This project implements a retro-style ADS-B radar display designed specifically for the ESP32 using a Cheap Yellow Display (CYD) ILI9341. It fetches aircraft data from local dump1090 instances and visualizes real-time information, including position, altitude, speed, and callsigns, on an interactive radar scope or within a tabular list.
Key features:
* Radar scope visualization featuring range rings, crosshairs, and blips for approaching aircraft.
* A detailed aircraft data table providing quick access to nearby flight info.
* Touchscreen support allowing users to cycle through large radar, split-screen, and full-table layout modes.
* Automatic identification of military aircraft via red color highlighting.
* Highly optimized for MicroPython on ESP32 hardware using specific CYD libraries.
Key features:
* Radar scope visualization featuring range rings, crosshairs, and blips for approaching aircraft.
* A detailed aircraft data table providing quick access to nearby flight info.
* Touchscreen support allowing users to cycle through large radar, split-screen, and full-table layout modes.
* Automatic identification of military aircraft via red color highlighting.
* Highly optimized for MicroPython on ESP32 hardware using specific CYD libraries.
This open-source firmware is designed for the ESP32-C3 Super Mini and a 1.28 inch GC9A01 round display to create a sonar-style aircraft radar. It visualizes live ADS-B data on a circular grid, showing flight paths, detailed aircraft models, altitude, and speed.
- Real-time tracking using adsb.fi for aircraft positions
- Route enrichment through ADSBDB for origin/destination info
- Integrated weather display via Open-Meteo and local time via NTP
- Web-based Wi-Fi setup portal for location and setting configuration
- Support for authenticated OTA firmware updates
- Real-time tracking using adsb.fi for aircraft positions
- Route enrichment through ADSBDB for origin/destination info
- Integrated weather display via Open-Meteo and local time via NTP
- Web-based Wi-Fi setup portal for location and setting configuration
- Support for authenticated OTA firmware updates
Building an affordable Home Assistant dashboard does not require expensive hardware. This guide explores several low-cost methods to create functional control panels and information displays using existing or cheap equipment.
Ways to build a budget dashboard include:
* Repurposing old tablets, phones, or even Kindles from your junk drawer using kiosk browsers or the Home Assistant companion app.
* Purchasing second-hand hardware like older tablets or digital photo frames through online marketplaces.
* Using small ESP32 touchscreen modules for low-power desktop dashboards.
* Implementing E-Ink displays for minimal, always-on information such as weather and calendars.
* Jailbreaking used smart displays to bypass manufacturer limitations and run custom software.
Ways to build a budget dashboard include:
* Repurposing old tablets, phones, or even Kindles from your junk drawer using kiosk browsers or the Home Assistant companion app.
* Purchasing second-hand hardware like older tablets or digital photo frames through online marketplaces.
* Using small ESP32 touchscreen modules for low-power desktop dashboards.
* Implementing E-Ink displays for minimal, always-on information such as weather and calendars.
* Jailbreaking used smart displays to bypass manufacturer limitations and run custom software.
CrowPanel Advanced 10.1-inch HMI Display Overview
This AI terminal uses dual-core ESP32-P4 RISC-V and ESP32-C6 wireless architecture. It is designed for industrial automation and smart home control.
* Dual-core processor with AI acceleration and up to 32MB PSRAM
* 10.1-inch IPS capacitive touchscreen (1024x600)
* Wi-Fi 6, Bluetooth 5.3, and replaceable modules for Zigbee or LoRa
* Facial recognition via integrated camera interface
* Voice interaction with microphone array and dual speakers
* Compatible with Arduino IDE, ESP-IDF, and LVGL
This AI terminal uses dual-core ESP32-P4 RISC-V and ESP32-C6 wireless architecture. It is designed for industrial automation and smart home control.
* Dual-core processor with AI acceleration and up to 32MB PSRAM
* 10.1-inch IPS capacitive touchscreen (1024x600)
* Wi-Fi 6, Bluetooth 5.3, and replaceable modules for Zigbee or LoRa
* Facial recognition via integrated camera interface
* Voice interaction with microphone array and dual speakers
* Compatible with Arduino IDE, ESP-IDF, and LVGL
ESP-Claw is an AI agent framework by Espressif that enables ESP32 series chips to function as active decision-making centers rather than passive executors. It implements a full intelligence loop involving sensing, reasoning, and execution locally on edge hardware. Through conversational programming via chat interfaces, users can define device behaviors using dynamic Lua loading without traditional coding expertise.
- Event-driven architecture with millisecond response times
- Structured memory management that prioritizes privacy by keeping data off the cloud
- MCP communication support allowing devices to act as both a client and a server
- Broad compatibility with various LLM APIs including OpenAI, Anthropic, Qwen, and DeepSeek
- Support for multiple development boards via web-based flashing or local builds
- Event-driven architecture with millisecond response times
- Structured memory management that prioritizes privacy by keeping data off the cloud
- MCP communication support allowing devices to act as both a client and a server
- Broad compatibility with various LLM APIs including OpenAI, Anthropic, Qwen, and DeepSeek
- Support for multiple development boards via web-based flashing or local builds
A wireless 24GHz mmWave motion tracking system consisting of a standalone radar node that reports detected targets over Wi-Fi to a separate display unit.
