We introduce a system for sensing complex social systems with data collected from one hundred mobile phones over the course of six months. We demonstrate the ability to use standard Bluetooth-enabled mobile telephones to measure information access and use in different contexts, recognize social patterns in daily user activity, infer relationships, identify socially significant locations, and model organizational rhythms.

The study of complex social systems has traditionally been an arduous process, involving extensive surveys, interviews, ethnographic studies, or analysis of online behavior. Today, however, it is possible to use the unprecedented amount of information generated by pervasive mobile phones to provide insights into the dynamics of both individual and group behavior. Information such as continuous proximity, location, communication and activity data, has been gathered from the phones of 100 human subjects at MIT. Systematic measurements from these 100 people over the course of eight months have generated one of the largest datasets of continuous human behavior ever collected, representing over 300,000 hours of daily activity. In this thesis we describe how this data can be used to uncover regular rules and structure in behavior of both individuals and organizations, infer relationships between subjects, verify selfreport

We present a novel approach to the creation of user-generated, documentary video using a distributed network of sensorenabled video cameras and wearable on-body sensor devices. The wearable sensors are used to identify the subjects in view of the camera system and label the captured video with real-time human-centric social and physical behavioral information. With these labels, massive amounts of continually recorded video can be browsed, searched, and automatically stitched into cohesive multimedia content. This system enables naturally occurring human behavior to drive and control a multimedia content creation system in order to create video output that is understandable, informative, and/or enjoyable to its human audience. The collected sensor data is further utilized to enhance the created multimedia content such as by using the data to edit and/or generate audio score, determine appropriate pacing of edits, and control the length and type of audio and video transitions directly from the content of the captured media. We present the design of the platform, the design of the multimedia content creation application, and the evaluated results from several live runs of the complete system.