ML on Mobile

Android & WearOS | iOS & watchOS & visionOS | Web & IoT (Rust)

Machine Learning on Mobile

HummingBird Fuel

This AI-powered mobile app utilizes machine learning to analyze health data and recommend personalized microdosing schedules for medication. This has the potential to optimize medication effectiveness while minimizing side effects. Our initial focus is on using caffeine for targeted energy boosts.

Website: https://www.hummingbirdfuel.com/

Photodo

This AI-powered to-do app lives conveniently on your phone. Simply capture a photo, record a voice memo, or take a note, and Photodo's intelligent assistant swings into action. It identifies the task, sets deadlines, locates nearby assistance, and even tracks your budget. It's like having a personal AI assistant in your pocket. (Android)

Article: https://zoewave.medium.com/ai-powered-todo-app-163172f20421

DrunkWatch

This innovative system leverages your smartwatch to assess your intoxication level and determine your driving suitability. It analyzes your walking patterns, writing style (when entering a code), and bio-sensor data to make this crucial call. This showcases the combined power of the iWatch's 4-core Neural Engine, accelerometer, and bio-sensors. (watchOS / iWatch10)

Website: https://www.zoewear.com/

RxDigita

Streamlining medication management, RxDigita allows you to add meds by voice or photo (the app reads the label!), set reminders, and keep track of everything in a clear and organized list view. (Android)

Website: https://www.rxdigita.com/

AshBike

This eco-friendly e-bike service leverages your fitness data (via Apple Health and Google Fit integration). Its ML capabilities help plan routes based on your calendar schedule and reward you with NFTs for choosing sustainable transportation. (Android & iOS)

Website: https:www.ashbike.com

Self-Driving LEGO® Car 

This project explores the exciting concept of creating a self-driving LEGO® car with your smartphone acting as the brains of the operation.

Design Docs:

https://zoewave.medium.com/self-driving-lego-car-concept-c3a50e72cccc

Demystifying Mobile Machine Learning

A Multi-Tool Approach

Android's & iOS ML Arsenal: Choosing the Right Tool


When it comes to Android & iOS , there's no one-size-fits-all solution for ML. 

Here's a breakdown of the key options and their ideal use cases

Android

ML Kit 

Perfect for quick integration. It offers user-friendly APIs and pre-built models for common tasks like face detection or text recognition. However, customization is limited.



Firebase ML

Seamlessly integrates with the Firebase ecosystem, providing pre-built models for specific tasks like image labeling or language translation. Similar to ML Kit, customization options are restricted.



TensorFlow (TF) Lite

If high performance and complete control are your priorities, TF Lite is the way to go. It allows you to leverage custom models, but requires a solid understanding of machine learning concepts.



MediaPipe (New)

This newcomer simplifies complex machine learning pipelines by offering a versatile and easy-to-use framework built on top of TF Lite. For developers seeking a low-code or no-code alternative to TF Lite, MediaPipe is a great option.




Gemini Nano (New)

Privacy takes center stage with Gemini Nano. This secure execution environment boasts a chat-like interface for interacting with models. However, current limitations include flexibility and device compatibility (currently only available on Pixel 8 Pro).




AI Core (New)

This hardware acceleration component complements Gemini Nano on compatible devices, further optimizing its performance.




iOS

Core ML and Create ML - A Powerful Duo
Apple's mobile ecosystem offers Core ML and Create ML for streamlined ML development on iOS:



Core ML

The core (pun intended) of on-device machine learning in iOS apps. It acts as a bridge, allowing your app to interact with various machine learning models in a unified way. These models can be used for tasks like image classification or making predictions. Core ML empowers you to run models directly on the device, enhancing speed and privacy compared to cloud-based solutions.



Create ML

This user-friendly tool streamlines the creation of custom machine learning models. Imagine it as a drag-and-drop interface where you provide your training data, and Create ML handles the model creation process. It's ideal for beginners or scenarios where complex models aren't required.


More here: https://zoewave.medium.com/ml-on-android-1ecc451625a6