Embedded Systems
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News, articles, guides, analytics, projects and startups from the embedded industry.

Topics of the channel:
◽️ machine learning
◽️ internet of things
◽️ embedded software
◽️ advanced electronics
◽️ new engineering ideas

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🧑‍🚀 ESP32-based Plane Radar

Plane Radar is an open-source ESP32 firmware that transforms an ESP32-C3 with a 1.28-inch round display into a live ADS-B aircraft radar. It visualizes nearby aircraft in a sonar-style interface, showing their position, distance and flight details in real time.

Features of the project:
➡️Live ADS-B aircraft tracking
➡️Sonar-style radar display
➡️Flight context and weather
➡️Wireless OTA firmware updates

Plane Radar is a compact and easy-to-build project for aviation enthusiasts and ESP32 makers. The materials are available on ☁️ GitHub. Its combination of real-time aircraft tracking, customizable firmware and convenient wireless updates makes it an appealing choice for anyone interested in embedded hardware or flight monitoring.

⛓ More information...

#projects #esp32
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💻 Barely Adequate Browser ESP32

Babe32 is a lightweight text-based web browser for ESP32-S3 touchscreen boards such as the Cheap Black Display. It renders a subset of HTML with 🇳🇱 LVGL library, supports optional image loading, and focuses on practical browsing without JavaScript.

Features of the project:
➡️Direct browsing with proxy fallback
➡️HTML rendering and forms
➡️Touchscreen navigation and keyboard
➡️WiFi, history and power management

Babe32 delivers a surprisingly capable browsing experience on inexpensive ESP32 hardware while remaining lightweight and resource-conscious.

More information:
🔗 The main article
😹 The GitHub repository

#projects #esp32 #lvgl
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🧠 Qapla': Training AI on ESP32 microcontroller

Qapla' is an open-source project that demonstrates training a transformer model entirely from scratch on an inexpensive ESP32-S3 microcontroller.

Instead of running a pre-trained model, it performs the complete training process—including backpropagation and weight updates—directly on the device.

Features of the project:
➡️Full on-device transformer training
➡️Handwritten C backpropagation
➡️No pre-trained model required
➡️Open and reproducible setup

Qapla' proves that even low-cost microcontrollers can train small transformer models without GPUs or cloud infrastructure. It is an interesting project for embedded AI developers, TinyML enthusiasts, and researchers exploring on-device learning under extreme hardware constraints.

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#projects #esp32 #artificial_intelligence
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🤖 Impulse - Open-Source Two-Wheeled Bipedal Robot

Developed from the scratch, this project explores a compact robotic platform that combines two-legged articulation with wheeled locomotion. The design prioritizes stability, responsive movement, adjustable height, and portability.

Features of the project:
➡️Self-balancing PID control
➡️Automatic deployment and landing
➡️Variable-height legs
➡️Fully 3D-printed construction

The project combines mechanical design with a compact electronics and control system built around a Teensy 4.1, ODrive motor controllers, magnetic encoders, an IMU, and CAN bus communication. Its 6-DOF structure and multiple PID controllers enable stable balancing, velocity control, and dynamic leg adjustment.

Impulse is particularly interesting for robotics enthusiasts and makers exploring balancing robots, actuator control, and practical control theory. Its detailed hardware and control approach also make it a useful reference for people building their own wheeled robots.

More information:
🔗 The main article
📥 Source files

#projects #robots
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📱📱 Samsung Raises Advanced Chip Prices as AI Demand Surges

Samsung has raised prices for new orders on its 4nm, 5nm and 8nm foundry processes, with increases of up to 15% for some customers in China and the U.S., according to Reuters. The biggest hikes are reportedly affecting Chinese chip designers, while Samsung’s 4nm facility in Pyeongtaek has been operating at full capacity since late last year as AI-related demand continues to grow.

The price increases could help Samsung’s loss-making foundry business move toward profitability as demand for advanced chips remains strong and competitors such as TSMC also raise prices. Samsung’s foundry business still trails TSMC significantly in market share, but growing orders from companies including Tesla, Apple, Broadcom and Nvidia are strengthening its position.

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#news #semiconductors
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Embedded Systems
🇨🇳 Espressif Unveils ESP32-S31: A Feature-Rich Next-Gen Wireless SoC Espressif announces the ESP32-S31, a new high-performance System-on-Chip designed for advanced IoT devices. The chip combines modern connectivity, processing power, and multimedia support…
🐧 Linux Comes to ESP32-S31

The Chinese company 🇨🇳 Espressif Systems has released a developer preview of its Linux BSP for the 🇳🇱 ESP32-S31, bringing Linux support to the dual-core RISC-V microprocessor. The chip’s MMU and 16MB of PSRAM make running a minimal Linux system possible, while the official Board Support Package (BSP) uses Buildroot and a Linux 6.18-based kernel. Those are available on ☁️ this GitHub repository.

