Situation awareness application

This thesis describes the design and implementation of a situation awareness application. The application gathers data from sensors including accelerometers for monitoring earthquakes, carbon monoxide sensors for monitoring fires, radiation detectors, and dust sensors. The application also gathers Internet data sources including data about traffic congestion on daily commute routes, information about hazards, news relevant to the user of the application, and weather. The application sends the data to a Cloud computing service which aggregates data streams from multiple sites and detects anomalies. Information from the Cloud service is then displayed by the application on a tablet, computer monitor, or television screen. The situation awareness application enables almost all members of a community to remain aware of critical changes in their environments.

Community sense and response systems

The proliferation of smartphones and other internet-enabled, sensor-equipped consumer devices enables us to sense and act upon the physical environment in unprecedented ways. This thesis considers Community Sense-and-Response (CSR) systems, a new class of web application for acting on sensory data gathered from participants' personal smart devices. The thesis describes how rare events can be reliably detected using a decentralized anomaly detection architecture that performs client-side anomaly detection and server-side event detection. After analyzing this decentralized anomaly detection approach, the thesis describes how weak but spatially structured events can be detected, despite significant noise, when the events have a sparse representation in an alternative basis. Finally, the thesis describes how the statistical models needed for client-side anomaly detection may be learned efficiently, using limited space, via coresets.

The Caltech Community Seismic Network (CSN) is a prototypical example of a CSR system that harnesses accelerometers in volunteers' smartphones and consumer electronics. Using CSN, this thesis presents the systems and algorithmic techniques to design, build and evaluate a scalable network for real-time awareness of spatial phenomena such as dangerous earthquakes.