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Help Me: Opportunistic Smart Rescue Application and System Osnat (Ossi) Mokryn, Dror Karmi, Akiva Elkayam, Tomer Teller.

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Presentation on theme: "Help Me: Opportunistic Smart Rescue Application and System Osnat (Ossi) Mokryn, Dror Karmi, Akiva Elkayam, Tomer Teller."— Presentation transcript:

1 Help Me: Opportunistic Smart Rescue Application and System Osnat (Ossi) Mokryn, Dror Karmi, Akiva Elkayam, Tomer Teller

2 Chile 2010 Japan 2011 Haiti 2010 Indian Ocean 2004 China 2010 Turkey 2011,2012 Disaster Areas

3 When disaster strikes  Communication infrastructure is damaged  Rescue forces take time to arrive, organize First hours are crucial  Skilled people, no communication  Everybody (almost) has a smartphone with 802.11  How do we enable smart communication between people over the spontaneously formed ad-hoc 802.11 network of smartphones?

4 HelpMe In a Nutshell A self-learning ad-hoc network of smartphones formed opportunistically Smart communication: A request is delivered to the best matching person that is close enough Messages are forwarded based on matching of user generated content to users’ skills Ad-hoc routing based on our matching algorithm within the opportunistic network Messages are routed to the best receiver  The network is unlimited in size, locality considerations

5 Problem Formalizing Unlimited number of people, with different skills  Nodes number is not bounded (N)  Each node has a set of skills |k|={0,1,...K}  No global knowledge People can ask or request anything  Unlimited number of possible classifications  Spontaneous requests, no local \ global knowledge Power limitations at some or all of the nodes

6 Scenario Limitations Let us consider a cloud-based Q&A scenario  Questions are classified using Google  “Apple” is 50% hi-tech, 50% fruit  Matching can be based on  Users’ ratings, location, etc.  Overall knowledge Crisis situation  Classification based on local dictionary

7 Prerequisites When a user registers and downloads HelpMe:  Cloud service. Please be prepared.  Specifies skills  Can be automated with corresponding agencies  Service creates  A list of categories of skills (or none)  Tailored dictionary for classification  Downloaded app is tailored to each user

8 Local Tailored Dictionary Classification requires a dictionary Smartphones are limited in resources  Memory, power consumption Per user tailored dictionary created at registration  Either skills-based or general Classification using local dictionary

9 Classification Accuracy Obtained With Tailored Partial Dictionaries Based on globally available general database with categories

10 Rescue Categories Root Non-specific MedicalRescue Law & Order xxxxxxxfirexxxx water? rescu e emergency Hierarchy of categories Each category is divided to several sub- categories

11 When a disaster strikes.. Activate app Smartphone is used in a peer-to-peer mode over the spontaneous opportunistic ad-hoc network formed by the app Requests are generated spontaneously upon need Neighboring devices exchange skill sets and location coordinates during a short hello

12 Initial hello - exchange skill sets WiFi: received power (in dBm) decays ~ as a function of the log of the distance.Each 802.11b hop: indoor 50m, outdoor 80-120m

13 Questions Classification Each word is classified and returns its set of values per category (if at all)  Using a Naive base classification The union of all values per category is calculated: Resulting classification  Only the highest category is chosen and published  The n-th top categories are chosen and published

14 How to Match? Matching algorithm tries to route to best matching person to help  Compares classified query categories to neighbors skills A nearby may seem able to help, but doesn’t..  Create ranks per skill per person  Prefer a highly ranked neighbor

15 Ranks Each node’s set of skills are assigned ranks A rank corresponds to the user’s  Responsiveness  Quality of help To enable ranking a feedback mechanism must be employed (i.e., ) Root Rescue fire rescu e 4 0 4 4

16 Matching Algorithm Given a peer k with m subscribed interests: Given a request R is classified to categories as follows: The request R is matched to peer k if: where T is a predefined threshold

17 Matching Based Routing A request is classified at the sending side Categories are matched to neighbors ranked skills Forwarded (directly) to best matching neighbor Re-classification at receiving node Forwarding (directly) if a better matching exists AND {number of hops} < Threshold ==> End receiver is the best possible match

18 User Controlled Load Users can control their received load automatically  A highly skilled professional who helps can be overloaded An availability setting determines load:  Accept all: users become forwarding hubs.  Accept by skills: normal matching  Accept by expertise only: filter out non-specific requests within expertise  Accept only emergency

19 iPhone Implementation

20 Haggle: A publish-subscribe middleware for exchanging interests [Diot et al., 2006]. MobiClique: Middleware for Mobile Social Networking Users that share interests are notified of each other The MobiSoC Middleware for Mobile Social Computing: Challenges, Design, and Early Experiences Applications Using Haggle to Create an Electronic Triage Tag Socially-Aware Routing for Publish-Subscribe in Delay-Tolerant Mobile Ad Hoc Networks (predict routing according to social knowledge)

21 Smartphone App Lifecycle

22 Initial Screens

23 Experiments: The effects of Availability on Load 4 devices corresponding to 2 skilled personnel and 2 victims 4 different experiments with different availability settings

24 Server Post- Processing All communication is stored locally When the server is available, everything is upload to it Location of all neighbors through out crisis  Missing people services Stats

25 Conclusions We presented a tailored application  Applicable also to rural areas, hiking, etc. The solution is general for any spontaneous ad-hoc opportunistic network  Who wants to go play tennis/ swim?  Who wants to share a taxi to Larnaka?  Where can I find a good sea-food restaurant around? Ranking makes it reliable

26 Thank you. Questions?

27 Our HelpMe System Efficient the emergency service Creates on-the-fly routes between people Finds the most suitable person to help within a neighborhood Post event, when communication is restored  Analyze the events  Help in locating lost people


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