Simulating Data Journalism to Communicate Hydrological Information from Sensor Networks

Presenting relevant information via web-based user friendly interfac- es makes the information more accessible to the general public. This is especial- ly useful for sensor networks that monitor natural environments. Adequately communicating this type of information helps increase awareness about the limited availability of natural resources and promotes their better use with sus- tainable practices. In this paper, I suggest an approach to communicating this information to wide audiences based on simulating data journalism using artifi- cial intelligence techniques. I analyze this approach by describing a pioneer knowledge-based system called VSAIH, which looks for news in hydrological data from a national sensor network in Spain and creates news stories that gen- eral users can understand. VSAIH integrates artificial intelligence techniques, including a model-based data analyzer and a presentation planner. In the paper, I also describe characteristics of the hydrological national sensor network and the technical solutions applied by VSAIH to simulate data journalism.

A multinational SDI-based system to facilitate disaster risk management in the Andean Community

A useful strategy for improving disaster risk management is sharing spatial data across different technical organizations using shared information systems. However, the implementation of this type of system requires a large effort, so it is difficult to find fully implemented and sustainable information systems that facilitate sharing multinational spatial data about disasters, especially in developing countries. In this paper, we describe a pioneer system for sharing spatial information that we developed for the Andean Community. This system, called SIAPAD (Andean Information System for Disaster Prevention and Relief), integrates spatial information from 37 technical organizations in the Andean countries (Bolivia, Colombia, Ecuador, and Peru). SIAPAD was based on the concept of a thematic Spatial Data Infrastructure (SDI) and includes a web application, called GEORiesgo, which helps users to find relevant information with a knowledge-based system. In the paper, we describe the design and implementation of SIAPAD together with general conclusions and future directions which we learned as a result of this work.

An Ant Colony System adaptation to deal with accessibility issues after a disaster

One of the main problems relief teams face after a natural or man-made disaster is how to plan rural road repair work tasks to take maximum advantage of the limited available financial and human resources. Previous research focused on speeding up repair work or on selecting the location of health centers to minimize transport times for injured citizens. In spite of the good results, this research does not take into account another key factor: survivor accessibility to resources. In this paper we account for the accessibility issue, that is, we maximize the number of survivors that reach the nearest regional center (cities where economic and social activity is concentrated) in a minimum time by planning which rural roads should be repaired given the available financial and human resources. This is a combinatorial problem since the number of connections between cities and regional centers grows exponentially with the problem size, and exact methods are no good for achieving an optimum solution. In order to solve the problem we propose using an Ant Colony System adaptation, which is based on ants? foraging behavior. Ants stochastically build minimal paths to regional centers and decide if damaged roads are repaired on the basis of pheromone levels, accessibility heuristic information and the available budget. The proposed algorithm is illustrated by means of an example regarding the 2010 Haiti earthquake, and its performance is compared with another metaheuristic, GRASP.