Helping Humanity with Phones and Clouds

Meeting global challenges requires informed decisions. Often, these decisions require gathering data across geographic regions over time, detecting patterns that indicate significant events, formulating best responses to an event, then executing and monitoring those responses. Such decisions are made when deploying first responses to earthquakes, providing health care to people in under-served remote areas, and monitoring natural resources. Smart phones and tablets enable acquisition of data from almost anywhere on the globe. Cloud computing, likewise, enables aggregation and analysis from anywhere on the globe. This talk describes research on applications combining phones and clouds for earthquake detection and rural health care. We show how coupling community sensing and citizen participation to phones and clouds could radically improve the way that technology serves humanity, including the less fortunate, around the globe.

Matthew Faulkner is a graduate student in Computer Science at Caltech. He received an S.B (2008) and an M.Eng. (2009) in Computer Science from MIT. His research interests are in machine learning, distributed systems, and sensor networks.

Michael Olson is a graduate student in Computer Science at Caltech. He received a B.S. (2004) in Computer Science from Carnegie Mellon. His research interests are in distributed systems, sensor networks, and event processing.