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MobEyes : Smart Mobs for Urban Monitoring with a Vehicular Sensor Network

MobEyes : Smart Mobs for Urban Monitoring with a Vehicular Sensor Network. Aditya Wagh. Issues with Evidence Collection. Importance of Evidence Collection Present Systems are inadequate Closed Circuit TV Scalability issues + Centralized operation Untapped vehicular resources.

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MobEyes : Smart Mobs for Urban Monitoring with a Vehicular Sensor Network

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  1. MobEyes: Smart Mobs for Urban Monitoring with a Vehicular Sensor Network Aditya Wagh

  2. Issues with Evidence Collection • Importance of Evidence Collection • Present Systems are inadequate • Closed Circuit TV • Scalability issues + Centralized operation • Untapped vehicular resources

  3. An Introduction to VANETs • Vehicular Ad Hoc Networks • Sensors placed on cars • Highly mobile • Relaxed constraints on computing power, storage capacity and power consumption • Massive number of vehicles+ nodes = large coverage

  4. Advantages of Mobile Nodes • Less vulnerable to attack • Scalable • Multiple sensors might be tracking a Target • In this case, VSN is built on top of VANET (basic communication capability)

  5. MobEyes System Requirements • Sensors deployed on vehicles • Collect data and process locally • Summary Repository • Summary Collection

  6. Summary Harvesting • Bloom Filtering • Police vehicles broadcast Bloom signatures • Other vehicles compute missing packets • One vehicle will reply with necessary packets • Police vehicle will respond with ACK carrying list of received packets • On repeating this 5 times, the packet loss due to false positives is 10^(-12)

  7. Performance Evaluation • Vehicles have 802.11 connectivity • 11 Mbps • Radio range: 100 – 300 meters • Speed: 10 m/s • Real map of Westwood 2400 x 2400 • Real Track model used

  8. Summary of MobEyes • Presents an opportunistic and decentralized approach to evidence collection / monitoring • System is shown to be scalable up to thousands of nodes • VANET implementation is still pending and will take over a decade once these systems are put into production

  9. Thank you for listening

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