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Memphis Electronic and Engicam

Long-term partnership for sustainable supply chain.

07 December 2021

A customer success story, a case study to explore.  Read the full article and discover how to set up and maintain a great partnership.

Adelsy presents the new Engicam's SmarCore EHL

30 November 2021

An interesting presentation by our italian distributor Adelsy, about our module based on Intel® Elkhart Lake ATOM® x6000E: "SmarCore EHL è il nuovo modulo Engicam su standard SMARC con processore Intel® Elkhart Lake ATOM® x6000E (anche Pentium® Celeron® saranno presto disponibili). Il ...

A conversation with SGET e.V.

Engicam SMARC modules and development projects for the next future. 

16 November 2021

We have enjoyed being interviewed by SGET e.V., (Standardization Group for Embedded Technologies) about Engicam #SMARC modules and our development projects for the next future.  'Engicam Srl is one of our Italian SGET members, specialized in providing high-end complex embedded solutions in a smart and flexible way. We have talked to their marketing team to get to know ...

Linux Embedded & Yocto training

Online training

22 October 2021

Do you need to learn how to begin to cross-compile the Linux Kernel for an ARM card and use Yocto Project to generate recipes and custom layers? We suggest you a very interesting online training of our partner KOAN: Linux Embedded & Yocto training – ONLINE Dates: 22/11/2021 - 26/11/2021 Time: 14:00 - 18:00   _The course will be held in Italian_. The reference hardware ...

Engicam becomes Intel® Partner Alliance Gold

06 September 2021

We are proud to be upgraded to Intel® Partner Alliance Gold. This is the recognition of a partnership that lasts over time in an increasingly profitable and effective way that has allowed us to develop high-performance solutions based on the latest Intel® modules, such as SmarCore EHL and SmarCore APL x86.

Machine Learning Application with NXP i.Mx8M Plus

Engicam for Developers - new webinars

20 May 2021

Enjoy now the new playlist on Engicam Youtube channel dedicated to developers: "BSP and Machine Learning Application with Engicam NXP i.Mx8M Plus based SOM".   You can take a look at 4 chapters:  Chapter 1 - Introduction to the Hardware: Engicam NXP i.Mx8M Plus based SOM - https://youtu.be/AZYnNi178FU Chapter 2 - BSP Introduction, Yocto Project, cross-compilation, ...

NXP i.MX8M Plus inference benchmark

An interview with Javier Garcia from GL Research

13 April 2021

We had the pleasure of speaking with Javier Garcia, founder and lead scientist at GL Research, about a benchmark made by his company on the performance of i.MX8MPlus products on Engicam module. Hi Javier! Can you please explain what business are your company in and what it's your role inside? My name is Javier Garcia and I'm the founder and lead scientist at GL Research, an ...

Beyond Machine Learning with NXP’s i.MX 8M Plus applications processor

Webinar Invitation - February 16-19, 2021

05 February 2021

Prior to the public launch of  i.MX8M Plus on Embedded World 2021, Engicam will be one of the protagonist of a webinar held by NXP Semiconductors and Avnet Silica to give to users insights on use cases and solutions with the i.MX8M Plus device and with SoMs from Engicam and Avnet Integrated. The webinar consists of two parts: a general presentation in local language and additional ...

'Engicam's SOM based on STM32MP1 processors'

Save the date! Tuesday, February 09, 2021 09:30 AM (GMT+1)

05 February 2021

  In collaboration with ST Microlectronics, we are pleased to invite you to our partner Avnet Silica's free webinar. The potential of the STM32MP1 MPU family along with the many benefits of the new SoM range from Engicam, based on these devices, will be highlighted. In this webinar, we will present the BSP for our modules based on the STM32MP1 processor ...

Yocto Project 2.7 support for MX6 Engicam boards

13 January 2021

Our partner KOAN released an unofficial Yocto Project setup system for Engicam iMX6 boards family for the latest BSP available from Engicam. The setup details are available on KOAN Github