1. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 1 A Wireless Sensor Network For Structural Monitoring (Wisden) Collaborators: Ning Xu, Krishna Kant Chintalapudi, Deepak Ganesan, Alan Broad, Ramesh Govindan, Deborah Estrin, Jeongyeup Paek, Nupur Kothari Sumit Rangwala

2. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 2 Background Structural health monitoring (SHM) –Detection and localization of damages in structures »Structural response Ambient vibration (earthquake, wind etc) Forced vibration (large shaker) Current SHM systems –Sensors (accelerometers) placed at different structure location –Connected to the centralized location »Wires (cables) »Single hop wireless links –Wired or single hop wireless data acquisition system

3. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 3 Motivation Are wireless sensor networks an alternative? Why WSN? –Scalable »Finer spatial sampling –Rapid deployment Wisden –Wireless multi-hop data acquisition system

4. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 4 Challenges Reliable data delivery –SHM intolerant to data losses High aggregate data rate –Each node sampling at 100 Hz or above »About 48Kb/sec (10 node,16-bit sample, 100Hz, 3 axes) Data synchronization –Synchronizing samples from different sources at the base station Resource constraints –Limited bandwidth and memory Energy efficiency –Future work

5. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 5 Wisden Architecture ChallengesArchitectural Component Description Reliable data delivery Reliable Data Transport Hybrid hop-by-hop and end-to-end error recovery High data rateCompressionSilence suppression Wavelet based compression Data Synchronization Residence time calculation in the network

6. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 6 Reliable Data Transport Routing –Nodes self-organize in a routing tree rooted at the base station –Used Woo et al.’s work on routing tree construction Reliability – Hop-by-hop recovery »How ? NACK based Piggybacking and overhearing »Why hop by hop? High packet loss NACK Retransmission NACK Retransmission NACK Retransmission

7. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 7 Reliable Data Transport (cont.) –End to End packet recovery »How ? Initiated by the base station (PC) Same mechanism as hop-by-hop NACK »Why ? Topology changes leads to loss of missing packet information Missing packet information may exceed the available memory –Data Transmission rate »Rate at which a node inject data Currently pre-configured for each node at R/N –R = nominal radio bandwidth –N = total number of nodes » Adaptive rate allocation part of future work.

8. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 8 Compression Sampled data significant fraction of radio bandwidth Event based compression –Detect Event »Based on maximum difference in sample value over a variable window size –Quiescent period »Run length encoding –Non-quiescent period »No compression –Saving proportional to duty- cycle of vibration Drawback –High latency Quiescent Period EventQuiescent Period CompressionNo Compression Compression

9. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 9 Compression For Low Latency Progressive storage and transmission –Event detection –Wavelet decomposition and local storage –Compression »Low – resolution components are transmitted –Raw data, if required available from local storage Current Status –Evaluated on standalone implementation –To be integrated into Wisden Wavelet Decomposition Quantization, Thresholding, Run length coding Sink Flash Storage To sink on demand Reliable Data Transport Event Low resolution components

10. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 10 Data Synchronization Synchronize data samples at the base station –Generation time of each sample in terms of base station clock –Network wide clock synchronization not necessary Light-weight approach –As each packet travels through the network »Time spent at each node calculated using local clock and added to the field “residence time” »Base station subtracts residence time from current time to get sample generation time. –Time spent in the network defines the level of accuracy S qAqA A qAqA q A + q B B qBqB T A =T-(q A + q B )T C =T-(q C + q D ) qCqC C qCqC q C + q D D qDqD

11. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 11 Implementation Hardware –Mica2 motes –Vibration card (MDA400CA from Crossbow) »High frequency sampling (up to 20KHz) »16 bit samples »Programmable anti-aliasing filter Software –TinyOS –Additional software »64-bit clock component »Modified vibration card firmware

12. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 12 Deployment Scenario 1 Seismic test structure –Full scale model of an actual hospital ceiling structure Four Seasons building –Damaged four-storey office building subjected to forced-vibration 1 Not presented in the paper

13. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 13 Seismic Test Structure Setup Setup –10 node deployment –Sampling at 50 Hz along three axes –Transmission rate at 0.5 packets/sec –Impulse excitation using hydraulic actuators For validation –A node sending data to PC over serial port (Wired node) –A co-located node sending data to the PC over the wireless multihop network (Wisden node)

14. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 14 Results: Frequency Response Low frequency modes captured High frequency modes lost –Artifact of compression scheme we used Power spectral density: Wisden nodePower spectral density: Wired node

15. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 15 Results: Packet Reception and Latency Packet reception –99.87 % (cumulative over all nodes) –100 %, if we had waited longer Latency –7 minutes to collect data for 1 minute of vibration

16. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 16 Four Seasons Building Setup –10 node deployment –Sampling at 50 Hz along three axes –Transmission rate at 0.5 packets/sec –Excitation using eccentric mass shakers For validation –Wisden nodes places alongside floor mounted force-balance accelerometer (Wired node)

17. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 17 Results: Frequency Response Dominant frequency captured Noise –Sampling differences, force balanced accelerometer much more sophisticated, packet losses Power spectral density: Wisden NodePower spectral density: Wired Node

18. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 18 Results: Packet Reception Packet reception –High data loss »Due to a bug

19. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory 19 Conclusions and Future Work Wisden – A wireless data acquisition system that provides –Reliable data collection –Supports high sampling rate –Data synchronization Future work –Adaptive rate allocation scheme –Integrating wavelet based compression –Power efficiency Wisden version 0.1 available at http://enl.usc.edu/ Thank you