Open Hardware: Raspberry Pi, Arduino, PinePhone
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Beagle introduces something like a Raspberry Pi, with long-range wireless
BeagleBoard has stepped into Raspberry Pi territory with a quad-Arm-core board called BeaglePlay, and at the same time has released a wireless microcontroller module called BeagleConnect Freedom.
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BeagleConnect™ Freedom
BeagleConnect™ is a revolutionary technology virtually eliminating low-level software development for IoT and IIoT applications, such as building automation, factory automation, and home automation. Choosing BeagleConnect™ simplifies development by eliminating the need for layer of software development. While numerous IoT and IIoT solutions available today provide massive software libraries for microcontrollers supporting a limited body of sensors, actuators and indicators as well as libraries for communicating over various networks, BeagleConnect™ simply eliminates the need for these libraries by shifting the burden into the most massive and collaborative software project of all time, the Linux kernel.
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Infra-Red, In Situ (IRIS) Inspection of Silicon
This post introduces a technique I call “Infra-Red, In Situ” (IRIS) inspection. It is founded on two insights: first, that silicon is transparent to infra-red light; second, that a digital camera can be modified to “see” in infra-red, thus effectively “seeing through” silicon chips. We can use these insights to inspect an increasingly popular family of chip packages known as Wafer Level Chip Scale Packages (WLCSPs) by shining infrared light through the back side of the package and detecting reflections from the lowest layers of metal using a digital camera. This technique works even after the chip has been assembled into a finished product. However, the resolution of the imaging method is limited to micron-scale features.
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Turn your lights on and off by staring at this little robotic switch
Based on an embedded machine learning model and a microcontroller, this device uses Person Sensor from Useful Sensors, which relies on a camera to gather images, processes them, and outputs the results over I2C. This information can include the total number of faces as well as individual bounding boxes for every detected face. From here, the information sent by the Person Sensor is read by an Arduino Uno and used to determine if someone is staring at the switch.
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Predicting when a fan fail by listening to it
Richmond started by collecting 15 minutes of data for each label, namely background noise, normal operation, soft failure, and severe failure. Once collected, the data was split into two-second samples and uploaded to the Edge Impulse Studio, after which an impulse was configured to use an MFE audio processing block and a Keras classification model. Once trained on the dataset, the model achieved an accuracy of almost 96% using real-world testing data.
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Mobile Linux camera pt6
The expectations this software has for "raw" image data is that it's high bit depth linear-light sensor data that has not been debayered yet. The data from the Librem 5 is exactly this, the PinePhone sensor data is weirder.