Today’s New York Times carries a fascinating study on how large numbers of users walking around with mobile phones, constituting a cheap sensor network. Urban planners, technology companies and officials from local governments see potential in projects like these that mine data collected from phones to provide better public services. Boston is developing a system called Street Bump that uses a smartphone’s accelerometer and GPS system to detect when a driver hits a pothole and then sends that information to city officials. Techniques like this may help cities collect data that until recently would have required expensive network sensors.
“Leptospirosis is out and Dengue is in” – these are the words of the Sarvodaya Research Assistant – Pubudini weerakoon – working in Kurunegala District of Sri Lanka on the real-time biosurveillance program (RTBP). This report on Leptospirosis in Sri Lanka gives a full account of the past events. The aim of the RTBP is to gather patient case information through the m-Healthsurvey mobile application and subject that data to real time analysis for rapid detection of emerging health events. The automated analytic and detection is driven by the T-Cube software, developed by Carnegie Mellon Universities Auton Lab, based on data mining principles. We took the weekly epidemiological reports (WER) from the past two years and put T-Cube to the test.