Improving Traffic Safety With a Crowdsourced Traffic Violation Reporting App

KAIST, 4/10/2017

Professor Uichin Lee and a research team at KAIST have developed and tested an app called Mobile Roadwatch. Mobile Roadwatch is a crowdsourced app that helps drivers record traffic violations with their phones and report them to the police. Professor Lee and his team aim to provide a safer way to capture and report traffic violations while operating a vehicle, in hopes that the reports will improve public safety.

Google Uses Neural Networks to Translate Without Transcribing

New Scientist, 4/4/2017

Researchers at Google Brain are developing a method to translate speech in one language to text in a different language, using neural networks. They hope to improve over more conventional automatic methods, where the speech is transcribed into written text, and then the written text is translated. The older method can be cumbersome, and initial experiments show that direct speech-to-text translation seems less subject to error. The new method could especially help speakers of rare languages communicate with others around the globe.

AncestryAI Algorithm Traces Your Family Tree Back More Than 300 Years

Aalto University, 3/16/2017

An Aalto University graduate student is developing a new family-tree algorithm called AncestryAI that uses Finnish parish registers to generate a probable family tree. Register data comes from HisKi, an open genealogical database supported by volunteer data entry. AncestryAI users can leave feedback on the accuracy of their tree, which is used to further train the algorithm.

Google Open-Sources Show and Tell, a Model for Producing Image Captions

Venture Beat, 9/22/2016

With the help of crowdsourced data, Google AI’s image recognition algorithms are achieving greater accuracy. Objects in photographs are now more accurately described, and are interrelated with other objects in auto-generated captions. With the increase in photo-captioning accuracy, more questions arise about privacy online and on social media.

IoT Early Warning System Helps Save People From Mudslides

Network World, 08/24/2016

This article describes an early warning system for mudslides and flood in rural El Salvador that uses a mesh network of simple devices, within local villagers’ needs and cultural structures. The article can be used to highlight differences between the U.S., where a vast array of technological advances can aid in mitigating disasters, and remote areas of the world where many of the basic technologies involved, such as cell-phone networks, do not exist or are not reliable.