Transcript Slide 1

Indian Institute of Technology Kharagpur
Indian Institute of Management, Kolkata
Bengal Engineering and Science University, Shibpur
National institute of technology, Durgapur
Heritage Institute of Technology, Kolkata
Kalyani Government Engineeting College, Kalyani
Personal Background
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Indian Scenario Disaster management…. (personal
experience)
Scenario
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User Meet
Advanced Country and Backward
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Case study to bring out contrast and hopes
Motivation
Summary of criticisms
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No comparison or mention of the recent Japan
disaster (A.2)
Lack of a detailed sketch of the architecture to be
deployed (A.1, A.3)
Absence of a precise problem definition (A.4-A.6),
(B.1, B.2)
Our connections with the disaster relief personnel
are not clearly stated (C.1, A.9).
Communication infrastructure (A.1 –
A.3)
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No cellular infrastructure
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We propose latency-aware ad-hoc network architecture
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SP – Shelter points
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MCS – Master control Station
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Four tier architecture
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Communication infrastructure (A.1 –
A.3)
Tier - 1: Rescue personnel carrying smart phones that can
form a DTN; exchange information among themselves
through the DTN
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Tier -2: Message packets shall be unloaded into Throwboxes
belonging to SPs
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Tier – 3: Communication among far apart Throwboxes shall be
facilitated through Data Mules
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Tier – 4: One of the Throwboxes within a small group shall be
elected as the center to communicate through Wi-Fi (Line-ofSight) devices with other groups as well as with the outside
world
TB
TB
Group Center
Group Center
MCS
Group 1
Group 2
Communication infrastructure (A.1 – A.3)
Four Tier hybrid Architecture using DTN Nodes, ThrowBoxes(TBs),
DataMules(DMs) and WiFi Towers(WTs)
[Saha 12] S. Saha, V. K. Shah, R. Verma, R. Mandal, S. Nandi,” Is It Worth Taking A
Planned Approach To Design Ad Hoc Infrastructure For Post Disaster
Research problems: 4 tier architecture (A.5, B.1)
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Given a (i) initial disaster hit area map which can be realized as a graph G(V,E), where V=
{set of ThrowBox (TB) at each shelter point} and E={set of pathways among those TB}. (ii)
finite pool of resources and (iii) load (function of no of victims and size of an affected area
which is under coverage of one Throwbox) -- what is the minimum achievable latency (L)
such that almost 100 % packet delivery is ensured?
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Conversely for aforesaid graph with given (i) latency, and (ii) load -- what is the optimal
number of network resources that are required to ensure almost 100 % of packet delivery?
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As disaster hit area may change with time it is also important to answer with existing network
setup and given resource what is the minimum achievable latency with least/ tolerable
movement of resources to ensure almost 100% of packet delivery?
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Designing the mixed-mode routing protocol lie in dealing with tradeoff between
fairness and prioritized access, protocol inter-operability, authentication, universal
user/device identity, group multicast, etc.
Our System Model
Affected Area
MCS
20 KM
24 KM
Input Parameters
Area
480 Sq KM
Location
Sundarban
Number of TBs
19
Location of TBs
Given
Location of MCS
Given
No of DTN nodes
10 DTNs/TB
Traffic Rate
4 Packets/hr/DTN
11 Packets/hr/DTN
Mobility Model
Post office cluster
mobility model
Simulator
Enhanced ONE
Simulator
List of
Components
DataMules(DM)
Quantity
WiFi Tower
7
11
2 hrs 40
mins
latency
3 hrs 20
mins
latency
Required Resources for Satisfying 3hr 20 minutes & 2 hrs 40 Minutes Latency
List of
Components
DataMules(DM)
Quantity
WiFi Tower
8
11
Comparison between Planned & Random Placement with 3 hrs
20 minutes Latency
Planned Approach
Random Approach
Time vs. Delivery Probability for Planned and Unplanned Approach
Topological change towards betterment with Time Keeping Same Latency Constraint
Improved Topology
Initial topology
Degradation of delivery probability due to
Deployment Overhead for topological
changes
Time vs. Delivery Probability with Low Load
Google Map Based User Interface for
Network Resource Planning
Feeding Input
Highlighting Activity Area and Variable Constraints are Fed
ThrowBox & Shelter Point Creation
SP and TB are Drawn on Google Map using Google Map
API
Determining Distance
Finding out the Geographical and Geodesic Distance between TB’s
for each Combination
Group Formation
TB’s form various groups as per the Heuristic
Approach Adopted & Wi-Fi Tower is placed on the
Group Center
Finding Data Mule Trajectory
Finding DM trajectory and the number of DM required for
each group
Location awareness
Problem Definition
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Build an annotated people/resource map
Approximate position of the victims and the resource
situation shall be highlighted on a time-varying basis
Location awareness
Solution
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Physical co-ordinates provided by smart-phones
carried by rescue workers shall serve as anchor points
Clever Crowd Sourcing to identify other users.
