1. An Intelligent and Adaptable Grid-Based Flood Monitoring and Warning System Phil Greenwood

2. The Problem Flooding is becoming a more common occurrence Climate change Land use Cost of damage correlates with Rate of flow Depth of water Warning time given To cope with this problem initiatives taken to: Improve flood defences Raise public awareness Improve flood warning systems

3. Traditional Approaches Deploy sensors at flood prone sites Collect data manually or transmitted using GSM technology Data then processed using spatial or point-based prediction algorithms The results from these algorithms can be used to issue flood warnings

4. Limitations Rigid separation between on-site sensor network and off-site computation Grid Tends to be bottleneck The sensors used are computationally dumb They simply record and store/transmit data Data holds valuable information on how the sensors should behave No variation in the sensor behaviour possible Turn device off when un-interesting events occurring Increase frequency of measurements made No dissemination of warnings

5. Proposed Approach Increase local computational power of sensors Allow the local execution of flood prediction algorithms i.e. light-weight Grid Adaptation of the wireless sensor network Support a wider range of hardware Novel techniques for flood prediction and analysis Timely distribution of flood warnings Proactive and passive warnings SMS/Audio-Visual/Web

6. The GridStix Platform Consists of a variety of hardware and software: Gumstix hardware platform Lancaster’s GridKit middleware platform Various networking technologies Flood prediction algorithms

7. Gumstix (1)

8. Gumstix (2) Specs 400Mhz Intel XScale processor 64Mb RAM 16Mb Flash Memory Variety of I/O Mechanism Standard Ethernet port Compact Flash slot Storage 802.11b Networking GPRS GPIO Lines for sensor connectivity On-board Bluetooth Radio

9. Power Consumption Significantly higher power consumption than devices used in traditional sensor networks Berkley Motes typically use 54mW Gumstix use 1W Can be powered using a combination of batteries and solar panels One 15cm 2 solar panel output of 1.9W 6v 10AH battery Aggressive power management

10. GridKit (1) Provides key functionality to implement Grid behaviour Service Binding Resource Discovery Resource Management Security Based on the OpenCOM component model Rich support Stripped-down deployments Overlay support Used to implement networking service not provided by the underlying network type

11. Overlay (1)

12. Overlay (2)

13. Supported Adaptations CPU Adaptation Throttle CPU frequency Overlay Adaptations Swap overlay components to alter topology Physical Network Adaptations Switch network types

14. Adaptation Scenario 1 Changes in Criticality Need to conserve power in normal operating conditions Operate at lowest CPU frequency Poll sensor infrequently Potential Flooding Detected GridStix can increase CPU frequency to execute prediction algorithms quicker Data can also be collected more frequently to improve the accuracy of the predictions

15. Adaptation Scenario 2 Adapting to Node Failure Need to increase the robustness of network when flooding is predicted Do this without changing network type Switch overlay types Shortest path trees consume less power Fewest hop trees are more robust

16. Adaptation Scenario 2 cont. Root Node B Node C Edge x Node D Edge x Node E Edge x Node F Edge x Root Node B Node D Node C Node F Node E Shortest Path Fewest Hops Trigger: Flooding predicted by a Gumstix. Bluetooth used by default due to lower power requirements. Shortest-Path tree overlay used due to its power conservation characteristics. Bluetooth continues to be used. Fewest Hop tree overlay applied to increase the robustness of the tree.

17. Adaptation Scenario 3 Node Submersion Likely that nodes will become submerged during flooding Want nodes to remain connected for as long as possible Switch network types when submersion is predicted Bluetooth -> Wifi or Wifi -> GPRS High power consumption and increased range

18. Adaptation Scenario 3 cont. Root Node B Node D Node C Node F Node E Fewest Hops Trigger: Submersion predicted by a Gumstix. Switch from Bluetooth to Wifi Same overlay type used. However, the different characteristics of Wifi causes a new topology to be created. Root Node B Node F Node D Node ENode C Fewest Hops

19. Current Status Small test-bed of nodes currently deployed: Three Gumstix Nodes Depth Sensors Image-based Flow Sensors Additional nodes are being added, to initial deployment size of 13 nodes. Performance of network hardware, solar panels and other hardware is being tested in the field.

20. Future Work Development of a simulator to test deployment approaches with past and predicted flood events. Bringing in more highly embedded hardware running the RUNES GridKit implementation. Integration with Lancaster’s main NW Grid Deployment.

21. Summary Proposes a more automatic and sophisticated mechanism for collecting and processing flood data Convergence of Grid and Wireless Sensor Network functionality Uses this sophisticated mechanisms for performing adaptations Can customise the configuration and behaviour of sensors to the current environmental conditions