1 Emergency Navigation by Wireless Sensor Networks in 2D and 3D Indoor Environments Yu-Chee Tseng...
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Transcript of 1 Emergency Navigation by Wireless Sensor Networks in 2D and 3D Indoor Environments Yu-Chee Tseng...
1
Emergency Navigationby Wireless Sensor Networks
in 2D and 3D Indoor Environments
Yu-Chee Tseng
Deptment of Computer Science
National Chiao Tung University
2
Outline
Introduction System Overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion
3
Outline
Introduction System Overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion
4
Introduction
Wireless Sensor Network Each sensor has
Limited Memory 、 Limited CPU 、 Wireless Transceiver 、 Sensing Unit
Each sensor can Sense environments Communicate with others Do simple computations
5
Introduction
Traditional Navigation Devices Advantage
Cheap Easy deployment
Disadvantage Fixed direction. Can not adapt to actual emergency situations.
6
Introduction
Motivation According to the statistic report of the NFA of Taiwan(內政部消防署) , 228 people died in fire accidents in 2003.
The main reason is that people can not find “right” escaping paths to exits.
Our Goal to develop an emergency navigation system for indoor 2D and 3D environments
7
Outline
Introduction System overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion
8
System Overview
Our system is composed of 3 parts Environment setting Regular reporting Emergency Navigation
Two network graphs Communication graph and guidance graph
room room
room room
room room
room room
Communication graph Guidance graph
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Environment Setting
Deploy sensors Construct reporting tree Setup initial navigation paths
navigating
reporting
10
Outline
Introduction System overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion
11
Deployment of Sensors
Plan locations of sensors Define the roles of sensors
Sink Exit sensors Normal sensors
Decide navigation links
navigationlinks
(for human)
12
Construct a Reporting Tree
Step 1. Discover symmetric links Each sensor periodically broadcasts HELLOs When receiving a HELLO, sensors reply ACKs After receiving an ACK, sensors record the sender ID in its
link table
HELLO
ACKACK
ACKLink table
1 02
3
2 3
13
Construct a reporting tree (cont.)
Step 2. Construct a spanning tree Sink floods a BEACON. For a sensor receives a BEACON, it checks if the sender is
in its link table If yes, it sends a REG(ister) to sink and rebroadcasts BEAC
ON. Else, drops it
BEACON
REG
BEACON
15
Outline
Introduction System overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion
16
Reporting Issues
How often a report should be sent? Will each sensor report individually? Is there any inaccuracy? False alarm? How to save energy of sensors?
17
Outline
Introduction System overview Environment setting Regular report Emergency navigation in 2D environment Simulation results Demonstration Conclusion
18
Design Principle
When a sensor detects an emergency event, it forms a hazardous region
The navigation algorithm will try to guide people as farther away from hazardous regions as possible
19
Problem Formulation
Each sensor has an altitude. Sensors in hazardous regions will raise their altitude
s. Each sensor guides people to the neighbor with the l
owest altitude After forming hazardous regions, some sensors may
become local minimum ones A partial link reversal operation is performed to solve this pr
oblem
20
Phases of Navigation
Initialization phase Initial phase is started by Exit sensor After this phase, every sensor has a default guiding directio
n.
Navigation phase This phase starts by the sensor which detects an emergen
cy event.
21
Terminology
D : The radius of the hazardous region Aemg : A large constant which represents the maxim
um altitude Ai : The altitude of sensor i
Ii : The altitude obtained in the initialization phase
ej,i : The hop count from emergency sensor j to sensor i
22
Initialization phase
Every exit sensor sets its altitude to 0 and broadcasts an initialization packet.
When receiving an initialization packet, a sensor adds its hop count by 1.
Then, it compares the hop count with its current altitude
1
3 4 5
6 7 8
2
0 0Initial Packet0
∞ ∞ ∞
∞ ∞ ∞
∞ ∞ ∞
00
Initial Packet
Sender ID Exit ID Hop Count
23
Initialization phase (cont.) If the hop count is smaller than its altitude, it resets its altitude an
d setups its initial guiding direction to that sender. Then, it rebroadcasts this packet.
1
3 4 5
6 7 8
2∞ ∞
∞ ∞ ∞
∞ ∞ ∞
0 1
1
0 0Initial Packet0
0 1Initial Packet3
0 1Initial Packet1
2
2
2
3
3
0 2Initial Packet2
0 3Initial Packet5
4
0
24
Navigation phase
When a sensor x detects an emergency, it will set its altitude to the maximum altitude Aemg (let it be 200).
Then it broadcasts an emergency packet EMG(seq, x, x, Aemg, 0)
seq : sequence number x : emergency ID w : sender ID Aw : altitude of sender h : hop count to emg. location
23 24 25
26 28
29 30 31
2727 27
EMG0 200 0
10 11
11 12
12
12 13
13
14
200
x w
EMG
Seq Aw H
25
Navigation phase (cont.) When a sensor node y receives a EMG packet originated from
node x, it will do the following steps. Step1:
Decide that the emergency is a new one or not If it’s a new emergency, record this event and set the hop count ex,y to h+1.
Else, compare the h and ex,y. If h is smaller than ex,y , set ex,y to h+1.
Record the altitude (Aw) in the navigation link table.
Emg Table
EmgID ex,y
23 24 25
26 28
29 30 31
27
10 11 12
12 13
13
14
11 200
Emg Table
27
EmgID ex,y
1
26
Navigation phase (cont.) Step 2:
If eX,Y was changed in step1 and eX,Y D, y considers itself withi≦n hazardous region. Then it re-calculates its altitude as follows :
Emg Table
27
EmgID ex,y
1
Safety Factor D:1
ex,y < D ?
23 24 25
26 28
29 30 31
27
10 11 12
12 13
13
14
11 200
2
,
1max ,
1y y emg y
x y
A A A Ie
2
,
2
1
1
1200 11 61
1 1
emg y
x y
A Ie
61 63
63
61
27
Navigation phase (cont.) Step 3:
If y has a local minimum altitude and it’s not an exit, it must adjust its altitude as follows :
= altitudes of y’s neighbors STA = standard deviation
A bigger value means closer to the hazardous region. So we need to adjust the altitude faster.
|Ny| = number of neighbors of y. A smaller | Ny | means less escape ways. So we need to adjust the altitude faster.
δis a small constant.
1( ) min
y yy N N
y
A STA A AN
yNA
23 24 25
26 28
29 30 31
2720061 63
63
61
12
1210
14
Local minimum?10 63 0.1 63.1
2
63.1
Static adjustment
Our scheme
Five iterations
Three iterations
28
Navigation phase (cont.) Step 4:
y has to broadcast an EMG(seq, x, y, Ay, ex,y) packet if any of the following conditions matches. It’s a new emergency y has changes its altitude or ex,y in the previous steps.
Step 5: If y is in hazardous regions and it sees an exit sensor which is
in Ny and which is also in hazardous regions, then y chooses this exit sensor
In all other cases, y directs users to a safer sensor first, and then gradually to a safe exit.
34
Outline
Introduction System overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion
35
Simulation results
We compare our navigation algorithm with “Distributed algorithm for guiding navigation across a sensor network” (MobiCom 03)
This algorithm guides people to the nearest exits However, nearest exits may not be good choices
36
Simulation results
Case1. Our algorithm will choose to pass hazardous region areas as farther away from emergency locations as possible.
Case2. Our algorithm will not guide people passing through the hazardous region.
Case3. Only the sensors near the exit in the hazardous region will guide people to that exit.
Exit Emergency Hazardous region
742 137
PathPkt.
count
Method of Li et al. Our method (D=2)
3
NoPath
Pkt. count
AA
979 2521
1254 4082
37
Outline
Introduction System overview Environment setting Regular report Emergency navigation service Simulation results Demonstration Conclusion
38
Demonstration
System Components MICAz sensors
Environment monitoring Navigation Sink
MIB510 serial Gateway Gateway between wireless sensor network and PC
PC Control Host
40
A Short Summary (2D)
Novel indoor monitoring and navigation services based on wireless sensor network technolgoies emergency will raise sensors’ altitudes navigation similar to TORA protocol, but different in that emergen
cies will disturb altitudes altitude adjustment is designed for quicker convergence navigation in emergency applications requires safer paths, but no
t necessarily longer paths
41
Emergency Navigation in Indoor 3D Environments by Wireless Sensor Networks
Yu-Chee Tseng
Department of Computer Science
National Chiao Tung University
42
Introduction Why 2D guiding algorithms can’t directly apply to 3D environments
room
room
room room
room room
2F
room room
room room
3F
room
room
1F
1F
room
room
2F
Rooftop
room
roomroom
room
room
room
43
System Architecture
Controller
SinkControl host
3F
room
room
room
room
2F
room
room
room
room
1F
room room
4F
room
room
room
room
exit sensorstair sensornormal sensorguidance direction
room room
to rooftop
to rooftop
B
AC
C
A
A
A
A
A
D
D
A: floor gatewayB: stair gatewayC: floor/stair gatewayD: floor/roof gateway
(0, 0) (0, 1)
(1, 0)
(0, 0)
(0, 2)(0, 0) (0, 1)
(0, 1)(0, 1)
(0, 2) (0, 3) (0, 2) (0, 1)
(0, 2)(0, 1)(0, 2)
(1, 1)
(1, 0)
(1, 2)(1, 2) (1, 3)
(1, 1)(1, 1)
(1, 2) (1, 3) (1, 2) (1, 1)
(1, 2)(1, 3)(1, 2)
(2, 1)
(2, 0)
(2, 2)(2, 2) (2, 1)
(2, 1)(2, 1)
(2, 2) (2, 3) (2, 2) (2, 1)
(2, 2)(2, 3)(2, 2)
(2, 0)
(3, 1)
(3, 0)
(3, 2)(3, 1) (3, 2)
(3, 1)(3, 1)
(3, 2) (3, 2) (3, 1) (3, 1)
(3, 1)(3, 0)(3, 1)
(3, 0)
(lemg, -(lIy+1))
(lemg, -(lIy+1))
44
Guidance initialization
(0, 0) (0, 1)
(0, 2)(0, 1)
(0, 2)
(1, 0)
(0, 3)
(1, 1)
(1, 1)
1F
2F
a
b
c
d
e
f
45
Guidance initialization
3F
room
room
room
room
2F
room
room
room
room
1F
room room
4F
room
room
room
room
room room
(0, 0) (0, 1)
(1, 0)
(0, 0)
(0, 2)(0, 0) (0, 1)
(0, 1)(0, 1)
(0, 2) (0, 3) (0, 2) (0, 1)
(0, 2)(0, 1)(0, 2)
(1, 1)
(1, 0)
(1, 2)(1, 2) (1, 3)
(1, 1)(1, 1)
(1, 2) (1, 3) (1, 2) (1, 1)
(1, 2)(1, 3)(1, 2)
(2, 1)
(2, 0)
(2, 2)(2, 2) (2, 1)
(2, 1)(2, 1)
(2, 2) (2, 3) (2, 2) (2, 1)
(2, 2)(2, 3)(2, 2)
(2, 0)
(3, 1)
(3, 0)
(3, 2)(3, 1) (3, 2)
(3, 1)(3, 1)
(3, 2) (3, 2) (3, 1) (3, 1)
(3, 1)(3, 0)(3, 1)
(3, 0)
46
Principles of 3D guidance
A sensor is located in a hazardous region if it is D hop away from the emergency point or it’s a stair sensor and its downstair sensor is in a hazardou
s region
When guiding Avoid to guide people through hazardous regions Try to guide people to the exits on the ground floor Guide people to rooftop if there is no proper ways to downs
tairs
47
Simulation results
1F
3F
2F
4F
1F
3F
2F
4F
1F
3F
2F
4F
1F
3F
2F
4F
1F
3F
2F
4F
1F
3F
2F
4F
roof gateway go upstairs go downstairs
48
Prototyping
We have implemented our system using MICAz motes and MTS310 sensors on TinyOS.
Protocol stack
Physical layer and Data link layer
TreeReconstruction
Deployment GUINetworkinitialization
Guidanceinitialization
Query
Sensor taskGuidance
service
Symmetric linkdetection
Tree maintenance
HELLO Report EMG
Application-level UI
Application layer
Network layer
Sensors partUsers part
Physical layer and Data link layer
TreeReconstruction
Sensor taskGuidance
service
Symmetric linkdetection
Tree maintenance
Guidance interface
HELLO Report EMG
(a) Sink (b) Sensor
49
JAVA GUI
Building plan panel
sink
Control panel
Monitor panel
Current guidance direction
exit
EMGstair
stair
stair
→ 21 (in dec.)
51
Demonstration
Environment A virtual 2-store
building
Sink
Control host
Exit
Exit
Exit
ExitStair
Stair
Stair
Stair
53
More Results
2F
1F
Stair sensor Exit sensor Emergency
Guidance pkt. count 151.8
Tree Reconstruction pkt. count 7.6
Guidance pkt. count 237.8
Tree Reconstruction pkt. count 16.5
Guidance pkt. count 78.8
Tree Reconstruction pkt. count 4.8
(a) (b) (c)
3F
roof
roof
54
Conclusions
Extending 2D navigation to 3D navigation
on each floor, the navigation is similar to 2D
stair and gateway sensors are paid of special attention
roof is also paid of special attention
55
References
Q. Li, and et. al, “Distributed algorithm for guiding navigation across a sensor network”, MobiCom 03.
Y.-C. Tseng, M.-S. Pan, and Y.-Y. Tsai, “A Distributed Emergency Navigation Algorithm for Wireless Sensor Networks”, IEEE Computers, Vol. 39, No. 7, July 2006, pp. 55-62.
M.-S. Pan, C.-H. Tsai, and Y.-C. Tseng, “Emergency Guiding and Monitoring Applications in Indoor 3D Environments by Wireless Sensor Networks”, Int’l Journal of Sensor Networks, Vol. 1, Nos. 1/2, pp. 2-10, 2006.