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Results and future of Wi-GIM

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Presentació realitzada per Giovanni Gigli i Emanuele Intrieri (Università Degli Studi Firenze) a la jornada sobre monitorització del terreny com a eina de gestió del risc i presentació del Projecte Europeu Wi-GIM (27/01/2017)

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Results and future of Wi-GIM

  1. 1. Results and future of Wi- GIM E. Intrieri, G. Gigli, L. Lombardi, M. Nocentini, T. Gracchi, N. Casagli
  2. 2. 2 Design criteria •Emergency monitoring •Low cost •Fast installation
  3. 3. 3 Wireless Sensor Network Ranging
  4. 4. 4
  5. 5. 5 Rapid installation Autonomy Low cost Modularity Real time (EW) Re-adaptability Low vulnerability High deformations Low environmental impact Versatility 24 h
  6. 6. 6 Stress tests
  7. 7. 7
  8. 8. 8 2.56 m 66.36 m
  9. 9. 9 2.56 m 66.36 m No relation with the distance was observed
  10. 10. 10 3.30 m On 20/12 the obstacle was removed: - Increased accuracy - Precision unaffected With obstacle Without obstacle
  11. 11. 11
  12. 12. Roncovetro test site Photo by G. Bertolini • Emilia-Romagna (Italy) • 2.5 km long mudflow • Average velocity of a few decameters per year • Velocity up to 10 m/day • 3·106 m3 volume
  13. 13. 13 2001 2014
  14. 14. 14 Propedeutical monitoring
  15. 15. 15 Propedeutical monitoring
  16. 16. 16 Propedeutical monitoring
  17. 17. 17 Propedeutical monitoring
  18. 18. 18 Wi-GIM installation
  19. 19. 19 Cluster 1
  20. 20. 20 Nodes distance
  21. 21. 21 Cluster 2
  22. 22. 22 Nodes distance
  23. 23. 23 Raw data
  24. 24. 24 Cluster 1 Measurements made
  25. 25. 25 Cluster 1 Valid measurements
  26. 26. 26 Cluster 2 Measurements made
  27. 27. 27 Cluster 2 Valid measurements
  28. 28. 28 Meteorological conditions
  29. 29. 29 Raw data X: distance between 3 and 7 O: distance between 7 and 3
  30. 30. 30 Valid measurements
  31. 31. 31 Corrected measurements
  32. 32. 32 Daily averages
  33. 33. 33 X: Wi-GIM data O: RTS data Data validation
  34. 34. 34 X: Wi-GIM data O: RTS data Data validation
  35. 35. 35 Data validation X: Wi-GIM data O: RTS data
  36. 36. 36 Node 10
  37. 37. 37 Data validation X: Wi-GIM data O: RTS data
  38. 38. 38 Data validation X: Wi-GIM data O: RTS data
  39. 39. 39 Cluster 1 Wireless extensometer
  40. 40. 40 Motion tracking
  41. 41. 41 Cluster 2 – Node 12 Motion tracking
  42. 42. Sallent test site 42 • Catanulya (Spain) • Old underground potash mine • 40 m large 110 m high natural cavity • 50 cm vertical subsidence between 1997 and 2010
  43. 43. 43 Google Earth photo 2006 Google Earth photo 2015
  44. 44. 44 Master Node UWB Master node with CW Radar
  45. 45. 45 X: distance between 1 and 5 O: distance between 5 and 1 Monitoring data Making 1 measurement every 6 hours 4x2 readings are obtained which can be averaged to obtain 8 cm precision.
  46. 46. Wi-GIM Results 46 Wi-GIM results First results of Wi-GIM show raw measurement accuracy of about 8 to 30 cm depending the sensor location. Due the nature of subsidence dynamics (small and slow but sustained in time), this accuracy implies that this monitoring system needs some time of continuous lectures to deliver information of the terrain movement. Nevertheless, it has been observed that there are several factors with influence on the system accuracy, which can be ranged and /or corrected.
  47. 47. 47 Wi-GIM results Daily noise range One of the main factors of data fluctuation which have been observed is temperature which show daily and seasonal influence. Daily, the sampling time-step of 8 hours translates into a three lectures in a fairly different temperature conditions, and hence a fairly different lectures in a temperature- affected sensor, generating a daily range. Seasonally, general temperature fluctuations affect general trends of measures, and require long datasets to be corrected. Seasonal fluctuation
  48. 48. 48 Wi-GIM results Daily fluctuation due temperature can be corrected by relating both variables. A linear relation between them can greatly improve accuracy to a daily fluctuations under 5 cm.
  49. 49. In order to gather more information about the system response to a subsidence phenomena, the displacement has been forced in two of the sensors. 49 Wi-GIM results
  50. 50. It has been seen that system responds adequately to the forced movement in the relation between the displaced sensors and the rest of the network within the accuracy limits. 50 Wi-GIM results
  51. 51. Future of Wi-GIM 51 •Geotechnical Engineering Centre at University of Alberta •Research mandate to apply and test innovative monitoring systems •Bilateral agreement of cultural and scientific cooperation between DST- UNIFI and Department of Civil and Environmental Engineering of University of Alberta •Application to Fountain Slide (Canada)
  52. 52. Future of Wi-GIM 52 •Oriente de Michoacán •Deep Seated Gravitational Slope Deformation •4 million m3
  53. 53. Conclusions 5353 Precision (raw data): 8-10 cm Precision (filtered): 2-3 cm Battery duration: ≈ 1 month Maximum range distance: 140 m Cost : ≈ 100 €/node Precision (filtered): <1 cm Reduce node size Increase battery duration Cost (industrialized): ≈ 50-70 €/node NOW FUTURE
  54. 54. 54  Accuratezza misure UWB  Distanza fra nodi  Rapida installazione  Basso costo  Bassa vulnerabiità  Elevata autonomia In corso di approfondimento: • Effetto multipath • Influenza fattori atmosferici • Influenza direzionalità antenne • Influenza ostacoli (altezza antenne) • Posizionamento 3D Promettente per earthflow e grandi frane in roccia

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