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Problem Description
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 calculation of flood detection. Current distributed state estimation techniques rely on fixed calculation topologies, but a flood morphs and mutates, something to which a fixed topology cannot adapt. We view adaptation to changing topologies in a sensor network as a key property of any effective flood warning system and a focus of our current algorithmic work. Adaptation is necessary at several levels. It is needed for routing to cope with a morphing flood phenomenon, Adaptation is also needed in the structure of the distributed calculation so that the resulting algorithm is robust.
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 relationship for the installation of a prototype system.
Publications and Additional Information
Elizabeth Basha, Daniela Rus - Design of Early Warning Flood Detection Systems for Developing Countries
- Proceedings of the Conference on Information and Communication Technologies and Development , Bangalore, India, December, 2007
Pdf Bibtex
Case Study by Microsoft Research - Wireless Sensor Network Provides Early Flood Detection for Underserved Countries
People
Primary Researchers
Elizabeth Basha
Daniela Rus
Sai Ravela
Implementation Contributors
Alexander Bahr
William Boos
Patrick Barragan
Alejandro Flores
Erika Granger
Andrea Llenos
Anthony Parolari
Sarah Rich
Tadd Truscott
Collaborators
Fundacíon San Alonso Rodríguez, Tocoa, Honduras: Gines Suarez, Director
Funding
- Xerox
- Microsoft Research
- Carrol Wilson Award
- Thrivent
- IDEAS Competition
- MIT Public Service Center
- MIT D-Lab
Links
- FSH Student Group
- Fundacíon San Alonso Rodríguez


