# PWM Published articles for PWM. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## ESP-IDF tutorial series: PWM DevFeed: [ESP-IDF tutorial series: PWM]() Original publisher: [Read original article]() Author: John Lee Published: 2026-08-03T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP-IDF](), [Tutorial](), [Espressif](), [configuration]() Tags: [article](), [blog](), [channel](), [configuration](), [conversion](), [devkit](), [esp-idf](), [espressif](), [generate](), [ledc](), [peripheral](), [pwm](), [signal](), [speed](), [tutorial]() ### AI overview This ESP-IDF tutorial explains pulse-width modulation, including duty cycle, switching frequency, and average voltage. It demonstrates PWM generation with the LEDC peripheral on Espressif devices and describes converting PWM to DC with an RC filter, including ripple and response-speed tradeoffs. ### Source excerpt This article explains what a PWM signal is, and how to generate PWM signal using the ledc peripheral on Espressif devices. It covers the LEDC timer and channel configuration, and shows how to convert a PWM signal into a clean DC value using an RC filter, including the tradeoffs between ripple and response speed. ## Building FOFOCA: An Open-Source AI Robot with ESP32, ESP32-C3, and Edge AI DevFeed: [Building FOFOCA: An Open-Source AI Robot with ESP32, ESP32-C3, and Edge AI]() Original publisher: [Read original article]() Author: John Lee Published: 2026-05-15T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32](), [Embedded Software Dev](), [ESP32-C3](), [Espressif](), [Raspberry Pi](), [Hardware](), [MQTT](), [Open Source](), [Nemotron](), [Cloud]() Tags: [ai](), [api](), [architecture](), [ble](), [blog](), [bluetooth](), [building](), [computer-vision](), [edge](), [edge-ai](), [esp32](), [esp32-c3](), [espressif](), [firmware](), [hardware](), [microcontrollers](), [mqtt](), [nemotron](), [nvidia](), [open-source](), [pwm](), [raspberry-pi](), [real-time](), [risc-v](), [robotics]() ### AI overview This article presents FOFOCA, an open-source household robot reference design using an ESP32 for real-time motor and sensor control, an ESP32-C3 for an MQTT-connected OLED display, and a Raspberry Pi 5 as the processing brain. A local Dell R210 server runs NVIDIA Nemotron Nano 8B and supporting services, while ThinkNEO provides AI governance and audit routing. ### Source excerpt FOFOCA is an open-source reference design for an AI-governed household robot, built around a Raspberry Pi 5 brain, an ESP32 for real-time motor control and sensor polling, and an ESP32-C3 driving an OLED status display over MQTT. This article walks through the hardware architecture, the firmware running on each Espressif chip, and how all of it connects to a local edge AI server running NVIDIA Nemotron Nano 8B for inference -- no cloud dependency required. ## I Rebuilt My Home Server -- Quieter, Faster, and Ready for 2025 DevFeed: [I Rebuilt My Home Server -- Quieter, Faster, and Ready for 2025]() Original publisher: [Read original article]() Author: Techno Tim Published: 2025-04-12T13:00:00Z Content type: opinion Language: en Sources: [Techno Tim]() Topics: [Homelab](), [Hardware](), [servers](), [cpu](), [GPU](), [intel](), [Nvidia](), [NVIDIA RTX]() Tags: [cpu](), [files](), [gpu](), [hardware](), [home-server](), [homelab](), [intel](), [lighting](), [noctua](), [nvidia](), [nvidia-rtx](), [pwm](), [server](), [ssd](), [upgrades]() ### AI overview Techno Tim describes rebuilding a home server with upgraded CPU, GPU, RAM, fans, SSDs, and power supply. The article says the rebuilt system is quieter and faster, and lists hardware including Noctua cooling components, Intel products, NVIDIA GPUs, ECC RAM, and SSDs. ### Source excerpt I rebuilt my home server from the ground up: CPU, GPU, RAM, fans, SSDs, and power supply... even some "accessory lighting". This thing is now quieter, faster, and built to handle just about anything I throw at it in 2025 and hopefully beyond. Thank you to Noctua for helping to make this server quiet! Thank you to Patrick from Serve the Home for the CPU upgrades! (Both Noctua and Patrick gifted... ## I turned a gaming case into a living room NAS DevFeed: [I turned a gaming case into a living room NAS]() Original publisher: [Read original article]() Author: Techno Tim Published: 2024-10-03T13:00:00Z Content type: article Language: en Sources: [Techno Tim]() Topics: [Homelab](), [Hardware](), [Server](), [Windows]() Tags: [asus](), [cpu](), [ddr5](), [gaming](), [hardware](), [home-server](), [homelab](), [nas](), [noctua](), [pwm](), [server](), [windows]() ### AI overview A build article and video describe converting a Fractal Design Terra gaming case into a quiet, attractive living-room NAS and home server. The project builds on an earlier low-energy Windows media server and lists the hardware used, including an Intel Core i3-14100 CPU, ASUS motherboard, 64GB of DDR5 RAM, storage, cooling, and power components. ### Source excerpt This case was meant for gaming but I decided to do a little tinkering to see if I could truly turn this build into a NAS for a good-looking home server in your living room. 📺 Watch Video Info I originally built a standalone media server on Windows that focused on low energy use, but decided to take it one step further. 📦 Products in video (affiliate links): Fractal Design Terra Case: ... ## Building a Low-Power, Fully Loaded Plex Server DevFeed: [Building a Low-Power, Fully Loaded Plex Server]() Original publisher: [Read original article]() Author: Techno Tim Published: 2024-09-16T13:00:00Z Content type: tutorial Language: en Sources: [Techno Tim]() Topics: [Server](), [Hardware](), [cpu](), [ddr5](), [intel]() Tags: [asus](), [cpu](), [ddr5](), [efficiency](), [hardware](), [homelab](), [low-power](), [monitor](), [motherboard](), [noctua](), [plex](), [pwm](), [server](), [storage]() ### AI overview A guide to building and tuning an efficient Mini ITX Plex server with processing power, storage, transcoding support, and reported power usage of 16 watts. It lists the selected hardware and explains that existing Plex servers can also be optimized for efficiency. ### Source excerpt I built an efficient, good looking, Mini ITX Plex server that doesn't skimp on the processing power, storage, or features like transcoding all while using only 16 watts of power. Each part is hand-picked and every setting is tweaked with efficiency in mind. Oh, and it would even look nice in your living space too! If you already have a Plex server, you can still follow this guide to be sure y... ## Playing audio files in a Pi Pico without a DAC DevFeed: [Playing audio files in a Pi Pico without a DAC]() Original publisher: [Read original article]() Published: 2024-03-06T10:52:34Z Content type: tutorial Language: en Sources: [Antirez]() Topics: [Microcontroller](), [MicroPython](), [Hardware](), [Software]() Tags: [audio](), [devices](), [embedded](), [mcu](), [micropython](), [pwm]() ### AI overview A tutorial explores playing audio files on a Raspberry Pi Pico without a DAC. It introduces PWM-generated sound, notes the limitations of square waves, and moves toward generating more complex waveforms for WAV playback. ### Source excerpt The Raspberry Pico is suddenly becoming my preferred chip for embedded development. It is well made, durable hardware, with a ton of features that appear designed with smartness and passion (the state machines driving the GPIOs are a killer feature!). Its main weakness, the lack of connectivity, is now resolved by the W variant. The data sheet is excellent and documents every aspect of the chip. Moreover, it is well supported by MicroPython (which I'm using a lot), and the C SDK environment is decent, even if full of useless complexities like today fashion demands: a cmake build system that in turn generates a Makefile, files to define this and that (used libraries, debug outputs, ...), and in general a huge overkill for the goal of compiling tiny programs for tiny devices. No, it's worse than that: all this complexity to generate programs for a FIXED hardware with a fixed set of features (if not for the W / non-W variant). Enough with the rant about how much today software sucks, but it must be remembered. One of the cool things one wants to do with an MCU like that, is generating some sound. The most obvious way to do this is using the built-in PWM feature of the chip. The GPIOs can be configured to just alterante between zero and one at the desired frequency, like that: from machine import Pin, PWM pwm = PWM(Pin(1)) pwm.freq(400) pwm.duty_u16(1000) Assuming you connected a piezo to GND and pin 1 of your Pico, you will hear a square wave sound at 400hz of frequency. Now, there are little sounds as terrible to hear as square waves. Maybe we can do better. I'll skip all the intermediate steps here, like producing a sin wave, and directly jump to playing a wav file. Once you see how to do that, you can easily generate your own other waves (sin, noise, envelops for such waveforms and so forth). Now you are likely asking yourself: how can I generate the complex wave forms to play a wav file, if the Pico can only switch the pin high or low? A proper non square waveform is ## Turing Pi 2 Supports Raspberry Pi Compute Modules and NVIDIA Jetson Boards DevFeed: [Turing Pi 2 Supports Raspberry Pi Compute Modules and NVIDIA Jetson Boards]() Original publisher: [Read original article]() Author: Techno Tim Published: 2022-01-01T13:00:00Z Content type: article Language: en Sources: [Techno Tim]() Topics: [Hardware](), [Raspberry Pi](), [Jetson](), [Nvidia](), [Artificial Intelligence](), [Machine learning](), [Homelab]() Tags: [ai](), [arm](), [hardware](), [homelab](), [jetson](), [ml](), [noctua](), [nvidia](), [pwm](), [raspberry-pi](), [raspberry-pi-compute-module](), [samsung]() ### AI overview The article introduces the Turing Pi 2, a compact ARM cluster designed for scalable edge computing. It describes its 32GB of RAM, SATA III interface, support for Raspberry Pi Compute Module 4 and NVIDIA Jetson boards, and the ability to combine Raspberry Pi and Jetson systems for general compute, AI, and machine-learning workloads. ### Source excerpt The Turing Pi 2 is a compact ARM cluster that provides a scalable computing on the edge.The Turning Pi 2 comes with many improvements over the Turning Pi 1.This model ships with 32GB of RAM, SATA III interface, Raspberry Pi Compute module 4 support, and support for NVIDIA Jetson boards.This