1. By: Tarek Abdelzaher, Yaw Aanokwa, Peter Boda, Jeff Burke, Deborah Estrin, Leonidas Guiba, Aman Kansal, Samuel Madden, Jim Reich Presentation By: Ankit Gupta

2. About the talk: General Idea Why Mobiscopes? Classes of Mobiscopes Common Requirements Mobility and Sampling coordination Heterogeneity Privacy Networking Challenges Human Factors & Social Implications Conclusion

3. General Idea Federation of distributed mobile sensors Why? Covering large areas can be challengeing Unavailability of wired power Expense of purchasing & maintaining enough devices The paper focuses on the challenges and opportunities Mobiscopes pose in human spaces.

4. Classes of Mobiscopes Vehicular Mobiscopes For traffic and automotive monitoring Equipped vehicle senses various surrounding conditions Benefit: Exploit oversampling provided by dense vehicle traffic Examples: Inrix, EZCab, NavTeq, TeleAtlas etc.

5. HandHeld Mobiscopes Could be useful for Monitoring health impact of exposure to highway toxins, Monitoring an individual’s use of transportation systems, Gather real time information about civic hazards & hotspots.

6. Common Requirements Data persistence must be assured Data access tends to be spatially correlated with the user’s location & can change rapidly Human in the loop as an actuator, sensor, interpreter, or responder Sensors & data to be shared by many public and private entities Trust, coordinated deployment and respect of users’s privacy

7. This all leads to: General architecture and design guidelines for future Mobiscopes Component reuse and reduction in development costs Interoperability amongst future systems

8. Mobility and Sampling Coordination Performance depends on patterns of transporters Highly structured (Road traffic) Less structured (foot traffic) Sensor densities Sensing device’s availability can depend on user behavior or device characteristics

10. Application Adaptation Must adapt to network’s available communication characteristics Could buffer data when connectivity unavailable Actuated Mobility Task some or all nodes to visit a specific location to collect information on demand Task actuators to visit some areas either one at a time or as part of a circuit

11. Opportunistic connectivity Building low-level network protocols to quickly identify and associate with nearby node (or networks) Routing algorithms to deliver data through such opportunistic connections Prioritization Buffered data to be prioritized Prioritization to avoid wasting valuable bandwidth when different nodes cover overlapping geographic areas

12. Challenges and opportunities of heterogeneity Mobiscopes take on various topologies & structures Federate devices with different capabilities Draw together components with varying levels of trust & credibility Benefits: Immune to weaknesses of sensing modalities Robust against defective, missing or malicious data sources

14. Heterogeneity of Ownership Individually owned devices Owners might not be trustworthy Might not maintain their devices in good condition Data Resolution & Types Derive & maintain metrics at multiple resolutions Simple interpolations (smoothly varying, temperature) Complex models (faster varying or sparse data)

15. Robustness Model driven approaches like Kalman filters & Particle filters adapt well to irregular sampling

16. Tackling data Privacy People’s ability to control information flow about themselves Definition Inability to publicly associate data with sources could lead to los of context Revealing too much context can potentially thwart anonymity, violating privacy requirements

17. Local Processing Putting the selectivity and filtering capabilities on the end-user Verification Important to develop systems where users can verify data’s correctness without violating the source’s privacy Proper incentives to promote successful participation, prevent abusive access with the purpose of “Gaming the system”

18. Privacy preserving data mining User isn’t willing to share his or her data, but might be interested in the result of aggregation over the target community Could use additive random noise to perturb data withour affecting the statistics to be collected

19. Networking Challenges Shifts the networks main utility from data communication to information filtering Need for network storage as a key service because aggregation and filtering both imply a need to buffer

20. Human Factors and Social implications Considering broader policy precedents in information privacy Extending popular education on IT’s new observation capabilities Facilitating individual’s participation Helping users understand & audit their own data uploads

21. User Interfaces Missing from traditional embedded systems Opportunity for ambient and explicit feedback to the user Help users configure their sensing participation Provide feedback on operational status

22. Conclusion Much research still needs to be done Much work still needs to be done on Platforms & API’s that offer efficient, robust, private & secure networking & sensory data collection in the face of heterogeneous connectivity and mobility

23. Questions ???