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Is There Light at the Ends of the Tunnel?Wireless Sensor Networks for Adaptive Lighting in Road
Tunnels
IPSN 2011
Sean
Outline
• Goal • Challenge• Contribution• System Architecture• Hardware & Software• Testbed• Evaluation• Conclusion
Goal• WSN-based Close-loop adaptive lighting in road tunnel
– Improve tunnel safety– Reduce power consumption
• State-of-the-art solutions– Pre-set lighting based on date and time– Relying only on external sensor
• Testbed evaluation• Real deployment
– Project TRITon– 630m, two-way, two-lane tunnel
Challenge• Peculiarities of Tunnels
– harsh environment, relatively studied on WSN– Vehicular traffic– dirt and dust accumulation– Periodic tunnel cleaning– Limited deployment & debugging– Light variation
• Need filtering
– Better connectivity• Robustness • Packet collision
o. Interference with WSN radioo. Occlusion & noise to light sensor
direct sunlight
Variation caused by vehicle
Challenge
• Real-world constraints– Extended lifetime : at least 1-year by tunnel operators– WSN cannot fail due to continuous operation– Sensed data must arrive timely– Quality of sensing– Integration with conventional, industrial-strength equipment
Contribution• Verify WSN-based solution to adaptive lighting is feasible• Understand what extent the mainstream WSN technology can
achieve• Real testbed implement• Gaining practical insight into tunnel scenario– Real-world lesson asset
System Architecture• 3 components
– An external sensor
– A grid of light sensor along the tunnel length
– A control algorithm
Measure the veil luminance
Compute error between legislated curve and actual lighting
Drive above error to zero
Determine the legislated curve
HPS in TestbedLED for project
Hardware & Software
• Collection tree– Use LQI as path cost – Periodically reconstructed every 3min
• Light Sensing– Average 4 sensor value into S(i)– Average all S(i) into S(all)– if |S(all) – S(i)| differs from S(all) by
50%, discard it– Recompute S(all)
Testbed• 40 nodes, 260m-long, two-way, two-lane tunnel• PLC relies only on first 15 node• 7-month experiments• More dense than TRITon
– 44 nodes, 630m• Light sensor sample every 5s, PLC collects data every 30s
Evaluation
• Light adaptive effect• Loss rate• Timely delivery• Resilience to gateway failures• Retransmission cost• Expected lifetime
Light adaptive effect• Artificial step response
• Node position relative to lamps bears great influence• Behavior of other node is closer to node 7 than node 4
Still follow the reference trend
Light adaptive effect• Real-world reference
Bound by the dynamic range of light actuatorOnly 150 lx maximum
Loss rateTime spent transmitting and waiting for receiver to wake up becomes significant
Timely delivery
30~60s:PLC may loss a sample in its cycle
> 60s:PLC will loss more than one sample in its cycle
Resilience to gateway failures
Retransmission cost
Expected lifetime
• Battery discharge profile– Temperature– Voltage– Discharge current
• Underestimate– Use average discharge current of
100mA– LPL-like MAC only consume a few mA
• 250ms LPL is better– Power consumed in channel check– Packet strobe time
Trade-off
Conclusion
• Reach the goal of close-loop adaptive lighting• Provide real-world insights and experience by
using WSN in road tunnel
Any Problem?