Search Results for : IoT

NANO-6063 is Designed with 2.5GbE featuring Intel TSN/TCC Real-time Capability and -40°C to 85°C Wide operating Temperature for Industrial Automation, Healthcare Systems and Outdoor Gateway Application. Intel Atom® x6000E Series SoC based NANO-ITX Board with Triple Display, GbE LAN,...

STMicroelectronics' color sensor with advanced light flicker extraction is fast and accurate thanks to an individual ADC STMicroelectronics' VD6283 (1.83 mm x 1.0 mm x 0.55 mm) is a color sensor with advanced light flicker extraction. Light measurement is fast and accurate thanks...

MYIR introduces the VECP Starter Kit, a complete Vision Edge Computing Platform designed to support excellent image processing for typical applications like Machine Vision, Industry, IoT, Medical and more others in different areas of business and everyday life. The VECP Starter Kit...

Featuring 6-core NVIDIA Carmel ARM® v8.2 64-bit CPU and 384-core NVIDIA Volta™ GPU, Vecow EAC-2000 Series features power-efficient in a small form factor to empower Edgae AI applications including Traffic Vision, Intelligent Surveillance, Auto Optical Inspection, Smart Factory,...

The R1810 Boost DC/DC Converter is an energy harvesting solution designed for powering low current consuming IoT devices by extracting energy from Photovoltaic cells. Target applications include wireless sensors, home and building automation, remote monitoring, presence detection,...

You don’t usually find a new AI development board by Arduino in the documentation before the release. For the Bosch Sensortec IoT Innovation Challenge, the first batch of the AI board has been sent to the participants. If you are interested in getting your hands on this new Arduino...

Netherlands bands Embedded computing solutions manufacturer, AAEON Technology Europe, last week announced the launch of their latest carrier board; the UP Connect Plus, which was designed to add 5G capability to its popular UP Core Plus and UP Xtreme platforms. The UP Core Plus, an...

For real-time AI applications, it is important to process incoming data using a trained neural network model. For faster data processing, the introduction to AI inference at cloud did support many aspects, increasing efficiency, but the need to process the data at the end device has...