1. BRIMON: Wireless Sensor Network based Railway Bridge Monitoring Kameswari Chebrolu Assistant Professor Department of Electrical Engineering IIT Kanpur http://home.iitk.ac.in/~chebrolu

2. People Kameswari Chebrolu Bhaskaran Raman Nilesh Mishra Hemanth Haridas Phani Kumar Valiveti Raj Kumar

3. Motivation Indian Railways consists of 1,20,000 bridges spread over a large geographical area Many in weak and distressed conditions  57% are over 80 years old An automated system to track bridge's health is of utmost importance.  Short term monitoring  Long term monitoring

4. Existing Techniques Mostly wired solutions  Equipment is bulky and very expensive  Large setup time (few days) for short-term monitoring Few wireless solutions  WISDEN (UCLA) Continuous monitoring  Golden-gate bridge (UCB) Short-term monitoring

5. Problem Statement Develop an easy to deploy, low maintenance and long-term structural health monitoring system for Railway bridges Easy to deploy: Huge number of bridges to monitor Low maintenance: Technical expertise is difficult to get Long-term: Useful to monitor a structure's health over time

6. Application Requirements What to measure? Acceleration in 3-axis of motion  Frequency components of interest 0.25-20Hz How long to measure?  Forced vibrations: 20sec; Free vibrations: 20sec Time Synchronization  Necessary only across node in a span  Need accuracy of 5ms 30-125m 3-axis accelerometers

7. Implications of Requirements 2km bridge can have as many as 200 sensors  6 nodes per span; 60m span Data collection duration: 40sec Data generated by a node: 3 channels * 12 bits * 40 Hz * 40 sec = 57.6kbits Maximum data from a data span (12 nodes): 691.2kbits Maximum data generated by the sensors on the bridge: 1.44 MBytes

8. Solution Approach Battery operated wireless sensor motes  Cheap alternative  Easy to deploy and maintain Eliminates hassle of laying cable to route data/power  No solar panels Expensive and prone to theft Sensors maybe placed under deck in shade Key Goal: Minimize energy consumption

9. Hardware Details Sensor mote: Tmote-Sky  8 Mhz MSP430 processor  250kbps 2.4Ghz radio complaint with 802.15.4 MEMS based ADXL 203 accelerometer  Dual axis  Range is +/- 1.7g  Sensitivity 1000mv/g 8dBi Omni Antenna

10. Challenges Event Detection  Cannot predict train arrival  To conserve power, sensor nodes have to duty- cycle (sleep + wake cycle) Remote Access  Bridges may not have network coverage to transfer data to central server Scalability  Can have as many as 200 sensors per bridge  Protocols and architecture needs to be scalable

11. Outline Motivation Application Requirements Challenges Overview of Architecture Event Detection Data Transfer Measurements on a Bridge Conclusions

12. Architecture Overview 1 2 3 4 5 6 Span 3 1 2 5 6 4 1 Cluster heads Channel 3 Channel 5 Channel 3 Channel 5 Piers Event Signaling module (Channel 1) Clusters Data Transport modules Data span as an independent network Each cluster operates on a different channel

13. 1 2 3 4 5 6 3 1 2 5 6 4 Channel 3 Channel 5 Topology Formation

14. 1 2 3 4 5 6 3 1 2 5 6 4 Channel 3 Channel 5 Time Synchronization

15. 1 2 3 4 5 6 3 1 2 5 6 4 Sleep-Wakeup Channel 1 Channel 3 Channel 5

16. 1 2 3 4 5 6 3 1 2 5 6 4 Train Arrival Detection Command Control: Wakeup

17. 1 2 3 4 5 6 3 1 2 5 6 4 Vibration Sensing

18. 1 2 3 4 5 6 3 1 2 5 6 4 Data Gathering by individual cluster heads Channel 3 Channel 5

19. 1 2 3 4 5 6 3 1 2 5 6 4 Sleep-Wakeup Channel 1 Channel 3 Channel 5

20. 1 2 3 4 5 6 3 1 2 5 6 4 Train Detection Data Uploading

21. 1 2 3 4 5 6 3 1 2 5 6 4 Sleep-Wakeup

22. Send Data to Repository

23. BriMon Architecture: Event Detection Span Head node P

24. BriMon Architecture: Event Detection Span Head node P

25. BriMon Architecture: Event Detection Span Head node P

26. BriMon Architecture: Event Detection Span Head node

27. Event Detection: Analysis Question: What should be the duration of sleep and wake up? T dc = max time available between detection of oncoming train and data collection T cc = sleep/wakeup cycle = T sl + T w T w = T det + T cd + T pc (at head mote)  T det : Time taken to detect the train  T cd : Maximum clock drift  T pc : Time taken for command propogation

