diff --git a/FeatureRequest.md b/FeatureRequest.md index 5858a099..862bb4cc 100644 --- a/FeatureRequest.md +++ b/FeatureRequest.md @@ -2,10 +2,9 @@ **There are a lot of ideas for further improvements, but only limited capacity on side of the developer.** Therefore I have created this page as a collection of ideas. -1. Who ever has a new idea can put it here, so it that it is not forgotten. +1. Whoever has a new idea can put it here, so that it is not forgotten. -2. Who ever has time, capacity and passion to support, can take any of the ideas and implement them. - I will support and help where ever I can! +2. Whoever has the time, capacity and passion to support the project can take any of the ideas and implement them. I will provide support and help wherever I can! @@ -51,7 +50,7 @@ haveing this state in the mqtt broker can trigger functions like closing the ate #### ~~#29 Add favicon and use the hostname for the website~~- implemented v11.3.1 -~~* https://github.com/jomjol/AI-on-the-edge-device/issues/927~~ +* ~~https://github.com/jomjol/AI-on-the-edge-device/issues/927~~ #### #28 Improved error handling for ROIs @@ -89,7 +88,7 @@ haveing this state in the mqtt broker can trigger functions like closing the ate #### ~~#22 Direct hint to the different neural network files in the other repositories~~- implemented >v11.3.1 -~~* https://github.com/jomjol/AI-on-the-edge-device/issues/644~~ +* ~~https://github.com/jomjol/AI-on-the-edge-device/issues/644~~ diff --git a/README.md b/README.md index df1c8909..c03b6904 100644 --- a/README.md +++ b/README.md @@ -1,31 +1,31 @@ # Welcome to the AI-on-the-edge-device -Artificial intelligence based systems have been established in our every days live. Just think of speech or image recognition. Most of the systems relay on either powerful processors or a direct connection to the cloud for doing the calculations up there. With the increasing power of modern processors the AI systems are coming closer to the end user - which is usually called **edge computing**. -Here this edge computing is brought into a practical oriented example, where a AI network is implemented on a ESP32 device so: **AI on the edge**. +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**. +Here, this edge computing is put into a practically oriented example, where an AI network is implemented on an ESP32 device so: **AI on the edge**. -This projects allows you to digitalize your **analoge** 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 easily 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 a bit of a practical hand. +All you need is an [ESP32 board with a supported camera](https://jomjol.github.io/AI-on-the-edge-device-docs/Hardware-Compatibility/) and something of a practical hand. ## Key features -- Tensorflow Lite (TFlite) integration - including easy to use wrapper -- Inline Image processing (feature detection, alignment, ROI extraction) -- **Small** and **cheap** device (3x4.5x2 cm³, < 10 EUR) -- camera and illumination integrated -- Web surface to administrate and control -- OTA-Interface to update directly through the web interface +- 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 +- Web interface for administration and control +- OTA interface for updating directly via the web interface - Full integration into Homeassistant - Support for Influx DB 1 - MQTT - REST API ## Workflow -The device takes a photo of your meter at a defined interval. It then extracts the Regions of Interest (ROI's) out of it and runs them through an artificial inteligence. As a result, you get the digitalized value of your meter. +The device takes a photo of your meter at a defined interval. It then extracts the Regions of Interest (ROIs) from the image and runs them through artificial intelligence. As a result, you get the digitized value of your meter. -There are several options what to do with that value. Either send it to a MQTT broker, write it to an InfluxDb or simply provide it throug a REST API. +There are several options for what to do with that value. Either send it to an MQTT broker, write it to an InfluxDb or simply provide access to it via a REST API. @@ -41,62 +41,62 @@ There are several options what to do with that value. Either send it to a MQTT b ## Setup -There is a growing [documentation](https://jomjol.github.io/AI-on-the-edge-device-docs/) which provides you with a lot of information. -Head there to get a start, set it up and configure it. +There is growing [documentation](https://jomjol.github.io/AI-on-the-edge-device-docs/) which provides you with a lot of information. Head there to get a start, set it up and configure it. -There are also a articles in the German Heise magazine "make:" about the setup and the technical background (behind a paywall) : [DIY - Setup](https://www.heise.de/select/make/2021/2/2103513300897420296) +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) -For further background information, head to [Neural Networks](https://www.heise.de/select/make/2021/6/2126410443385102621), [Training Neural Networks](https://www.heise.de/select/make/2022/1/2134114065999161585) and [Programming on the ESP32](https://www.heise.de/select/make/2022/2/2204010051597422030) +For further background information, head to [Neural Networks](https://www.heise.de/select/make/2021/6/2126410443385102621), [Training Neural Networks](https://www.heise.de/select/make/2022/1/2134114065999161585) and [Programming on the ESP32](https://www.heise.de/select/make/2022/2/2204010051597422030). ### Download -The latest available version is available on the [Releases page](https://github.com/jomjol/AI-on-the-edge-device/releases). +The latest available version can be found on the [Releases page](https://github.com/jomjol/AI-on-the-edge-device/releases). -### Flashing of the ESP32 -Initially you will have to flash the ESP32 through an USB connection. Later an update is possible directly over the Air (OTA). +### Flashing the ESP32 +Initially you will have to flash the ESP32 via a USB connection. Later updates are possible directly over the air (OTA). There are different ways to flash your ESP32: -- [Web Installer and Console](https://jomjol.github.io/AI-on-the-edge-device/index.html) (Webbrowser based tool to flash the ESP32 and extract the Log over USB) +- [Web Installer and Console](https://jomjol.github.io/AI-on-the-edge-device/index.html) (Browser-based tool to flash the ESP32 and extract the log over USB) - Flash Tool from Espressif -- ESPtool (Command Line Tool) +- ESPtool (command-line tool) -See the [Docu](https://jomjol.github.io/AI-on-the-edge-device-docs/Installation/) for more information. +See the [documentation](https://jomjol.github.io/AI-on-the-edge-device-docs/Installation/) for more information. -### Flashing the SD-Card -The SD-Card must be flashed separately, see the [Docu](https://jomjol.github.io/AI-on-the-edge-device-docs/Installation/) for details. +### Flashing the SD Card +The SD card must be flashed separately, see the [documentation](https://jomjol.github.io/AI-on-the-edge-device-docs/Installation/) for details. ## Casing -A 3d-printable housing can be found here: +A 3D-printable housing can be found here: - https://www.thingiverse.com/thing:4573481 (Water Meter) - https://www.thingiverse.com/thing:5028229 (Power Meter) - https://www.thingiverse.com/thing:5224101 (Gas Meter) - - https://www.thingiverse.com/thing:4571627 (ESP32-Cam housing only) + - https://www.thingiverse.com/thing:4571627 (ESP32-cam housing only) -## Build it yourself +## Build It Yourself See [Build Instructions](code/README.md). ## Donate -If you would like to support the developer with a cup of coffee you can do that via [Paypal](https://www.paypal.com/donate?hosted_button_id=8TRSVYNYKDSWL). +If you would like to support the developer with a cup of coffee, you can do that via [PayPal](https://www.paypal.com/donate?hosted_button_id=8TRSVYNYKDSWL).
-If you have any technical topics, you can create an [Issue](https://github.com/jomjol/AI-on-the-edge-device/issues). -In other cases you can contact the developer via email: +If you have any technical problems, you can create an [Issue](https://github.com/jomjol/AI-on-the-edge-device/issues). + +In other cases you can contact the developer via email: ## Changes and History -See [Changelog](Changelog.md) +See [Changelog](Changelog.md). ## Tools * Logfile downloader and combiner (Thx to [reserve85](https://github.com/reserve85)) - * Files see ['/tools/logfile-tool'](tbd), How-to see [Docu](https://jomjol.github.io/AI-on-the-edge-device-docs/outdated--Gasmeter-Log-Downloader/) + * Files see ['/tools/logfile-tool'](tbd), how-to see [documentation](https://jomjol.github.io/AI-on-the-edge-device-docs/outdated--Gasmeter-Log-Downloader/) ## Additional Ideas -There are some ideas and feature requests which are not followed currently - mainly due to capacity reasons on side of the developer. They are collected here: [FeatureRequest.md](FeatureRequest.md) +There are some ideas and feature requests which are not currently being pursued – mainly due to capacity reasons on the part of the developer. They are collected here: [FeatureRequest.md](FeatureRequest.md). ------ diff --git a/docs/index.html b/docs/index.html index eba21381..8c553f6f 100644 --- a/docs/index.html +++ b/docs/index.html @@ -22,9 +22,9 @@