means that you can mix and match both raspberry Pis along with Nvidia Jetson boards. This gives us a ton ... ## GPIO port for Raspberry Pi DevFeed: [GPIO port for Raspberry Pi]() Original publisher: [Read original article]() Author: Nenad Rakocevic (noreply@blogger.com) Published: 2019-07-18T16:08:00Z Content type: release Language: en Sources: [Red]() Topics: [Raspberry Pi](), [Hardware](), [API](), [Code](), [Software](), [GTK]() Tags: [3](), [api](), [code](), [dsl](), [gpio](), [hardware](), [led](), [port](), [pwm](), [raspberry-pi](), [raspberrypi]() ### AI overview The article announces a GPIO driver for Raspberry Pi boards implemented as Red's gpio:// scheme. It describes board detection, GPIO state access, hardware PWM, and a command DSL, and demonstrates the functionality with a joypad project running on a Raspberry Pi 3. ### Source excerpt As part of the R&D work on port! datatype in port-type branch, we have implemented a GPIO driver for Raspberry Pi boards, as a gpio:// scheme (no third-party library needed). This work helped define the low-level API for ports written in purely Red/System or a mix of Red and Red/System. The Raspberry Pi is a very popular board with millions of units sold, so this is a market where Red could be potentially helpful to developers. We could run Red on such boards for years but did not have proper GPIO support, so this is now fixed! The current features supported by the GPIO port are: auto-detecting the Raspberry Pi board type uses /dev/mem or/dev/gpiomem for direct and fast access. reading a GPIO pin state. writing to a GPIO pin state. hardware PWM output support (on capable pins). a simple DSL for sending commands. Planned (but not scheduled) future features include: generating events when a pin state changes. software PWM on all GPIO pins. a higher-level reactive object layer for a API-less interface. various drivers for common peripherals. The source code for the gpio:// scheme can be found there. In the short video below, you can find a little pet project meant for testing some of the features. It implements a simple joypad with 4 directions support, a red LED indicating when the pad is active and a green one for notifying when a level is completed. The game is the Red port contributed by Huang Yongzhao of Rebox!, my old clone of BoxWorld written in Rebol. In the video below, it is running on a Raspberry Pi 3 using our work-in-progress red/GTK backend for Red (contributed by Rcqls), locally merged with the red/port-type development branch (EDIT: that branch has been merged into master now). You can find the breadboard layout below made using Fritzing. Sorry for the messy wiring, it is my first try with such kind of tool. If you have the skills to improve it, here is the sketch file. The buttons rely on the internal pull-down resistors. Note that in the video, the bo ## Android Things: first look DevFeed: [Android Things: first look]() Original publisher: [Read original article]() Author: Marc Plano-Lesay Published: 2017-01-06T09:55:08Z Content type: tutorial Language: en Sources: [Marc Plano-Lesay]() Topics: [Android](), [Internet of things](), [Hardware](), [Raspberry Pi](), [intel](), [SDKs](), [API](), [Android Studio]() Tags: [adb](), [android](), [android-studio](), [framework](), [gpio](), [hardware](), [i2c](), [intel](), [iot](), [optional](), [preview](), [pwm](), [raspberry-pi](), [sdk](), [spi](), [ui]() ### AI overview This article introduces Android Things, an Android version for developing embedded IoT devices. It describes supported boards, the Peripheral I/O and User Driver APIs, limitations of the bundled Android system, optional displays, installation on physical hardware, and initial project setup with Android Studio and adb. ### Source excerpt What is Android Things? Android Things is an alternative Android version, announced at Google I/O 2015, and released as a first developer preview in December 2016. Its purpose is to develop embedded IoT devices, with a known and widely documented Android ecosystem basis. It's currently running on three different boards: the Intel Edison, the NXP Pico i.MX6UL, and the Raspberry Pi 3. Some higher-end boards are coming soon. On the SDK side, Android Things comes with a specific support library to ease low-level hardware usage. It consists in two parts: the Peripheral I/O API, which supports GPIO, PWM, I2C, SPI and UART, and the User Driver API, which allows a developer to write a hardware-specific, high-level driver, to ease hardware reusability by injecting events into the Android framework. Other applications can in turn use those events without having to interact with the hardware directly. There's a downside: the bundled Android is not as complete as the one you can find on a phone. Most of the standard applications aren't installed (Calendar, Phone...), and standard content providers are absent too (MediaProvider, Dictionary...). Android Things supports displays, with the default Android UI toolkit. However, the display is a bit different from what you're used to seeing on an Android device: there's no notification bar, navigation bar or anything, the running application will use the full display. That is, if it uses it at all: displays are purely optional.