LILYGO T-LoRa Pager: ESP32-S3 IoT Board with LoRa, GNSS, NFC, and IMU Support


https://www.electronics-lab.com/lilygo-t-lora-pager-esp32-s3-iot-board-with-lora-gnss-nfc-and-imu-support/

The T-LoRa Pager from LILYGO is a compact IoT development board designed for applications such as asset tracking, remote sensing, and portable communication. It is powered by the ESP32-S3 microcontroller and comes with 16MB flash and 8MB PSRAM. Key hardware features include an RTC circuit, GPIO expansion headers, a battery management system, an audio codec, […]

Altech DO-1 Universal Monitor with Dual Power Input Supports Monitoring of up to 128 Modbus RTU/TCP Devices with 30-Day Battery Backup


https://www.electronics-lab.com/altech-do-1-universal-monitor-with-dual-power-input-supports-monitoring-of-up-to-128-modbus-rtu-tcp-devices-with-30-day-battery-backup/

Altech Corp. has recently announced the release of its DO-1 universal monitor for Modbus devices. By removing the traditional barriers to entry, this solution opens the door to valuable operational insights that were previously inaccessible, particularly for small- and medium-sized companies, to easily monitor, collect, and analyse their equipment and process data without any subscription […]

LILYGO T-Pico 2350 Development Kit Features Raspberry Pi RP2350, ESP32-C6, 2.33-inch Color Touchscreen, and HDMI Output


https://www.electronics-lab.com/lilygo-t-pico-2350-development-kit-features-raspberry-pi-rp2350-esp32-c6-2-33-inch-color-touchscreen-and-hdmi-output/

LILYGO has announced a new model of T-Pico all-in-one development kit known as the T-Pico-2350. It is a fully integrated devkit featuring a Raspberry Pi RP2350A MCU and an Espressif ESP32-C6 SoC for wireless connectivity. The design is an update to the T-PicoC3 introduced in 2022, with the case design of the T-Display S3 Pro. […]

Topaz Tz170 J484 Development Kit features a 16 nm Efinix Quantum fabric FPGA and 256 Mbit of LPDDR4 memory


https://www.electronics-lab.com/topaz-tz170-j484-development-kit-features-a-16-nm-efinix-quantum-fabric-fpga-and-256-mbit-of-lpddr4-memory/

The Topaz Tz170 J484 FPGA Development Kit from Efinix is a compact FPGA evaluation platform built around the Efinix Tz170 FPGA for evaluating and prototyping. This FPGA is built around a low-power, high-density 16 nm Quantum fabric and comes in a compact 484-ball FineLine BGA package. It integrates onboard memory, configurable I/O, and a preloaded […]

ArmSoM Forge1 SBC Features Rockchip RK3506J SoC with Cortex-A7/M0 Cores for Industrial and Audio Applications


https://www.electronics-lab.com/armsom-forge1-sbc-features-rockchip-rk3506j-soc-with-cortex-a7-m0-cores-for-industrial-and-audio-applications/

ArmSoM Forge1 is an industrial-grade single-board computer (SBC) built for embedded applications such as smart audio systems and factory automation. It is based on the Rockchip RK3506J system-on-chip, which integrates a triple-core Arm Cortex-A7 CPU running at up to 1.5GHz along with an Arm Cortex-M0 core for real-time control tasks. The board comes with 512MB […]

Forlinx FET3506J-S SoM and OK3506J-S Carrier Board Feature Rockchip RK3506J SoC for Industrial Applications


https://www.electronics-lab.com/forlinx-fet3506j-s-som-and-ok3506j-s-carrier-board-feature-rockchip-rk3506j-soc-for-industrial-applications/

Forlinx Embedded’s FET3506J-S System on Module (SoM) features the Rockchip RK3506J, an industrial-grade tri-core Cortex-A7 SoC designed for smart industrial applications. It operates at low power consumption of approximately 0.7W and can withstand temperatures up to +85°C at full load without additional heat dissipation. Originally introduced in 2023 through a product roadmap, the Rockchip RK3506 […]

CM5-NANO-B: Raspberry Pi CM5 Carrier Board with USB 3.2, HDMI, PCIe, and Gigabit Ethernet


https://www.electronics-lab.com/cm5-nano-b-raspberry-pi-cm5-carrier-board-with-usb-3-2-hdmi-pcie-and-gigabit-ethernet/

The CM5-NANO-B is a CM5 carrier board designed for the Raspberry Pi Compute Module 5 (CM5), integrating essential I/O interfaces in a compact form factor. It features a USB 3.2 Gen1 port, HDMI output, an audio interface, and an Ethernet port, making it suitable for embedded applications that require display and connectivity options. The board […]

Adafruit Metro RP2350: RP2350-Based Arduino-Compatible Board with Dual Cortex-M33, TPS563201 Buck Converter, and HSTX Expansion


https://www.electronics-lab.com/adafruit-metro-rp2350-rp2350-based-arduino-compatible-board-with-dual-cortex-m33-tps563201-buck-converter-and-hstx-expansion/

The Adafruit Metro RP2350 is an Arduino-compatible development board based on the Raspberry Pi RP2350 microcontroller. It features a dual-core ARM Cortex-M33 processor running at 150MHz, 528KB of RAM, and 16MB of QSPI flash for program storage. The board operates at 3.3V logic and includes a 5V buck converter (TPS563201) that accepts a 4.5V to […]

STEVAL-MKI109D: An Evaluation Platform for ST MEMS Sensors


https://www.electronics-lab.com/steval-mki109d-an-evaluation-platform-for-st-mems-sensors/

The STEVAL-MKI109D, ST’s latest-generation sensor evaluation board, is powered by the STM32H563ZI microcontroller featuring an Arm Cortex-M33 core. This core enables the processing of complex datasets and sensor readings, including barometric pressure, accelerometer, and gyroscope data, and facilitates the rapid development of context-aware applications while utilizing MEMS sensors. Specifications of the STEVAL-MKI109D Microcontroller STM32H563ZI Arm […]

Axelera AI Metis Compute Board: RK3588-Based SBC with Metis AI Accelerator for Edge AI Applications


https://www.electronics-lab.com/axelera-ai-metis-compute-board-rk3588-based-sbc-with-metis-ai-accelerator-for-edge-ai-applications/

Axelera AI has introduced the Metis Compute Board, a compact SBC designed for edge AI applications. It features the Rockchip RK3588 processor, combining Cortex-A76 cores for high performance and Cortex-A55 cores for power efficiency. The board integrates the Metis AI accelerator with a four-lane PCIe connection to the CPU, enabling high-speed AI inference. With 16GB […]