Devices: Coral mPCIe, Zynq, and ESPHome
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Using Google Coral mPCIe Card into a Compact Marvell Octeon TX Linux SBC
Google launched Coral mPCIe and M.2 cards at the very beginning of the year. The cards integrate the company’s 4 TOPS Edge TPU used for low power edge AI applications to bring the solutions to boards with mPCIe or M.2 sockets.
Those are just hardware sockets that are optionally connected to USB, PCIe, I2C, etc… so you have to make sure the socket on your board exposes PCIe Gen2 x1. If you worry about compatibility, it’s good to get a board that’s known to work, and one of those is Gateworks Newport GW6903 SBC that offers two mPCIe sockets and features Marvell Octeon TX dual or quad-core Armv8 processor coupled with up to 4GB RAM.
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Zynq UltraScale+ Arm FPGA FZ3 Deep Learning Accelerator Card Supports Baidu Brain AI Tools
FZ3 card runs PetaLinux, and supports Baidu PaddlePaddle deep learning AI framework, as well as Baidu Brain AI tools such as EasyDL, AI Studio, and EasyEdge. Those enable the development of deep learning applications such as smart cameras, AI Edge embedded PCs, AI robots, smart cars, intelligent electronic scale, autonomous UAV, and more.
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Simple IoT Devices using ESPHome
ESPHome is a build and deployment system that takes all of the manual coding work out of integrating custom Internet of Things (IoT) devices with Home Assistant. It advertises support for not only the ESP8266, but also its big-brother the ESP32 and even various ESP8266-based off-the-shelf consumer devices from Sonoff. ESPHome achieves a code-free integration by implementing the auto-discovery protocols necessary for Home Assistant to pull the features of the device into the hub with just a few clicks. Wiring up an ESP8266 to the desired hardware, and defining that hardware properly in the configuration, is all that is needed to enable it in the hub.
For hardware wired to an ESP8266 to be used with ESPHome, it must first be supported by an ESPHome component. The ESPHome project's website lists the various hardware it understands how to work with, from sensors to displays. While the collection of IoT device components is not as comprehensive as one could imagine, ESPHome does offer many of the common ones used in smart homes. The project's last release, v1.14.0 in November 2019, included 24 new components.
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The ESPHome project has a healthy community supporting it with 132 contributors and 67 releases to date, including the latest v1.14.0 release. The project itself operates under a dual licensing model where the C++ code is released under GPLv3 and the Python code is released under an MIT license. Those interested in contributing (both documentation or code) can review the contributor guidelines for how best to get involved. There doesn't appear to be a mailing list for the project, but there is a Discord channel available.
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