Location awareness
Caveats
GPS Constraints
 Many mobile phones (Give a snapshot of your phone) cannot
do GPS localization without wireless connection
 Atmospheric Condition hinders GPS localization
Mobility and Delay
 Delay in aggregating the data brings in accuracy as the
user has already moved from the reported position
Location awareness
Proposed methodology
Mobility induced error correction
Movement is predominantly deterministic
Landmark based localization
Annotate the disaster prone area graph with landmarks
Identify them as anchor points
Location awareness
In-built sensors of smart phones produce/identify
anchor points
Gyroscope, accelerometer – can sense turns/bumps on
roads
Relative humidity sensor – can sense the presence of
a place like pond
Barometric sensor / gravity sensor – can sense the
different floors of a building
Initial study: landmarks of the 2nd floor of
the CSE Department, IIT Kharagpur
 Phone : Samsung Galaxy S2
i9100G
 Platform : Android 2.3.6
 App Used : SensoSaur
CSE IIT Kgp 2nd Floor Plan
28
Toilet
Starting/Ending Pt.
Swadhin
7/17/2015
Landmarks using GSM signal strength
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(Manual)
Strongest
(15-22)
Weakest (712)
Landmarks using Wi-Fi (Manual)
Linksys,Research,HWLAB
,58.x AP
30
Linksys,HWLAB,Res
earch,Abhishek_PC
Linksys,HWLAB,Res
earch
Linksys,HWLAB,Research
,Abhishek_PC,58.x AP
Landmarks using light (Day)
31
Highest Light
Highest Light
Lowest Light
Landmarks using light (Night)
32
Bright (Tube
Light)
Dark (No
Tube Light)
Landmarks using
33
Gyro/Lacc/Magnetometer/Rotation
vector
Using online social media to gather
authentic situational information (A.4)
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Good indicators of the situation of victims of manmade calamities – victims themselves can tweet
about the extent of damage caused and the specific
help required
Recent studies show that 30% of tweets posted
immediately after calamities contain situational
information …
But only 17% are credible
Using online social media to gather
authentic situational information (A.4)
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Research questions
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Judge credibility of the tweets posted immediately after a
calamity
Retweets not a good metric since rumors might also get
retweeted millions of times
Proposed: identify authoritative experts on calamities
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Challenge – to discover such experts in Twitter
Utilize knowledge of location of the person posting a tweet
Analyze local flow patterns
Sensor information can be coupled with tweets
Example of rumors after Blasts in Mumbai
http://blogs.wsj.com/indiarealtime/2011/07/15/mumbai-blasts-did-twitter-really-help/
Example of rumors after terrorist attack
http://www.in.com/news/current-affairs/mumbai-blast-13th-and-on-kasabs-birthday-19724405-in-1.html
Examples of rumors after UK Riots
http://www.guardian.co.uk/uk/interactive/2011/dec/07/london-riots-twitter
Examples of rumors after UK Riots
Comparison with relief measure
earthquake
Japanese
India and other
developing countries are still not equipped
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with an organized post-disaster relief programme
Japan enjoys
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State and private machineries,
Huge economic power,
A strong socio-cultural backbone
to combat with post-disaster situation that is non-replicable in
the context of India
Japan use UAVs (unnamed aerial vehicles ) and under water
robots to analyze post-disaster situation and fix damaged
cables
The economic strength of India does not allow of such an
infrastructure and an alternative could be to use smart-phones
(augmented with various sensors) to design low-cost (possibly
not the best) solutions
Online social media:
Source
of authentic situational information
 Works as good indicators of the situation of victims
of man-made calamities – victims themselves can
(A.4)
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tweet about the extent of damage caused and the
specific help required
Recent studies show that 30% of tweets posted
immediately after calamities contain important
situational information
Research questions – credibility of the tweets
posted
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Retweets -- not a good metric since rumors might also
get retweeted millions of times
Rumors about disaster on
the social media (Mumbai Blast)
 http://blogs.wsj.com/indiarealtime/2011/07/15/mumbai-blasts-did-twitter-really-help/
Rumors about disaster on
the social media (Mumbai Blast)
http://www.in.com/news/current-affairs/mumbai-blast-13th-and-on-kasabs-birthday19724405-in-1.html
Rumors about disaster
on the social media (UK Riots)
http://www.guardian.co.uk/uk/interactive/2011/dec/07/london-riots-twitter
Rumors about disaster
on the social media (UK Riots)
Online social media:
Source
oflocal
authentic
situational
information
 Identify
authoritative
experts – difficult
to
track since Twitter-like social media are full of
(A.4)
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celebrities that completely shadow the presence of
these experts
Challenge – to discover such experts
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Analyze local flow patterns
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Sensor information can be coupled with tweets
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Relevance of a tweet reporting a damage can be better
judged if the location information of the person tweeting
is available.
