The Sensor Web Fire Shield (SWeFS) research project aims at delivering:
- a methodology for developing a novel Sensor Web platform for dynamic data-driven assimilation (DDDAS) for securing the Wildland-Urban Interface (WUI) zones against environmental risks, and,
- a prototype DDDAS system specifically optimized/tuned for addressing the serious threat of forest fires in Greece. SWeFS calls for multidisciplinary research in the areas of sensor networks, distributed vision systems, remote sensing, geographical information systems (GIS), data stream fusion, space-time predictive modeling and control systems.
The main objectives of the proposed research are:
- Design a novel Sensor Web architecture with heterogeneous sensors, remote sensing and risk prediction models into a closed loop system for the effective and timely detection of environmental risks.
- Test the proposed architecture through the development of a prototype platform for fire detection in WUI zones in Greece.
- Improve the prediction of the spatiotemporal evolution of a hazardous phenomenon by adopting a DDDAS approach for calibrating simulation models in real-time.
SWeFS is organized in six workpackages (WPs).
- WP1 manages all project activities.
- WP2 covers the underlying Sensor Web infrastructure.
- WP3 focuses on the development of the necessary satellite remote sensing and GIS.
- WP4 produces the design/implementation of the data fusion schemes and predictive models.
- WP5 integrates all the components in a closed-loop control system and evaluates its performance.
- WP6 covers the project dissemination activities.
The first significant deliverables of SWeFS will be the design and implementation of the sensing infrastructure (WSN and optical detection). Furthermore, an efficient monitoring system based on satellite imaging technologies and GIS and efficient prediction models and data fusion techniques will follow. Last result will be a prototype system for forest fire detection.