28. Event Detection T w = 2*T cd + T pc (at non-head mote) Ans: T dc = T cc + T w = T sl + 2T w

29. Radio Range Measurements T dc = D/V D is found to be about 400m with 8dBi omni- antenna for various speeds At 80kmph, T dc = 36s Use of 802.11 extends range to 800m Frontier Nodes

30. Time Synchronization T w is function of T det & T cd & T pc  T sl = T dc - 2* T w T pc : We use same protocol for synchronization as well as command issue  Flooding with multiple retransmissions (3)  T pc turns out to be about 72ms  Error in synchronization is 0.18ms

31. Time Synchronization Calculating T cd  Worst case clock drift in 36 sec is 20ppm  Synchronization error is 0.31ms  T cd = 36s * 20 * 10^-6 (0.72) + 0.18 = 0.9ms T cd << T pc ; T det ~ 50ms; T w ~ 125ms; T sl ~ 36–0.25 = 35.75; Duty Cycling ~ 0.3%

32. Data Transfer Long distance wireless links infeasible  2km bridge with 200 sensors generate 1.5MB data  Transfer to single hop over 10-20 hops presents scalability problems  Data transfer time for 14 node network is 5 min Reference: “A Wireless Sensor Network for Structural Health Monitoring: Performance and Experience”, EmNetS-II, May 2005

33. Data Transfer: Our Approach Use multiple channels; one for each data span  Data across spans independent  At most 12 nodes per span; very scalable  Adjacent channels are 7 spans apart with 16 available channels Transfer data of the span motes to the head mote Transfer data from head mote to train

34. Data Transfer C3 C5 C7 C9 Head Mote 3 6 5 2 4 1

35. Data Transfer within Span: Routing Issues Links are very stable in our setting  Reference: “Implications of Link Range and (In)Stability on Sensor Network Architecture”, WINTECH 2006 Any simple protocol can be used  Centralized 2 Phase routing  Average duration of routing for 6 nodes : 567ms

36. Routing Protocol: An Example 2 4 13 6 5 (a) Cluster of six nodes 2 4 13 6 5 (b) Neighbourhood Discovery 2 4 13 6 5 (c) Nodes 2,3 & 4 are good neighbours to node 1 2 4 13 6 5 (d) Node 6 is a good neighbour to node3, node 5 has no good neighbour 2 4 13 6 5 (e) Node 5 is a bad neighbour to node 3 2 4 13 6 5 (f) Dispatch Tree information

37. Data Transfer within Span: Transport Protocol Transport protocol  Transfers data from the motes to the head mote  NACK based block transfer HEAD Mote NODE-2 FLASH NODE-3NODE-4 FLASH CMD Data TFR CMD Data ACK CMD Data TFR CMD Data ACK CMD Data TFR CMD Data ACK Block Data TFR Block Data ACK Block Data TFR Block Data ACK Block Data TFR Block Data ACK

38. Single Hop Data Transfer

39. Mobile Data Transfer Achievable data transfer rate using block transfer transport protocol on hardware is 46kbps (tested on field) Max data per data span is 693Kbits (12 nodes) Contact duration required is 15sec  Contact Range required = contact duration * speed of train Head node Contact Range = D

40. Throughput Considerations Contact range required for data transfer is  330m at train speed of 80kmph  250m at train speed of 60kmph Our measurements give a contact range of 400m (one-side) Transfer is possible with enough leeway. Throughput can be further increased via  Compression  Multiple receivers at head and rear of train  Better Hardware Simultaneous operation of flash and radio Bluetooth Radio (1Mbps)

41. Lifetime Estimate Can achieve 1.5 year of operation using a 2500mAH battery 131s 33s 15s 36s

42. Measurements on a Bridge Omni antenna

43. Measurements on a Bridge Sink Mote

44. Data Analysis Tool

45. Conclusions Application specific design  Extensive measurement study Novelty of our contributions  Event detection mechanism  Mobile data transfer  Integration with time-synchronization/routing Estimates indicate network can operate without intervention for 1 1/2 years