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TriopusNet Ted Tsung-Te Lai

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Presentation on theme: "TriopusNet Ted Tsung-Te Lai"— Presentation transcript:

1 TriopusNet Ted Tsung-Te Lai
Automating Wireless Sensor Network Deployment and Replacement in Pipeline Monitoring Ted Tsung-Te Lai Albert Wei-Ju Chen Kuei-Han Li Polly Huang Hao-Hua Chu National Taiwan University

2 Outline Motivation TriopusNet System Design Evaluation Limitations
Related Work Conclusion

3 Water pipelines are everywhere people live

4 Pipelines carry important resources (gas, oil…etc.)

5 Pipelines carry very important resources (beer pipeline!)

6 Pipeline monitoring is essential
Motivation leaking leaking

7 Water contamination (Boston, 2010)

8 Difficult sensor deployment

9 WSN challenges (Deployment and maintenance)
Deployment challenges Difficult to access pipelines to place sensors (often hidden inside walls or underground) May need to break pipes to install sensors inside Maintenance challenge Difficult to replace out-of-battery sensors Real pipeline environment Difficult to ensure network connectivity during sensor placement and replacement

10 Research question Can we automate WSN sensor placement and replacement in pipeline? While minimize the number of sensor nodes Good sensing and networking coverage Reduce the human effort bottleneck for long-term, large-scale WSN deployment & maintenance.

11 Single-Release Point the enabling concept
Place sensors at a single release point Sensors automatically place themselves in the pipes

12 How to realize single-release point?
Sensor placement Mobile sensors Sensor latch mechanism Sensor placement algorithm Sensor localization Sensor replacement Sensor replacement algorithm

13 Outline Motivation TriopusNet System Design Evaluation Limitations
Related Work Conclusion

14 TriopusNet automate WSN deployment in pipeline
Triopus node three arms for latching Single-release point Gateway node Gateway node Gateway node

15 TriopusNet automate WSN deployment in pipeline
Sensor placement Mobile sensors Sensor latch mechanism Sensor placement algorithm Sensor localization Sensor replacement Sensor replacement algorithm

16 Mobile sensor (components)
Sensor mote Actuator pull/push a mechanical arm Localization sensors (SenSys’ 10) water pressure gyro

17 Mobile sensor (kmote) = + Kmote CPU board USB board
(data processing) (program uploading) A Telosb-like platform, TinyOS compatible Smaller form-factor, only CPU board is needed

18 Mobile sensor (latch & delatch mechanism)
Linear actuator, off-the-shelf from market A motor with gear inside to control the arm Spec: Stroke: 2cm Weight: 15gram Arm extending speed: 2cm/sec 2cm 1cm 0cm

19 Prototype #1 (8cm diameter)

20 Prototype #2 (one motor, three arms)

21 Prototype #2 (6cm diameter)

22 Sensor placement algorithm
Where are the optimal locations to place sensors in pipes (after releasing them from the single-release point)? Networking coverage Interconnectivity among all nodes Sensing coverage Each pipe segment has at least one sensor Minimize # of sensor nodes for deployment

23 Sensor placement algorithm
root water inlet branch 2 branch 1 faucet 1 branch 3 faucet 4 faucet 3 faucet 2

24 Sensor placement algorithm
root water inlet branch 2 n7 branch 1 faucet 1 branch 3 n1 n6 faucet 4 faucet 3 n4 n5 faucet 2 n2 n3

25 Sensor placement algorithm
root water inlet branch 2 n7 branch 1 faucet 1 branch 3 n1 n6 faucet 4 faucet 3 n4 n5 faucet 2 n2 n3

26 Sensor placement algorithm
root water inlet branch 2 branch 1 faucet 1 branch 3 faucet 4 faucet 3 faucet 2

27 Sensor placement algorithm
root Post-order traversal : n1 -> n2 -> … n7 n7 n1 n6 n4 n5 n2 n3

28 Sensor placement algorithm
root Post-order traversal : n1 -> n2 -> … n7 n7 1st n1 n6 n4 n5 n2 n3

29 Sensor placement algorithm
root Post-order traversal : n1 -> n2 -> … n7 n7 1st n1 n6 n4 n5 2nd n2 n3

30 Sensor placement algorithm
root Post-order traversal : n1 -> n2 -> … n7 n7 1st n1 n6 n4 n5 2nd 3rd n2 n3

31 Sensor placement algorithm
root Post-order traversal : n1 -> n2 -> … n7 n7 1st n1 n6 4th n4 n5 2nd 3rd n2 n3

32 Sensor placement algorithm
root Post-order traversal : n1 -> n2 -> … n7 n7 1st n1 n6 4th 5th n4 n5 2nd 3rd n2 n3

33 Sensor placement algorithm
root Post-order traversal : n1 -> n2 -> … n7 n7 6th 1st n1 n6 4th 5th n4 n5 2nd 3rd n2 n3

34 Sensor placement algorithm
root Post-order traversal : n1 -> n2 -> … n7 7th n7 6th 1st n1 n6 4th 5th n4 n5 2nd 3rd n2 n3

35 Sensor placement algorithm
Post-order traversal : n1 -> n2 -> … n7 Reasons: 1. Assure nodes cover all pipes 2. Allow blockage-free movement (bottom-up placement) root 7th n7 6th 1st n1 n6 4th 5th n4 n5 2nd 3rd n2 n3

36 Sensor placement algorithm
Single-release point Gateway node Testing packet received ratio Bad link quality Good link quality, placement completed Gateway node Gateway node

37 Sensor localization Previous PipeProbe system [SenSys’10]
Pressure graph Previous PipeProbe system [SenSys’10] cm-level positional accuracy Vertical pipe location Water pressure changes at different height levels Horizontal pipe location Node distance = node velocity * node flow time Pipe turn detection Gyroscope

38 Data Collection Collection Tree Protocol (CTP) in TinyOS
Single-release point Collection Tree Protocol (CTP) in TinyOS Multi-sink tree to balance network load Gateway node Gateway node Gateway node

39 Sensor replacement algorithm
Single-release point Gateway node Gateway node Low Battery… Gateway node

40 Outline Motivation TriopusNet System Design Evaluation Limitations
Related Work Conclusion

41 Testbed

42 Testbed spatial layout
Single-release point 150cm 200cm 200cm 200cm 200cm 200cm

43 Evaluation metrics Automated sensor placement
# Nodes for pipeline deployment Data collection rate Energy consumption Automated sensor replacement

44 Experimental procedure (4 test scenarios)
Single-release point 5 tests for each scenario gateway Scenario 3 Scenario 2 Scenario 4 Scenario 1 gateway gateway

45 # Deployed Nodes (Static v.s. TriopusNet deployment)
Avg # of nodes deployed -Static: 7.5 -TriopusNet: 4.4 Avg. node-to-node distance: 173cm Std: 58cm Static (90cm) TriopusNetA TriopusNetB TriopusNetC

46 Avg. node-to-node distance

47 Avg. node-to-node distance

48 Avg. node-to-node distance

49 Avg. node-to-node distance

50 Data collection rate Each node sent 1000 packets to gateway -80% nodes achieve 99% packet receive rate -All nodes > 87% rate

51 Energy consumption (node placement)
Each node requires 2.4 actuations on average (1 actuation consumes ~1J)

52 Evaluation metrics Automated sensor placement
# nodes for sensing/networking coverage Data collection rate Energy consumption Automated sensor replacement

53 Test scenario and result for replacement
Data collection rate Initial deployment After replacement Without replacement 0.99 0.98 0.80 Set these two nodes to low battery level and trigger replacement

54 Outline Motivation TriopusNet System Design Evaluation Limitations
Related Work Conclusion

55 Limitation: Lack automatic faucets

56 Limitation: Node size

57 Limitation: Node size Single-release point Low Battery…

58 Outline Motivation TriopusNet System Design Evaluation Limitations
Related Work Conclusion

59 PipeNet (IPSN’07, pipeline monitoring)
Detect and localize leakage by pressure and ultrasonic sensors

60 NAWMS (SenSys’08, water flow sensing)

61 HydroSense (Ubicomp’09, water event sensing)
Single-point pressure-based sensor of water usage toilet kitchen sink shower

62 Comparison to related work
Multi-point sensing Single-point Single-release point NAWMS HydroSense TriopusNet PipeNet

63 Outline Motivation TriopusNet System Design Evaluation Limitations
Related Work Conclusion

64 Conclusion TriopusNet: automating WSN deployment and replacement in pipeline monitoring Automated sensor placement and replacement to reduce human deployment and maintenance effort: mobile sensors with self-latching mechanism from a single-release point Results show smaller number of sensor nodes with good sensing/networking coverage

65 Thank shepherd (Prof. Gian Pietro Picco) & reviewers for valuable comments
Questions & Answers TriopusNet: Automating WSN Deployement and Replacement in Pipeline Monitoring Ted Tsung-Te Lai, Albert Wei-Ju Chen, Kuei-Han Li Polly Huang, Hao-hua Chu Ubicomp lab National Taiwan University

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