Key details:
- Multi-target tracking for up to 3 people within a 7m range
- Live radar-style visualization on an Arduino GIGA Display Shield
- Distance-reactive audio alerts via a passive piezo buzzer
- Battery-powered operation with USB-C recharging and LED level indicators
- Includes 3D-printable enclosure files and full firmware for the XIAO ESP32-S3 and GIGA R1
Key details:
- Multi-target tracking for up to 3 people within a 7m range
- Live radar-style visualization on an Arduino GIGA Display Shield
- Distance-reactive audio alerts via a passive piezo buzzer
- Battery-powered operation with USB-C recharging and LED level indicators
- Includes 3D-printable enclosure files and full firmware for the XIAO ESP32-S3 and GIGA R1
This project is an ESP32-based ADSB tracker that provides a real-time flight radar display similar to FlightRadar24 on a small round TFT screen. It displays aircraft positions, trails, and local airport markers using data from sources like ADSB.lol or OpenSky. The system includes advanced visual features such as auto zoom cycling, decorative day/night sky layers with sun and moon calculations based on solar math, and optional GPS support for localized tracking.
- ESP32 DevKit V1 compatibility with Waveshare 1.28 inch GC9A01 round TFT display
- WiFiManager integration for easy network configuration
- Real-time aircraft trails and deconfliction to reduce visual clutter near airports
- Dynamic zoom cycling from 25 km to 250 km range
- Local solar math for sun position and moon phase rendering
- Optional TinyGPSPlus support for live location coordinates
- ESP32 DevKit V1 compatibility with Waveshare 1.28 inch GC9A01 round TFT display
- WiFiManager integration for easy network configuration
- Real-time aircraft trails and deconfliction to reduce visual clutter near airports
- Dynamic zoom cycling from 25 km to 250 km range
- Local solar math for sun position and moon phase rendering
- Optional TinyGPSPlus support for live location coordinates
Esposito OS is a simple operating system designed for the ESP32 Cheap Yellow Display (CYD). It features dynamic application loading from an SD card and utilizes an event-driven architecture. The system follows a single-tasking, single-app model with a Palm-style lifecycle that allows apps to checkpoint and save their state.
Main points:
- Dynamic app loading via SD card filesystem
- Event-driven architecture using a central queue
- Hardware support for ESP32 CYD (2USB version) and BBQ20 keyboard
- Built on the ESP-IDF framework
Main points:
- Dynamic app loading via SD card filesystem
- Event-driven architecture using a central queue
- Hardware support for ESP32 CYD (2USB version) and BBQ20 keyboard
- Built on the ESP-IDF framework
An overview of ESPConnect, a free self-hosted web utility used to manage and flash ESP32 microcontrollers. The tool provides detailed hardware profiling for various MCU models, allows for advanced partition management, and enables flashing firmware or creating system backups through filesystem access. It also includes essential debugging features like an NVS Inspector and a Serial Monitor.
- Detailed hardware profile generation (MAC address, memory, clock speeds)
- Partition layout modification and flash backup capabilities
- File system support including SPIFFS, LittleFS, and FATFS
- Debugging via UART logs and session history tracking
- Easy deployment on Proxmox using LXC scripts
- Detailed hardware profile generation (MAC address, memory, clock speeds)
- Partition layout modification and flash backup capabilities
- File system support including SPIFFS, LittleFS, and FATFS
- Debugging via UART logs and session history tracking
- Easy deployment on Proxmox using LXC scripts
The author demonstrates how to run Espressif's ESP-Claw agent framework on an ESP32-P4 microcontroller using a self-hosted Qwen 3.6 LLM. Unlike standard TinyML implementations that only use microcontrollers for simple tasks, this setup allows the chip to manage sensing, decision-making, and tool execution through Lua scripts triggered via Telegram. The project shows how hardware behavior can be modified in real-time through chat without needing to recompile firmware.
Main topics:
* Implementation of an agent loop directly on a microcontroller
* Using Lua modules for dynamic runtime skill acquisition
* Interfacing with LLMs via OpenAI-compatible APIs
* Controlling peripherals like GPIO, I2C, and sensors through natural language
* Utilizing Telegram as the primary user interface
Main topics:
* Implementation of an agent loop directly on a microcontroller
* Using Lua modules for dynamic runtime skill acquisition
* Interfacing with LLMs via OpenAI-compatible APIs
* Controlling peripherals like GPIO, I2C, and sensors through natural language
* Utilizing Telegram as the primary user interface
