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: