Do, Done.

AI POWERED TO-DO APP

Native iOS to-do list app using Natural Language Recognition AI.

When you add a new item it’s text is scanned with Language Recognising Engine which searches for verbs/nouns in the input text.

Found noun/verb is then used as a search text for images via Pixabay API - as soon a image is found and downloaded successfully it will display next to the to-do item in the list - this is subject to your network availability.

Note that nouns found in input item text are always preferred to verbs while searching for images.

APP RECOGNISES YOUR TO-DO ITEMS ✔

To-do list app using natural language recognition to find verbs and nouns in your input item which it then uses to find and download custom image to your to-do item.

POWER OF ARTIFICIAL INTELLIGENCE 💡

App downloads custom images to show next to your to-do items -> i.e. if you add an item called "buy a car" the app will find a noun “car”, search for an image of a car and attempt to download it in order to show next to your to-do item.

App also caches all your items so no need to worry to lose your to-do list!

You will need a stable internet connection in order for the app to able to find and download images.

All images are downloaded from Pixabay.

TECH USED TO DEVELOP 👨‍💻

Written in Objective-c
Used MVVM architectural pattern
Using Realm database to store and query to-do items - using cocoapods dependency manager
Screens are modular and can be reused in any context
Using Realm database to store and query to-do items
Using Natural Language recognition native framework to add custom images to to-do items (NLTagger) How does that work? i.e. if you add an item called "buy a car" the app tries to fetch and show an image of a car besides to-do item.
Using Pixabay public REST API to download image with a search term retrieved from Natural Language Recognition framework
Added a few unit tests to cover Realm and Natural Language Recognition

UX 📱