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AliOS Things Documentation

repository·master·Indexed 26 days ago

https://github.com/alibaba/alios-things

A highly scalable IoT operating system supporting ARM, RISCV, and MIPS architectures. It features a component-based architecture for applications in C++, JavaScript, or MicroPython. Key components include A2SA (Advanced AliOS Things Sound Architecture), a lightweight audio system compatible with Linux ALSA-Lib API, and an ai_agent framework that supports various reasoning engines such as ucloud-ai for tasks like OCR, object detection, and face recognition.

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What's inside AliOS Things

  1. Overview of DotZLib .NET Wrapper

    master

    DotZLib is a .NET wrapper class library for ZLib1.dll. It provides managed support for several ZLib functionalities:

    • Memory Buffers: Inflating and deflating memory buffers.
    • Streaming: .NET streaming wrappers for the gz streams part of zlib.
    • Checksums: Wrappers for the checksum components of zlib.

    For implementation examples, refer to DotZLib/UnitTests.cs.

  2. Overview of ESP-S3-12K-Kit Hardware

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    The ESP-S3-12K-Kit is a development board based on the ESP32-S3 MCU, which features a 2.4 GHz Wi-Fi and Bluetooth 5 (LE) connectivity with Long Range support. It is powered by an Xtensa® 32-bit LX7 dual-core processor running at up to 240 MHz and includes 512 KB of internal SRAM (TCM).

    Key capabilities include:

    • AI Acceleration: Supports vector instructions for accelerating neural network computations and signal processing. Developers can use the ESP-DSP and ESP-NN libraries for high-performance image recognition and voice wake-up/recognition. Support is also provided via ESP-WHO and ESP-Skainet.
    • Rich I/O: Features 45 programmable GPIOs and various communication interfaces including SPI, I2S, I2C, PWM, RMT, ADC, UART, and SD/MMC.
    • HMI Support: 14 GPIOs can be configured as capacitive touch inputs.
    • Low Power: Includes an Ultra-Low Power (ULP) coprocessor for low-power application scenarios.

  4. Overview of ucloud_ai

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    ucloud_ai is a cloud-based AI inference engine implemented via Alibaba Cloud OpenAPI. It connects to the Alibaba Cloud Visual Intelligence Open Platform to provide AI capabilities. Currently, it supports 15 types of AI models, including:

    • Face and Body Recognition
    • Expression Recognition
    • Character Animation
    • Object Detection
    • Subject Detection
    • General Segmentation
    • Face Segmentation
    • ID Card Recognition
    • Bank Card Recognition
    • OCR (Text Recognition)
    • Garbage Classification
    • Fruit Recognition
    • Image Human Erasing
    • Style Transfer

  5. Overview of Micro Speech Example

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    The Micro Speech example demonstrates how to run a small (20 kB) TensorFlow Lite Micro model that recognizes two keywords, "yes" and "no", from audio data. The application uses a microphone to listen to surroundings and indicates detection by lighting an LED or displaying data on a screen. It is designed for low-resource systems, requiring approximately 22 KB of Flash and 10 KB of RAM (e.g., suitable for an STM32F103).

  6. Overview of the POSIX component

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    The posix component provides a Portable Operating System Interface (POSIX) implementation for AliOS Things, ensuring compatibility with Unix/Linux application ecosystems.

    Supported features include:

    • pthread thread and attribute management
    • pthread condition variables and attribute management
    • pthread mutex and attribute management
    • File system interfaces
    • Environment variable management
    • POSIX semaphores
    • POSIX timers
    • POSIX message queues

  7. Overview of HaaSEDUK1 Development Board

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    HaaSEDUK1 (HaaS Education Kit1) is an IoT education development board built on the quad-core high-performance MCU-HaaS1000 chip. It serves as a hardware/software 'building block' platform for cloud-to-device full-link solutions.

    Key integrated technologies include:

    • AliOS Things IoT operating system
    • HaaS Light Applications
    • Mini Programs
    • Alibaba Cloud IoT Platform

    It is designed to help developers learn and develop full-link practical projects for real-world scenarios or innovative applications.

  9. Overview of epoll component

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    The epoll component provides a high-efficiency I/O multiplexing mechanism compatible with Linux's epoll. It supports the following scenarios:

    • Socket file descriptor (fd) event notification.
    • VFS (Virtual File System) fd event notification.
    • Mixed event notification for both sockets and VFS fds.

  10. Overview of HaaS EDU K1 scenario-based cases

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    The HaaS EDU K1 provides 10 built-in scenario-based application cases designed to teach various IoT and embedded development concepts without requiring external peripherals. These cases include:

    1. Homepage System Information Screen: OLED drivers, system version, Wi-Fi/IP/Bluetooth status, and battery level.
    2. Thermometer/Hygrometer: I2C communication, SI7006 sensor, and OLED drawing.
    3. Gyroscope Ball: MPU-6050 driver, gyroscope principles, and basic motion algorithms.
    4. Shake/Shake-Shake Machine: 3-axis accelerometer, random number generation, and jitter filtering algorithms.
    5. Electronic Compass: QMC5883L magnetic sensor, geomagnetic principles, and dynamic OLED refreshing.
    6. Light Meter: AP3216C light sensor, proximity sensor, and light/distance algorithms.
    7. Barometer/Altimeter: SPL06 pressure sensor, I2C communication, and altitude calculation algorithms.
    8. Retro Music Box: PWM, buzzer usage, music score encoding, and player development.
    9. Greedy Snake: Button event handling, game design, and scoring systems.
    10. Aircraft Battle: Vertical screen button events, OLED game design, and scoring systems.