Yahui Ji

Materials Ameba x 1 Waveshare 2.9inch e-Paper HAT (D) x 1 Example In this example, we use the Ameba RTL8722 module connects to a Waveshare 2.9inch e-Paper module to display a few QR codes. The display uses the flexible substrate as the base plate, with interface and a reference system design.The 2.9” active area contains 296×128 pixels and has 1-bit white/black full display capabilities. An integrated circuit contains gate buffer, source buffer, interface, timing control logic, oscillator, etc… are supplied with each panel. You may refer to the official 2.9inch e-Paper HAT (D) datasheet to know more about this module. Front view of the e-Paper Module:RTL8722 wiring diagram:Firstly, you need to open the “DisplayQR” example in “File” -> “Examples” -> “AmebaEink” -> “EinkDisplayQR”:Modify the URL in the loop() section as your wish, after that, verify and upload the code to the Ameba board. Upon successfully upload the sample code and press the reset button, a QR code generated based on the URL of your input will be shown on the E-Paper module. The QR code showing below leads to our Ameba IoT official website: Ameba ARDUINO Code Reference [1] We use Good Display GDEH029A1 2.9 Inch / 296×128 Resolution / Partial Refresh Arduino Sample Code to get the e-Paper successfully Display: http://www.good-display.com/product/201.html [2] Provide the link to how to generate a QR code on the E-paper module: https://eugeniopace.org/qrcode/arduino/eink/2019/07/01/qrcode-on-arduino.html [3] A simple library for generating QR codes in C, optimized for processing and memory-constrained systems: https://github.com/ricmoo/QRCode#data-capacities Join in the community discussions at: https://www.facebook.com/groups/amebaioten https://forum.amebaiot.com/ Purchase links for the various Realtek development boards can be found at: https://www.amebaiot.com/en/where-to-buy-link/

Materials • Ameba D [RTL8722 CSM/DM] x 1 • Adafruit PDM MEMS microphone • LED x 4 Example Procedure Connect the microphone and LEDs to the RTL8722 board following the diagram. Download the Ameba customized version of TensorFlow Lite for Microcontrollers library at ambd_arduino/Arduino_zip_libraries at master · ambiot/ambd_arduino. Follow the instructions at Arduino - Libraries to install it. Ensure that the patch files found at ambd_arduino/Ameba_misc at master · ambiot/ambd_arduino are also installed. Open the example, “Files” -> “Examples” -> “TensorFlowLite_Ameba” -> “micro_speech”. Upload the code and press the reset button on Ameba once the upload is finished. Once it is running, you should see one of the LEDs flashing, indicating that it is processing audio. Saying the word “yes” will cause the green LED to light up. Saying the word “no” will cause the red LED to light up. If the word is not recognized, the blue LED will to light up. The inference results are also output to the Arduino serial monitor, which appear as follows: If you are having trouble in getting the words recognized, here are some tips: – Ensure that your surroundings are quiet with minimal noise. – Experiment with varying the distance of the microphone, starting with it at an arm’s length. – Experiment with different tones and volume when saying the words. – Depending on how you pronounce the words, the characteristics of the microphone used, getting one keyword recognized may be easier than the other. Code Reference More information on TensorFlow Lite for Microcontrollers can be found at: TensorFlow Lite for Microcontrollers Join in the community discussions at: Ameba IoT Forum[RTL8722/RTL8195/RTL8710/...] Realtek Ameba IOT Developers Forum (RTL8722, RTL8195, RTL8710, RTL8720, BW16 Development board) - IOT / MCU Solutions 瑞昱開發者論壇 開發板 开發者论坛 开發板 Purchase links for the various Realtek development boards can be found at: Buy Ameba Boards – Realtek IoT/Wi-Fi MCU Solutions

Materials • Ameba D [RTL8722 CSM/DM] x 1 • Adafruit LSM9DS1 accelerometer • LED x 2 Example Procedure Connect the accelerometer and LEDs to the RTL8722 board following the diagram. Download the Ameba customized version of TensorFlow Lite for Microcontrollers library at ambiot/ambd_arduino. Follow the instructions at Arduino - Libraries to install it. Ensure that the patch files found at ambiot/ambd_arduino are also installed. In the Arduino IDE library manager, install the Arduino_LSM9DS1 library. This example has been tested with version 1.1.0 of the LSM9DS1 library. Open the example, “Files” -> “Examples” -> “TensorFlowLite_Ameba” -> “magic_wand”. Upload the code and press the reset button on Ameba once the upload is finished. Holding the accelerometer steady, with the positive x-axis pointing to the right and the positive z-axis pointing upwards, move it following the shapes as shown, moving it in a smooth motion over 1 to 2 seconds, avoiding any sharp movements. If the movement is recognised by the Tensorflow Lite model, you should see the same shape output to the Arduino serial monitor. Different LEDs will light up corresponding to different recognized gestures. Note that the wing shape is easy to achieve, while the slope and ring shapes tend to be harder to get right. Find out more at: https://www.amebaiot.com/en/amebad-micropython-periodical-timer/ Join in the community discussions at: https://www.facebook.com/groups/amebaioten https://forum.amebaiot.com/ Purchase links for the various Realtek development boards can be found at: https://www.amebaiot.com/en/where-to-buy-link/

