(1) Collecting quantitative data
Hearing comments and feedbacks from Pecha-Kucha presentation was really helpful for reexamining my project in general. Since then, I have been investigating how do NYPD make decision on installing surveillance camera. Apparently, they say it depends on crime rate. However, so far, I could not find any accurate crime rate number for this. It might be helpful if there is statistics for every each street corner. Then I can put the data on camera locations. But NYPD open crime statistics for every precinct, which is a large area. And there are other possible factors for making decision on installing surveillance camera. For example, Lower Manhattan is full of CCTVs for the sake of defending economic infrastructure from terrorists’ attacks, not because crime rate is high there. Since the process of installing surveillance camera is related to Counterterrorism and Homeland Security issue, some of the process is veiled and hard to know. I have to make a decision on this: should I keep trying to collect such data?
(2) Collecting qualitative data
Still, I believe interviewing average people in the neighborhood will be interesting and helpful for my project. Questions will be: do you think this neighborhood is unsafe? How do you feel about the surveillance tower? Do you know when it installed? Did you know about camera presence? etc.
(3) Identifying camera locations; how can I differentiate fixed cameras and mobile cameras?
When I actually walked the streets of Corona, I saw cameras on mobile vehicles. This gets my mapping project complicated. How can I map the moving cameras? Doable option for me is visiting the site as frequently as possible and taking notes what time they were there. And I would need to use different marks (i.e. flickering mark for mobile cameras) for fixed cameras and mobile cameras.
(4) Identifying network channel
I think one of the distinctive aspect of NYPD surveillance network is, it is all connected in one system and enables realtime reactions. Cameras are connected to wireless video transmitter. In this case, network channel is an important infrastructure and I would love to investigate on it. I know NYPD uses I-NET as a part of their communication channel. Would it be helpful to investigate the infrastructure of I-NET? I need more information on this.
(5) investigating camera’s capacity
This idea came out from the Pecha-Kucha presentation – visualizing the area that cameras can see. Work on progress.
(6) news articles/video reports
I found out that news articles are helpful for showing things unreachable to me. For example, news articles or video channel of NYPD shows the inside of Real Time Crime Center.
Surveillance Data Center
Surveillance Data Receivers
Type of cameras: camera / camera installed on tower (skywatch)/ camera installed on vehicle, etc.
Type of data center: NYPD headquarter
Type of data receivers: regional offices, individual police officers with notebook, etc.
Crime Rates (?)
News Reports/ Video Reports