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Digital Neighborhood Watch: Investigating the Sharing of Sensed Data amongst Neighbors A.J. BrushJaeyeon JungRatul MahajanFrank Martinez.

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Presentation on theme: "Digital Neighborhood Watch: Investigating the Sharing of Sensed Data amongst Neighbors A.J. BrushJaeyeon JungRatul MahajanFrank Martinez."— Presentation transcript:

1 Digital Neighborhood Watch: Investigating the Sharing of Sensed Data amongst Neighbors A.J. BrushJaeyeon JungRatul MahajanFrank Martinez

2 Inspiration

3 Digital Neighborhood Watch +

4 1)Providing digital evidence of incidents 2)Increasing visibility of neighborhood activity 3)Automatically detecting and alerting for suspicious events

5 Social Feasibility? Does the perceived value of DNW outweigh the privacy and security risks of sharing camera data?

6 Related Work Highlights Technology that supports community policing should facilitate communication and discussion Lewis & Lewis, CHI 2012 Community mailing lists facilitate interaction and collective action “Netville” & Blacksburg Electronic Village Studies Value of human monitoring of CCTV to detect incidents and challenges around managing digital evidence Tullio et. al, CHI 2010

7 Social Feasibility? Does the perceived value of DNW outweigh the privacy and security risks of sharing camera data?

8 Method High-crime neighborhood In Region Interviews with 11 households: Block watch/Neighborhood association members 5 in High-crime neighborhood 6 with security systems house Share with Neighbors? Sharing Chart

9 Sharing options “Always”, “Sometimes” (by request or under specific circumstances), “Never” Low-resolution

10 Sharing options “Always”, “Sometimes” (by request or under specific circumstances), “Never”

11 Limitations Participants reactions could be speculation – Interface mock-ups, maps of their own house, showed data from existing surveillance cameras – Recruited households in neighborhood groups Relatively small numbers of households in a few neighborhoods

12 Household Sensing Systems Desired All households except one interested in cameras 4 outdoor cameras (median): Front yard, back door, side yards Audio data for gunshots, glass breaking (9 HH) Security and non-security benefits

13 Trust Not Proximity for Sharing Existence Hypothesis: People would treat households in view of cameras differently Wrong! Neighbors grouped based on trust Existence of cameras shared with trusted neighbors (9HH) 5 households renamed proximate neighbors to “trusted neighbors” in chart Concerns of perceived spying, dangerous households.

14 Reluctance to Share Field of View Divulging Field of View shows neighbors the blind spots No household would share field of view with neighborhood group Foreground only was introduced to address this concern

15 Reluctance to Share Field of View Divulging Field of View shows neighbors the blind spots No household would share field of view with neighborhood group we want to tell that we have a camera, we just don’t want to tell them where it is. And this way we could show them the guy in the yellow shirt, but they wouldn’t know [the FoV]” Foreground only was introduced to address this concern

16 Digital Neighborhood Watch 1)Providing digital evidence of incidents 2)Increasing visibility of neighborhood activity 3)Automatically detecting and alerting for suspicious events

17 Share Evidence With Reason All ten households would share for evidence ! Good reason required One more comfortable with police than neighbors “if it was a murder, whether I didn’t like you or not, I’d probably still share that information” “I feel more comfortable sharing the images with the police department because they’re the ones who need to take the action.”

18 Limited Willingness to Share Access Three households while on vacation Two would trade data “Public-only” view was more acceptable to a few households – Three would always share with trusted neighbors and law enforcement

19 Cautious Interest in Suspicious Activity Detection Five households (4 high-crime) would share events on ongoing basis for pattern detection Seven share high-fidelity for specific requests (police looking for car, child) Lots of concerns about how it would actually work, false alerts…

20 Neighborhood Types vs. Acceptability of DNW Broad similarity in attitudes we found in high and low crime neighborhoods. – equally willing to share data for evidence – interest in sensing audio was present in both types Unique to high crime neighborhood: – willingness to share events with a detection service on an ongoing basis (4 of the 5 households from the high crime neighborhood were interested) – hidden cameras

21 Complex Neighborhood Trust Let neighbors build their own sub-networks Increased concern about renters

22 Implications for other neighborhood sharing systems? Other neighborhood data could be shared – water, electricity, commute patterns, … Our findings suggest avenues of exploration: – Share based on specific events rather than ongoing anonymized information – Look for abstraction that preserve appropriate levels of privacy.

23 Work in Progress Social Feasibility – Cautiously optimistic, particularly with processed views Technical Feasibility – What can be recognized from video or audio semi-reliably? – Soon running in our houses More generally, this is one possible application on

24 Thanks. A.J. BrushJaeyeon JungRatul MahajanFrank Martinez


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