Open Hardware and Linux Hardware: Pine64 Ox64 SBC, I2C, Arduino, Kria KR260, and Siemens
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$6 Pine64 Ox64 SBC features BL808 64-bit/32-bit RISC-V multi-protocol WiSoC with 64MB RAM - CNX Software
Pine64 Ox64 is a single board computer powered by Bouffalo Lab BL808 dual-core 64-bit/32-bit RISC-V processor with up to 64MB embedded RAM, multiple radios for WiFi 4, Bluetooth 5.0, and 802.15.4 (Zigbee), as well as an AI accelerator.
The board also features up to 16MB XSPI NOR flash, a MicroSD card socket, a USB 2.0 OTG port with support for a 2-lane MIPI CSI camera module, and two 20-pin GPIO headers for expansion. It measures just 51 x 21mm, or in other words, is about the size of a Raspberry Pi Pico W.
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Using I²C Sensors With Any Linux Via USB And IIO | Hackaday
Hooking up I2C sensors is something which is generally associated with microcontrollers and SBCs, yet it’s very easy to use such I2C sensors from basically any system that runs Linux. After all, I2C (that is, SMBus) is one of the interfaces that is highly likely to be used on your PC’s mainboard as well as peripherals. This means that running our own devices like the well-known BME280 temperature, pressure and humidity sensor, or Si1145 light sensor should be a piece of cake.
In a blog post from a few years ago, [Peter Molnar] explains in detail how to wire up a physical adapter to add a USB-connected I2C interface to a system. At its core is the ATtiny85 AVR-based MCU, which provides a built-in USB interface, running the I2C-Tiny-USB firmware.
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Detect vandalism using audio classification on the Nano 33 BLE Sense | Arduino Blog
Having something broken into and/or destroyed is an act that most people hope to avoid altogether or at least catch the perpetrator in the act when it does occur. And as Nekhil R. notes in his project write-up, traditional deterrence/detection methods often fail, meaning that a newer type of solution was necessary.
Unlike other glass breaking sensors, Nekhil’s project relies on a single, inexpensive Arduino Nano 33 BLE Sense and its onboard digital microphone to record audio, classify it, and then alert a property owner over WiFi via an ESP8266-01 board. The dataset used to train the machine learning model came from two sources: the Microsoft Scalable Noisy Speech Dataset for background noise, and breaking glass recorded on the device itself. Both of these were added to an Edge Impulse project via the Studio and split into two-second samples before being processed by a Mel-filterbank Energy (MFE) algorithm.
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Binbot 9000 moves to where the trash is | Arduino Blog
Our modern societies create a lot of garbage, which we can fortunately remove from our homes thanks to local waste management services. But the garbage people won’t come sift through your house for refuse, which forces you to utilize trash bins. Those bins never seem to be nearby when you need them, which is why James Bruton built the Binbot 9000.
The Binbot 9000 is exactly what it sounds like: a robotic trash can. No longer must the bin remain stationed in some out-of-the-way location. Instead, Binbot 9000 can drive around a home in search of people who need to throw things away.
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Edge Impulse on Kria KR260 - Hackster.io
This project walks through how to install Edge Impulse on the Ubuntu 22.04 image of the Kria KR260 and the development of a basic ML model.
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Siemens streamlines medical standards compliance for Linux OS based systems
Siemens Digital Industries Software today introduced the first software documentation package developed to help original equipment manufacturers (OEMs) streamline compliance with stringent standards for medical device manufacturers deploying either of Siemens’ embedded Linux distributions, Sokol™ Flex OS software or Sokol™ Omni OS software.