The BSP is currently intended for experimentation rather than production, with limited features, possible breaking changes, and irregular updates. Meanwhile, community developers are also working on Linux ports for the ESP32-S31, with projects exploring newer kernels and features such as Wi-Fi, Bluetooth, and dual-core support.

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#news #esp32 #linux
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🤖 Open-Source Humanoid Breaks 400m Record

Robot “Tiangong” made headlines at the 2nd World Humanoid Robot Games in Beijing by completing the 400m race in 38.15 seconds, beating the previous human world record of 43.03 seconds. The robot is part of China’s state-backed X-Humanoid program and is built as a platform for advancing humanoid robotics, with its latest version featuring 43 degrees of freedom and high-dynamic movement control.

A notable part of Tiangong’s development is that some of its technology is open source. X-Humanoid has released components including 😹 locomotion-control software, robot models, training tools and large robotics datasets, allowing researchers and other developers to build on its technology.

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#news #robots
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🚦 Open-Source UV Protection Amulet

The UV Protection Amulet is a hardware/firmware project built around a compact electronic pendant that detects and warns about ultraviolet radiation. The project combines custom PCB design, embedded electronics, and precision-machined metalwork in a highly compact device.

Features of the project:
➡️Ultraviolet radiation detection
➡️Custom PCB hardware design
➡️Precision-machined metal enclosure
➡️Open-source firmware and CAD

The project is a compelling example of small-scale hardware engineering, showing how electronics, mechanical fabrication, and embedded software can be integrated into a functional wearable device. It may be especially interesting to hardware makers, electronics enthusiasts, and engineers exploring compact custom devices.

More information:
🔗 The main article
😹 The GitHub repository
📺 The YouTube video

#projects
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📊 Report: Inside the $585 billion embedded systems market

The embedded systems market was worth an estimated $585 billion in 2025 and is forecast to reach about $857 billion by 2032. Automotive, mobility, industrial, and robotics applications account for more than half of demand, while embedded systems also support billions of connected IoT devices.

Development is becoming faster and more flexible through unified toolchains, coding agents, and virtual hardware that allows software to be tested before physical boards are available. At the same time, memory capacity, bandwidth, availability, and cost can limit performance; new silicon can be difficult to integrate into existing development environments; and connected products require security updates, vulnerability management, and compliance throughout their operational lifetime.

Overall, embedded systems are becoming more intelligent, connected, and complex, creating new possibilities while increasing engineering demands. The report therefore emphasizes system-level decisions, where hardware, memory, software, development tools, deployment, and security need to be considered together rather than separately.

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#articles
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🧠 AI Image Generation on an RP2350 Microcontroller

This project brings generative AI image generation to a $1 RP2350 microcontroller, as used in the 🍓 Raspberry Pi Pico 2. Its compact model and inference code fit within 4 MB and run using 520 KB of RAM, generating 128×128 RGB face images in roughly 10–20 seconds.

Features of the project:
➡️Latent flow diffusion transformer
➡️Five-class conditional generation
➡️Int8 post-training quantization
➡️VGA and USB output

The project demonstrates how far generative AI can be pushed on extremely constrained hardware, combining model compression with a highly optimized inference engine. The source code is available on the dedicated 😹 GitHub repository alongside with examples.

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#project #raspberry #artificial_intelligence
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🧠 Robots Get a Sense of Touch

Robots are getting better at complex tasks with vision-language-action (VLA) models, but they still struggle with precise manipulation such as inserting cables, turning keys, or handling deformable objects. Tactile sensing can provide information about force, grip, and slipping, but progress has been limited by the lack of large, diverse datasets. Recent research is addressing this gap by combining touch with vision and robot-action data.

Berkeley researchers created the T-Rex dataset with about 100 hours of tactile demonstrations involving more than 200 household objects. Another project aggregated over 3,000 hours of publicly available data covering 21 sensor types and different robot platforms. USC researchers also released a model that can infer tactile information from visual data, potentially helping researchers create more tactile training data from existing vision datasets.

Early results show that touch can significantly improve robot manipulation. In one study, tactile feedback produced a 65% average success rate across 12 tasks, nearly twice the performance of the best VLA baseline; another approach achieved 62.8% success compared with 28.2% without touch. The main challenges remain data diversity, sensor compatibility, and how robots process sparse tactile signals in real time.

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#articles #robots #artificial_intelligence
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