Flood Early Warning System

In developing countries, warning communities of an incoming flood is an expensive proposal given their limited resources. The equipment necessary for early warning flood systems is expensive and centralized to support flood detection schemes that are computationally complex. This project explores new techniques for distributing the computation of flood detection within a wireless sensor network, grounding the research in reality through the design and installation of an early warning system for flooding in a developing country.

Sensor networks for flooding do not exist in a real-time automated capacity within developing countries. We are developing such a sensor network and examining how to distribute and adapt the flood prediction calculation. Current flood prediction relies on physically-based models requiring large amounts of data in order to calibrate the model, and significant computation power to compute the model. Neither of these being feasible on a sensor network as data storage and computing power are limited, we are working on statistical algorithms capable of online, distributed computation.

Given a suite of robust adaptive distributed algorithms for flood warning, we are planning to implement these algorithms on a system that can be deployed within a developing country. This poses a number of challenges, ranging from survival in harsh flood environments, lack of trained personnel to maintain the system, and an illiterate populace to warn. Designing and implementing a system that addresses these issues poses interesting engineering problems. Key research questions here include: (1) How does each sensor node measure its environment? (2) How does each sensor communicate with the rest of the network, and convey its ongoing status given the worst weather conditions possible on a river? (3) How and where should the information from the sensors be processed and fused?

Understanding the sensor system and computational design issues requires implementing the system within a developing country. We are working with a local non-governmental organization, the Fundacion San Alonso Rodriguez in Tocoa, Honduras to develop a test system in the Rio Aguan basin. Our two organizations have worked together since January 2004, exploring issues related to adapting technologies to solve developing world issues. This area regularly suffers from severe flooding so, with the support of FSAR and the Honduran communities, this location epitomizes an ideal testbed for the installation of a prototype system.