Google has announced the ten winners of the Helpful Innovation Android Develop Challenge in which developers were asked to incorporate Machine Learning, specifically TensorFlow Lite and ML Kit, into their apps.

This challenge was launched at the Android Developer Summit in November 2019 with developers being asked to suggest innovate apps that took advantage of on-device machine learning. 

In the blog post announcing the winners, Jacob Lehrbaum, Director of Developer Relations, Android reported:

We received hundreds of creative projects, and at the end of last year, picked 10 winners who each combined a strong idea and a thirst to bring it to life. Since then, we’ve been working with those winners to help turn their ideas into reality. 

In the video announcing the outcome of #AndroidDevChallenge, Stephanie Cuthbertson, Director, Android explains its rationale:

Helpful innovation is a mission and a huge focus for Google and is really about technology which meets users where you are, which helps you in what you want to get done everyday.

According Hoi Lam, Developer Advocate, ML and Android, #AndroidDevChallege connected developers from across the world who had proposed cutting-edge solutions that utilize on-device machine learning with the various domain experts within Google in order to turn their ideas into reality using tools like MLKit and TensorFlowLite.

The list below (in alphabetical order) gives an outline of each of the 10 winning apps. Although some of them are still at an early stage, they are all available for download so you can try them out for yourself: 

• AgroDoc helps farmers diagnose plant disease and make treatment plans. [Navneet Krishna; Kochi, India]
• AgriFarm helps farmers detect plant diseases and prevent major damage in fruits and vegetables such as tomatoes, corn and potatoes. [Balochisan, Pakistan]
• Eskke streamlines mobile money management for people in the Congo, letting them transfer money, pay bills, buy subscriptions and essential airtime through SMS. [David Mumbere Kathoh; Goma, Democratic Republic of Congo]
• Leepi helps students learn hand gestures and symbols for American Sign Language. [Prince Patel; Bengaluru, India]
• MixPose is a live streaming platform that gives yoga teachers and fitness professionals the opportunity to teach, track alignment, and give feedback in real-time. [Peter Ma; San Francisco, California, USA]
• Pathfinder could help people with visual impairments navigate complex situations by identifying and calculating the trajectories of objects moving in their path. [Colin Shelton; Addison, Texas, USA]
• Snore & Cough helps you identify and analyze snoring and coughing, to help provide info to users seeking assistance from a medical professional. [Ethan Fan; Mountain View, California, USA]
• Stila pairs with a wearable device, like the Fitbit wristband or a device running on Wear OS by Google to monitor and track the body’s stress levels. By monitoring stress levels over time, you have the chance to better understand and manage stress in your life. [Yingdin Wing; Munich, Germany]
• Trashly makes recycling easier. Just point the on-device camera at an item, and through object detection, the app identifies and classifies plastic and paper cups, bags, bottles, etc. [Elvin Rakhmankulov; Chicago, Illinois, USA]
• UnoDogs helps owners better support their pet’s wellness, providing customized information and fitness programs. [Chinmany Mishra; New Delhi, India]

For me, Stila is the standout app for its use of ML Kit to identify stress. Here its creator Yingdin Wing showcases it: 

According to  Lehrbaum for most of the winners of the Android Developer Challenge, this was their first foray into machine learning and he goes on to outline two key offerings from Google, which bring on-device machine learning into reach for millions of developers around the world and how they were used by some of the winning apps:

ML Kit brings Google’s on-device machine learning technologies to mobile app developers, so they can build customized and interactive experiences into their apps. This includes tools such as language translation, text recognition, object detection and more. Eskke, for instance, uses offline text recognition and barcode scanning from ML Kit so users can scan the QR code at a mobile money kiosk and quickly withdraw money. And MixPose uses ML Kit's forthcoming Pose detection API to detect each user’s yoga positions and movements, so teachers can provide feedback.

The other Google resource that many of the Android Dev Challenge winners used was TensorFlow Lite. This powerful machine learning framework can help run machine learning models on Android, iOS and IoT devices that would never normally be able to support them. Its set of tools can be used for all kinds of powerful neural network-related applications, from image detection to speech recognition, bringing the latest cutting-edge technology to the devices we carry around with us wherever we go. Trashly, for instance, uses a custom TensorFlow Lite model to report if an object is recyclable and how to recycle it.

Lehrbaum concludes the announcement of the winners with:

Helpful innovation, such as the 10 winning apps in the Android Developer Challenge, has the potential to change the way we access, use, and interpret information, making it available when we need it, where we need it most. By working with these developers focused on helpful innovation, we hope to inspire the next wave of developers to unlock what’s possible with this new technology.

More Information

Announcing the winners of the #AndroidDevChallenge, powered by on-device machine learning

ML Kit 

TensorFlow Lite

Related Articles

TensorFlow Lite For Mobiles 

TensorFlow 1.5 Includes Mobile Version 

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