Introduction to Google TensorFlow TensorFlow (TF) is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML, and developers easily build and deploy ML-powered applications. While TensorFlow Lite (TFL) for Microcontrollers is designed to run machine learning models on microcontrollers and other devices with only a few kilobytes of memory. The core runtime just fits in 16 KB on an Arm Cortex M3 and can run many basic models. It doesn't require operating system support, any standard C or C++ libraries, or dynamic memory allocation. Ameba and TensorFlow Lite TFL Ameba is an easy-to-program platform for developing all kinds of IoT applications. AmebaD is equipped with various peripheral interfaces, including WiFi, GPIO INT, I2C, UART, SPI, PWM, ADC. Through these interfaces, AmebaD can connect with electronic components such as LED, switches, manometer, hygrometer, PM2.5 dust sensors, …etc. Hello World Example Running on Ameba RTL8722DM The materials we are going to prepare only requires: 1 x Ameba D RTL8722DM or RTL8722DM-mini, and 1 x LED. Example Guide Download the Ameba customized version of TensorFlow Lite for Microcontrollers library at ambiot/ambd_arduino. Follow the instructions at Arduino - Libraries to install it. Ensure that the patch files found at ambiot/ambd_arduino are also installed. Open the example, “Files” -> “Examples” -> “TensorFlowLite_Ameba” -> “hello_world”. Upload the code and press the reset button on Ameba once the upload is finished. Connect the LED to digital pin 10 and ground, ensuring that the polarity is correct. You should see the LED fade in and out rapidly. In the Arduino serial plotter, you can see the output value of the Tensorflow model plotted as a graph, it should resemble a sine wave. References You can train your model with google collab by following this weblink: Google Colaboratory Code Reference More information on TensorFlow Lite for Microcontrollers can be found at TensorFlow Lite for Microcontrollers Find out more at: Ameba MicroPython: [RTL8722CSM] [RTL8722DM] Timer – Periodical timer – Realtek IoT/Wi-Fi MCU Solutions www.amebaiot.com Join in the community discussions at: Ameba IoT Forum[RTL8722/RTL8195/RTL8710/...] Share anything about Realtek Ameba or IoT information. Official website: http://www.amebaiot.com/en/ Forum: forum.amebaiot.com 分享 Ameba RTL8722/RTL8195/RTL8710/... 相關資訊及 Maker 的大小事，一同促進 IoT 產業的發展... www.facebook.com Realtek Ameba IOT Developers Forum (RTL8722, RTL8195, RTL8710, RTL8720, BW16 Development board) - IOT / MCU Solutions 瑞昱開發者論壇 開發板 开發者论坛 开發板 Discuss anything about Ameba RTL8722 RTL8195 RTL8710, RTL8720, BW16 Development board or IOT / MCU Solutions forum.amebaiot.com Purchase links for the various Realtek development boards can be found at: Buy Ameba Boards – Realtek IoT/Wi-Fi MCU Solutions www.amebaiot.com

Here we introduce another way to download firmware to your microcontroller board. With a BLE5.0 & Dual-band WiFi microcontroller, you will never have to worry about re-compiling the code just to change the WiFi SSID and password. Write an introduction for your project How does it work? The working principle of BLE5.0 is working as follows: the Ameba RTL8722DM board will send BLE information to your phone; the phone will send the corresponding WiFi configuration including SSID and password to the RTL8722DM board; the board is able to connect to the WiFi with the same SSID as your phone; #include "BLEDevice.h" #include "BLEWifiConfigService.h" BLEWifiConfigService configService; void setup() { Serial.begin(115200); BLE.init(); BLE.configServer(1); configService.addService(); configService.begin(); // Wifi config service requires a specific advertisement format to be recognised by the app // The advertisement needs the local BT address, which can only be obtained after starting peripheral mode // Thus, we stop advertising to update the advert data, wait for advertising to stop, then restart advertising with new data BLE.beginPeripheral(); BLE.configAdvert()->stopAdv(); BLE.configAdvert()->setAdvData(configService.advData()); BLE.configAdvert()->updateAdvertParams(); delay(100); BLE.configAdvert()->startAdv(); } void loop() { delay(1000); }

This video demonstrates how Ameba RTL8722 Mini supports TensorFlow Lite. Product Links: https://www.amebaiot.com/en/where-to-buy-link/#buy_amb21