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
o. Interference with WSN radio
Vehicular traffic
dirt and dust accumulation o. Occlusion & noise to light sensor
Periodic tunnel cleaning
direct sunlight
Limited deployment & debugging
Light variation
• Need filtering
– Better connectivity
• Robustness
• Packet collision
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
Measure the veil luminance
Determine the legislated curve
– A grid of light sensor along the tunnel length
Compute error between legislated curve and actual lighting
– A control algorithm
Drive above error to zero
HPS in Testbed
LED 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
Still follow the reference trend
• Node position relative to lamps bears great influence
• Behavior of other node is closer to node 7 than node 4
Light adaptive effect
• Real-world reference
Bound by the dynamic range of light actuator
Only 150 lx maximum
Loss rate
Time spent transmitting and waiting for receiver to wake up becomes significant
Timely delivery
> 60s:
PLC will loss more than one sample in its cycle
30~60s:
PLC may loss a 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?