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Flooding is a critical global problem, which is growing more severe due to the effects of climate change. This problem is particularly acute in the state of São Paulo, Brazil, where flooding during the rainy season incurs significant financial and human costs. Another critical problem associated with flooding is the high level of pollution present

Considerable research has been performed in applying run-time reconfigurable component models to the domain of wireless sensor networks. The ability to dynamically deploy and reconfigure software components has clear advantages in sensor networks, which are typically large in scale and expected to operate for long periods in the face of node mobility, dynamic environmental conditions, and changing application requirements. LooCI is a component and binding model that is optimized for use in resource-constrained environments such as Wireless Sensor Networks. LooCI components use a novel event-based binding model that allows developers to model rich component interactions, while providing support for run-time reconfiguration, reflection, and policy-based management. This paper reports on the design of LooCI and describes a prototype implementation for the Sun SPOT. This platform is then evaluated in context of a real-world river monitoring and warning scenario in the city of São Carlos, Brazil.

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This paper describes the application of the DisSeNT middleware to implement Wireless Sensor Network based river monitoring. DisSeNT provides LooCI, an efficient run time reconfigurable component model, PMA, a lightweight policybased management framework and QARI, a declarative qualityaware deployment framework. Using a river monitoring casestudy, this paper analyses how these distinct software development paradigms can be used in a complimentary fashion to develop efficient wireless sensor network applications. The resulting system has been deployed and evaluated in a realworld river monitoring scenario in the city of São Carlos, Brazil.