UC Berkeley

The emergence of pervasive sensing, high bandwidth communications and inexpensive data storage and computation systems makes it possible to drastically change how we design, monitor and regulate very large-scale physical and human networks. Even small performance gains in the way we operate these networks translate into large savings. There are many critical challenges to create functional monitoring systems, such as data reliability, computational efficiency and proper system design, including choices of sensors, communication protocols, and analysis approaches.

In this dissertation introduces a framework to design a monitoring system, deploy it, maintain it and process the incoming heterogeneous sources of information, resulting in new applications. The framework is applied to urban traffic monitoring and road infrastructure sensing. We develop various state of the art statistical inference algorithms, compute performance guarantees and study some of the fundamental limits of the proposed ideas. We illustrate the methodology using experimental deployments we have built and are currently in use.