2 sensor designed for makers, but based on Sensirion SCD40 sensor instead, and mostly designed to monitor indoor CO2 levels since high concentrations may impact your health negatively. The first one is the M5Stack UNIT CO2 that’s designed to be connected to one of the company’s Core modules through an I2C interface, and TeHyBug portable mini sensor device equipped with ESP8285 WiFi microcontroller, as well as optional AHT10 temperature & humidity sensor and BMP280 pressure sensor, besides the SCD40 sensor. M5Stack UNIT CO2 Specifications: Sensirion SCD40 sensor CO2 Measurement range – 400 ~ 2000 ppm CO2 Sampling accuracy – ±(50 ppm + 5% of reading) Temperature range – -10 – 60°C with 0.8°C   accuracy Humidity range – 0 – 95% RH […]

Infineon XENSIV PAS CO2 Shield2Go board enables carbon dioxide measurements

Infineon XENSIV PAS CO2 Shield2Go board

Infineon has added new a shied to its Shield2Go ecosystem with the XENSIV PAS CO2 Shield2Go board integrating the company’s XENSIV PAS CO2 sensor capable of measuring carbon dioxide levels. We first wrote about the Shield2Go module with the OPTIGA Trust-M evaluation kit integrating a security module, but the family also includes various sensors shield and microcontroller boards notably the XMC 2Go board. The new Shield2Go board can be used for both air quality monitoring and controlled ventilation for energy savings.     XENSIV PAS CO2 Shield2Go board specifications: XENSIV PAS CO2 sensor: Accuracy – ±30 ppm ±3% “Advanced compensation and self-calibration algorithms” Host interfaces – UART, I2C, PWM Dimensions – 14 x 13.8 x 7.5 mm 19x through holes and castellated holes with I2C, UART, PWM, interrupt, 5V, 3.3V, GND, plus SWD interface Power Supply 5V DC input 12V DC DCDC boost converter to power the IR transmitter in […]

ESP32 board supports 2.4Ghz LoRa with SX1280 RF transceiver

LilyGO LoRa V1.8 SX1280 antenna headers

We’ve seen plenty of ESP32 LoRa boards with the traditional 433 MHz, 868 MHz, or 915MHz frequencies, but I think LilyGO LoRa V1.8 (aka T3 V1.8) is the first ESP32 board that integrates a Semtech SX1280 transceiver for the 2.4GHz LoRa standard used for global coverage, notably maritime applications, and ranging. The ESP32 & SX1280 board also offers 26 pins for expansion, a microSD card for data storage, a 2-pin connector for batteries, a 0.96-inch OLED for information display, and comes with a 3D antenna and u.FL connector for WiFi and Bluetooth, and an SMA antenna for LoRa connectivity. LilyGO LoRa/T3 V1.8 specifications: SoC – Espressif ESP32 dual-core Xtensa LX6 processor with 2.4 GHz WiFi 4 and Bluetooth 4.2 Storage – 4MB SPI flash, microSD card slot Display – 0.96-inch OLED display with 128×64 resolution (SSD1306 I2C driver) Connectivity 802.11 b/g/n WiFi 4 up to 150 Mbps +  Bluetooth 4.2 […]

$7 Lolin S3 ESP32-S3 board ships with MicroPython firmware

Lolin S3 ESP32-S3 board

Lolin S3 is the first ESP32-S3 board from the company, but instead of using the more compact D1 mini form factor, the board features a longer design with two rows of 20 pins offering up to 31 GPIOs. Based on ESP32-S3-WROOM-1 module, the board features 16MB QSPI flash, 8MB SPRAM, two USB Type-C OTG and UART ports, a Lolin I2C port, an RGB LED, as well as Reset and user buttons. Lolin S3 specifications: Wireless module – ESP32-S3-WROOM-1 module with: Espressif Systems ESP32-S3 dual-core Tensilica LX7 @ up to 240 MHz with vector instructions for AI acceleration, 512KB RAM, 2.4 GHz WiFi 4 and Bluetooth 5.0 LE with support for long-range, up to 2Mbps data rate, mesh networking 16MB QSPI flash 8MB PSRAM PCB antenna USB – 2x USB Type-C ports, one OTG port, one UART port for programming and debugging Expansion 2x 20-pin headers with up to 31x GPIO, […]

AI, computer vision meet LoRaWAN with SenseCAP K1100 sensor prototype kit

Wio Terminal Grove Vision AI LoRaWAN module

CNXSoft: This is another tutorial using SenseCAP K1100 sensor prototype kit translated from CNX Software Thai. This post shows how computer vision/AI vision can be combined with LoRaWAN using the Arduino-programmable Wio Terminal, a Grove camera module, and LoRa-E5 module connecting to a private LoRaWAN network using open-source tools such as Node-RED and InfluxDB. In the first part of SenseCAP K1100 review/tutorial we connected various sensors to the Wio Terminal board and transmitted the data wirelessly through the LoRa-E5 LoRaWAN module after setting the frequency band for Thailand (AS923). In the second part, we’ll connect the Grove Vision AI module part of the SenseCAP K1100 sensor prototype kit to the Wio Terminal in order to train models to capture faces and display the results from the camera on the computer. and evaluate the results of how accurate the Face detection Model is. Finally, we’ll send the data (e.g. confidence) using […]

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