Comparison with relief measure
earthquake
Japanese
India and other
developing countries are still not equipped

with an organized post-disaster relief programme
Japan enjoys

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



State and private machineries,
Huge economic power,
A strong socio-cultural backbone
to combat with post-disaster situation that is non-replicable in
the context of India
Japan use UAVs (unnamed aerial vehicles ) and under water
robots to analyze post-disaster situation and fix damaged
cables
The economic strength of India does not allow of such an
infrastructure and an alternative could be to use smart-phones
(augmented with various sensors) to design low-cost (possibly
not the best) solutions
Collaboration and management plan:
Past
Experience
(Research)
 A Secure Decentralized Disaster Management
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Information Network using Rapidly Deployable
Wireless and Mobile Computing Technologies -- A
DIT Funded project successfully accomplished by
Prof. Somprakash Bandyopadhyay (IIM Calcutta),
Dr. Siuli Roy (HIT, Kolkata) and Mr. Sujoy Saha,
NIT Durgapur
Work on directional antenna, DIT funded projects
on peer-to-peer networks, Vodafone funded
projects on mobile communication networks (Prof.
Niloy Ganguly)
Collaboration and management plan:
Past Experience (Field work)
The communication was setup among three island near gosaba using 802.11 enabled
with optilink devices configured in point to multipoint bridge with 15dbi antenna which
was found to be able to cover near about 7 to 8 km range in line of sight. Using this
link voice communication was established with NGOs as shown in figure.
Collaboration and management plan:
On-going work
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IIT Kharagpur
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Comparison of infrastructure for disaster management after
calamities in Japan, Pakistan, Haiti and India
Information dissemination in DTN using bipartite networks
Online social media for gathering situational updates (jointly
with BESU Shibpur )
SensoSaur - Landmark based location tracking
Collaborative download framework
IIM Kolkata
Collaboration and management plan:
On-going work
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NIT Durgapur
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BESU Shibpur
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Layered architecture for post-disaster communication
Disaster management services - Android application
Google map based user interface for disaster management
Using online social media for gathering situational updates (jointly
with IIT Kharagpur)
Installing smart-phone based DTN in disaster-hit region
HIT Kolkata
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Wireless sensor networks – tracking miners and the mining
environment, agro-parameter monitoring system, pollution
monitoring system, traffic congestion detection system
Impact on curriculum
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Study groups
Planet-lab installation
Tweet collection on social media
PG level electives:
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Wireless Networks for Crisis Management: IIM Kolkata +
KGEC
ICTs for Disaster Management: IIM Kolkata + Heritage
Institute of Technology (HIT)
Distributed Systems and Unreliability: IIT KGP + BESU
Impact on curriculum
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Disaster related database development
Building computer solutions
Refresher course (through AICTE)
Recruitment of new faculty members
Summer/winter training programmes
Measure to attract good MS/PhD students
Societal sensitivity development
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Through the established banners of
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A structured list of members (User-Groups)
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Initiative for Community Action (INCA) – IIM Kolkata
National Service Scheme -- IIT Kharagpur
NGOs
Government agencies
Community based organizations
Victims of disaster
First User-Group meeting already held at IIM Kolkata on
March 30, 2012
Four workshops for sensitization planned to be held at
IIT KGP and IIM Kolkata
References
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http://cse.iitkgp.ac.in/resgrp/cnerg/disaster_dtn/