Modular risk modeling and management of water infrastructure disaster incidents

Water supply and wastewater control are critical elements of society's infrastructure. The objective of this study will be to provide a generic risk assessment tool to provide municipalities and the nation as a whole with a quantifiable assessment of their vulnerability to water infrastructure threats. The approach will prioritize countermeasures and identify where research and development is required to further minimize risk. This paper outlines the current context, primary concerns and state-of-the art in critical infrastructure risk management for the water sector and proposes a novel approach to resolve existing questions in the field. The proposed approach is based on a modular framework that derives a quantitative risk index for varied domains of interest. The approach methodology is scaleable and based on formal definitions of event probability and severity. The framework is equally applicable to natural and human-induced hazard types and can be used for analysis of compound risk events.

Selecting a multi-agent system development tool for industrial applications: A case study of self-serving aircraft assets

Industrialists have few example processes they can benchmark against in order to choose a multi-agent development kit. In this paper we present a review of commercial and academic agent tools with the aim of selecting one for developing an intelligent, self-serving asset architecture. In doing so, we map and enhance relevant assessment criteria found in literature. After a preliminary review of 20 multiagent platforms, we examine in further detail those of JADE, JACK and Cougaar. Our findings indicate that Cougaar is well suited for our requirements, showing excellent support for criteria such as scalability, persistence, mobility and lightweightness. © 2010 IEEE.

Progressive 3D reconstruction of infrastructure with videogrammetry

A number of methods are commonly used today to collect infrastructure's spatial data (time-of-flight, visual triangulation, etc.). However, current practice lacks a solution that is accurate, automatic, and cost-efficient at the same time. This paper presents a videogrammetric framework for acquiring spatial data of infrastructure which holds the promise to address this limitation. It uses a calibrated set of low-cost high resolution video cameras that is progressively traversed around the scene and aims to produce a dense 3D point cloud which is updated in each frame. It allows for progressive reconstruction as opposed to point-and-shoot followed by point cloud stitching. The feasibility of the framework is studied in this paper. Required steps through this process are presented and the unique challenges of each step are identified. Results specific to each step are also presented.