abdelmalek essaâdi university, morroco laboratory...
TRANSCRIPT
Abdelmalek Essaâdi University, Morroco
Laboratory of Information Systems and Telecommunication
The International Conference on Intelligent Distributed Computing - IDC 2012 :
Calabria, Italy, September 24-26, 2012
Sefrioui Imane, Cherrat Loubna, Ezziyyani Mostafa, Mohammed Essaaidi
Natural disasters:
Earthquakes
Tsunamis
Floods
…
Cause huge loss of human
life and property.
Disaster management:
Management of disasters plays a decisive role to minimize the damages.
we propose the development of an intelligent evacuation system for management of flood disasters.
The system proposed is based on Wireless Sensors Network and Multi-Agent Model.
The system gives the best decisions that can be taken in this emergency situation taking into account the changes of the environment. It provides directions to the users for the shortest and less hazardous routes.
Flood disaster occurs in an area.
Firebrigade wants to evacuate a victim.
Firebrigade wastes time seeking for safe path while the hazard has increased.
The victim is in more critical state.
The system gives the safest and shortest path.
Save time.
Evacuate victim fastly.
The firebrigade has time to evacuate more victims.
Around Project: ◦ Autonomous Robots for Observation of Urban
Networks after Disasters.
◦ Focus on Earthquakes.
◦ Developped in GAMA platform.
Robocup Rescue: ◦ Focus on Earthquakes.
An Emergency Response System for Intelligent Buildings: ◦ Focus on evacuation in case of fire hazard in a
building
◦ Indoor navigation
Geographic Information System ◦ The simulation environment should be based on GIS that contains a
complete and reliable spatial data.
Wireless Sensors Network ◦ Sensors are used to monitor the hazards that can occur on road
transport networks and determine the road damage degree.
Multi-agent System ◦ Agents are used to represent various types of actors that interact
inside a virtual world. Agents can communicate and coordinate with each others to make decisions.
Shortest & Safest Path Algorithm ◦ An algorithm to compute the shortest and safest path in an
environment which is subject to continous changes.
We use GIS to represent spatial data.
Each node represents a location where there is a choice of roads to travel on or a terminal extremity of a road.
Each edge represents a straight line of walkway or traffic road.
Sensors deployed in the edge (i,j) and monitors the hazards.
They integrate a unit of environmental data acquisition (temperature, precipitation, water level) that can be transformed into numerical quantities, a processing unit with limited computing power and limited memory, a communication device (radio transmission) and a battery.
They cooperate with each other to form a system called wireless sensors network.
Agents: Victims
Ambulance
FireBrigade
Police
Helicopters
Animals
Vehicles
…
1
4
2
3
Ambulance Police
Hospital Victim
GIS determine the graph.
Cost of every edge: ◦ L(i,j) = l(i, j) . H(i, j)
T(i,j)
l(i,j) = length of the edge
H(i,j) = hazard intensity
H(i,j) ∈ [1, ∞ [
T(i,j) = 1 if the current user can take this edge
0 otherwise
Require the node u
Ensure the next decision node v
Remove node u from the set of unvisited nodes Q
For every neighbors, n of u do
◦ GET H(u,n) from sensor in (u,n)
◦ Compute L(u, n) = l(u, n) . h(u, n) T(u,n)
◦ C(n) min{C(n), C(u) + L(u, n)}
end for
v argmin{Q}
n1
n2
u n3
n4
Require the node u
Ensure the next decision node v
n1
n2
u n3
n4
Require the node u
Ensure the next decision node v
Remove node u from the set of unvisited nodes Q
n1
n2
u n3
n4
Require the node u
Ensure the next decision node v
Remove node u from the set of unvisited nodes Q
For every neighbors, n of u do
end for
n1
n2
u n3
n4
Require the node u
Ensure the next decision node v
Remove node u from the set of unvisited nodes Q
For every neighbors, n of u do
◦ GET H(u,n) from sensor in (u,n)
end for
n1
n2
u n3
n4
Require the node u
Ensure the next decision node v
Remove node u from the set of unvisited nodes Q
For every neighbors, n of u do
◦ GET H(u,n) from sensor in (u,n)
◦ Compute L(u, n) = l(u, n) . h(u, n) T(u,n)
end for
n1
n2
u n3
n4
Require the node u
Ensure the next decision node v
Remove node u from the set of unvisited nodes Q
For every neighbors, n of u do
◦ GET H(u,n) from sensor in (u,n)
◦ Compute L(u, n) = l(u, n) . h(u, n) T(u,n)
◦ C(n) min {C(n), C(u) + L(u, n)}
end for
n1
n2
u n3
n4
Require the node u
Ensure the next decision node v
Remove node u from the set of unvisited nodes Q
For every neighbors, n of u do
◦ GET H(u,n) from sensor in (u,n)
◦ Compute L(u, n) = l(u, n) . h(u, n) T(u,n)
◦ C(n) min {C(n), C(u) + L(u, n)}
end for
v argmin{Q}
n1
n2
u n3
n4
Conclusion: ◦ we proposed a model for computing the shortest
and safest path towards the destination during flood disasters.
Further work: ◦ Select the appropriate sensors for the system and
the areas where to deploy them.
◦ Extend the algorithm : Include expert knowledge.
◦ Implement this model and give results.
