diff --git a/README.md b/README.md index 2ee8e5c7e..2b3b805d9 100644 --- a/README.md +++ b/README.md @@ -1,17 +1,17 @@ # Welcome to the AI-on-the-edge-device -Artificial intelligence based systems have become established in our everyday lives. Just think of speech or image recognition. Most of the systems rely on either powerful processors or a direct connection to the cloud for doing the calculations there. With the increasing power of modern processors, the AI systems are coming closer to the end user – which is usually called **edge computing**. +Artificial intelligence-based systems have become established in our everyday lives. Just think of speech or image recognition. Most of the systems rely on either powerful processors or a direct connection to the cloud for doing the calculations there. With the increasing power of modern processors, the AI systems are coming closer to the end user, a concept known as **edge computing**. In this project, edge computing is demonstrated through a practical example, where an AI network is implemented on an ESP32 device, hence: **AI on the edge**. -This project allows you to digitize your **analog** water, gas, power and other meters using cheap and easily available hardware. +This project allows you to digitize your **analog** water, gas, power and other meters using cheap and readily available hardware. All you need is an [ESP32 board with a supported camera](https://jomjol.github.io/AI-on-the-edge-device-docs/Hardware-Compatibility/) and some practical skills. ## Key features -- Tensorflow Lite (TFlite) integration – including easy-to-use wrapper +- Tensorflow Lite (TFLite) integration – including easy-to-use wrapper - Inline image processing (feature detection, alignment, ROI extraction) - **Small** and **cheap** device (3 x 4.5 x 2 cm³, < 10 EUR) - Integrated camera and illumination @@ -45,7 +45,7 @@ There is growing [documentation](https://jomjol.github.io/AI-on-the-edge-device- There are also articles in the German Heise magazine "make:" about the setup and technical background (behind a paywall): [DIY - Setup](https://www.heise.de/select/make/2021/2/2103513300897420296) -A lot of people created useful Youtube videos which might help you getting started. +A lot of people created useful YouTube videos which might help you getting started. Here a small selection: - [youtube.com/watch?v=HKBofb1cnNc](https://www.youtube.com/watch?v=HKBofb1cnNc) @@ -62,7 +62,7 @@ For further background information, head to [Neural Networks](https://www.heise. The latest available version can be found on the [Releases page](https://github.com/jomjol/AI-on-the-edge-device/releases). ### Flashing the ESP32 -Initially you will have to flash the ESP32 via a USB connection. Later updates are possible directly over the air (OTA using WIFI). +Initially you will have to flash the ESP32 via a USB connection. Later updates are possible directly over the air (OTA using Wi-Fi). There are different ways to flash your ESP32: - The preferred way is the [Web Installer and Console](https://jomjol.github.io/AI-on-the-edge-device/index.html) which is a browser-based tool to flash the ESP32 and extract the log over USB: @@ -89,7 +89,7 @@ If you would like to support the developer with a cup of coffee, you can do that ## Support -If you have any technical problems please search the [discussions](https://github.com/jomjol/AI-on-the-edge-device/discussions). In case you found a bug or have a feature request, please open an [issue](https://github.com/jomjol/AI-on-the-edge-device/issues). +If you have any technical problems please search the [discussions](https://github.com/jomjol/AI-on-the-edge-device/discussions). In case you find a bug or have a feature request, please open an [issue](https://github.com/jomjol/AI-on-the-edge-device/issues). In other cases you can contact the developer via email: