Thursday, June 20, 2013
Ph.D. Student's Team Creates Winning Pebble App at Evernote & Honda Hackathon
Evernote and Honda recently joined together to hold their first design hackathon in Silicon Valley over the course of three days. Teams had a variety of APIs to choose from including Evernote, Honda Silicon Valley Lab (HSVL), LeapMotion, Pebble and NODE. Carnegie Mellon University Silicon Valley (CMU-SV) Ph.D. student, Le Nguyen, and his teammate, Weiyi Liu, chose to hack wtih the Pebble API and won their category for the app, BeSafe.
BeSafe is an app integrated with Pebble that allows users to share their location and audio info simply by touching a button on the Pebble watch. Especially useful in emergency situations, users can also directly call someone for help. Additionally, the app can remotely lock and locate users’ phones. Pebble is an e-paper watch that connects by Bluetooth to iPhone and Android devices.
“We came up with the idea for BeSafe as we were thinking about features that would leverage the unique capabilities offered by the Pebble watches,” explained Nguyen. “We realized that besides the convenience, these "smartwatches" allow users to perform many time-sensitive actions through just a single press of a button.”
Nguyen’s main research interest at CMU-SV is in human behavior modeling, which led him to consider smartwatches as an interesting platform for applications. “As opposed to smartphones, which people often leave behind on a desk or in a jacket, watches are typically worn on the wrist all the time,” said Nguyen. “This allows us to detect a large variety of human activities, which are essential for understanding human behavior in everyday life.”
“I'm really excited by Le and his team's success at the hackathon,” said Nguyen’s Ph.D. advisor and CMU-SV Assistant Research Professor, Dr. Joy Zhang. “His Ph.D. work on mobile sensing and behavior modeling is important because inferring information from smartphone and mobile sensors has opened doors to behavior-aware, personalized intelligent systems, limited only by our imagination.”
“Le has demonstrated what a typical CMU Ph.D. student does best: he’s submitted 4 conference papers this semester and 3 have already been accepted; he’s passed the qualification exam; he’s also released two major application systems: ProbIN for indoor positioning and Tacit Knowledge Extraction from Realworld Sensing,” explained Zhang. “Our students excel in producing research that goes the next step in real world applications.”
Pictured above (from left): Weiyi Liu, Le Nguyen