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<div class="header reader-header reader-show-element"> <font
size="-2"><a class="domain reader-domain"
href="https://theintercept.com/2020/01/27/surveillance-cctv-smart-camera-networks/">https://theintercept.com/2020/01/27/surveillance-cctv-smart-camera-networks/</a></font>
<h1 class="reader-title">The Rise of Smart Camera Networks, and
Why We Should Ban Them</h1>
<div class="credits reader-credits">Michael Kwet - January 27,
2020<br>
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<p><u>There’s widespread concern</u> that video cameras
will use facial recognition software to track our
every public move. Far less remarked upon — but every
bit as alarming — is the exponential expansion of
“smart” video surveillance networks.</p>
<p>Private businesses and homes are starting to plug
their cameras into police networks, and rapid advances
in artificial intelligence are investing
closed-circuit television, or CCTV, networks with the
power for total public surveillance. In the
not-so-distant future, police forces, stores, and city
administrators hope to film your every move — and
interpret it using video analytics.</p>
<p>The rise of all-seeing smart camera networks is an
alarming development that threatens civil rights and
liberties throughout the world. Law enforcement
agencies have a long history of using surveillance
against marginalized communities, and studies show
surveillance chills freedom of expression — ill
effects that could spread as camera networks grow
larger and more sophisticated.</p>
<p>To understand the situation we’re facing, we have to
understand the rise of the video surveillance
industrial complex — its history, its power players,
and its future trajectory. It begins with the
proliferation of cameras for police and security, and
ends with a powerful new industry imperative: complete
visual surveillance of public space.</p>
<h3>Video Management Systems and Plug-in Surveillance
Networks</h3>
<p>In their first decades of existence, CCTV cameras
were low-resolution analog devices that recorded onto
tapes. Businesses or city authorities deployed them to
film a small area of interest. Few cameras were placed
in pubic, and the power to track people was limited:
If police wanted to pursue a person of interest, they
had to spend hours collecting footage by foot from
nearby locations.</p>
<p>In the late 1990s, video surveillance became more
advanced. A company called Axis Communications
invented the first <a
href="https://www.axis.com/newsroom/article/first-network-camera">internet-enabled
surveillance camera</a>, which converted moving
images to digital data. New businesses like Milestone
Systems built Video Management Systems, or VMS, to
organize video information into databases. VMS
providers created new features like motion sensor
technology that alerted guards when a person was
caught on camera in a restricted area.</p>
<p>As time marched on, video surveillance spread. On <a
href="https://www.amazon.com/Business-Magnetism-Mr-Lars-Thinggaard/dp/0615892140">one
account</a>, about 50 years ago, the United Kingdom
had somewhere north of 60 permanent CCTV cameras
installed nationwide. Today, the U.K. has over <a
href="https://www.bbc.com/news/uk-30978995">6
million</a> such devices, while the U.S. has <a
href="https://technology.ihs.com/583114/north-american-security-camera-installed-base-to-reach-62-million-in-2016">tens
of millions</a>. According to marketing firm IHS
Markit, <a
href="https://www.wsj.com/articles/a-billion-surveillance-cameras-forecast-to-be-watching-within-two-years-11575565402">1
billion cameras</a> will be watching the world by
the end of 2021, with the United States rivaling
China’s <a
href="https://technology.ihs.com/619515/the-us-has-a-security-camera-penetration-rate-rivalling-chinas">per
person camera penetration rate</a>. Police can now
track people across multiple cameras from a
command-and-control center, desktop, or smartphone.</p>
<p>While it is possible to link thousands of cameras in
a VMS, it is also expensive. To increase the amount of
CCTVs available, cities recently came up with a clever
hack: encouraging businesses and residents to place
privately owned cameras on their police network — what
I call “plug-in surveillance networks.”</p>
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<p><img
src="https://theintercept.imgix.net/wp-uploads/sites/1/2020/01/h_15235476-edit-1579897222.jpg?auto=compress%2Cformat&q=90&w=1024&h=682"
alt="Video from surveillance cameras around the
city is displayed at the Real Time Crime Center
the viewing space for Project Green Light, at the
Police Department's headquarters in downtown
Detroit, June 14, 2019. In recent weeks, a public
outcry has erupted over the facial recognition
program employed in conjunction with the network
of cameras. (Brittany Greeson/The New York Times)"></p>
<p class="caption">Video from surveillance cameras
around the city is displayed at the Real-Time Crime
Center, the viewing space for Project Green Light,
at the police department headquarters in Detroit on
June 14, 2019.</p>
<p class="caption">
Photo: Brittany Greeson/The New York Times via Redux</p>
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<p>By pooling city-owned cameras with privately owned
cameras, policing experts say an agency in a typical
large city may amass <a
href="https://www.rand.org/pubs/research_reports/RR2619.html">hundreds
of thousands</a> of video feeds in just a few years.</p>
<p>Detroit has popularized plug-in surveillance networks
through its controversial Project Green Light program.
With Project Green Light, businesses can purchase CCTV
cameras and connect them to police headquarters. They
can also place a bright green light next to the
cameras to indicate they are part of the police
network. The project claims to deter crime by
signaling to residents: The police are watching you.</p>
<p>Detroit is not alone. <a
href="https://www.chicago.gov/city/en/depts/oem/provdrs/tech.html">Chicago</a>,
<a href="https://www.safecamnola.com/">New Orleans</a>,
<a
href="https://www.cityandstateny.com/articles/policy/technology/how-new-york-city-is-watching-you.html">New
York</a>, and <a
href="https://atlantapolicefoundation.org/programs/operation-shield/">Atlanta</a>
have also deployed plug-in surveillance networks. In
these cities, private businesses and/or homes provide
feeds that are integrated into crime centers so that
police can access live streams and recorded footage.
The police department in New Haven, Connecticut, told
me they are looking into plug-in surveillance, and
others are likely considering it.</p>
<p>The number of cameras on police networks now range
from tens of thousands (Chicago) to several hundred
(New Orleans). With so many cameras in place, and only
a small team of officers to watch them, law
enforcement agencies face a new challenge: How do you
make sense of all that footage?</p>
<p>The answer is video analytics.</p>
<h3>Video Analytics Takes Off</h3>
<p>Around 2006, a young Israeli woman was recording
family videos every weekend, but as a student and
parent, she didn’t have time to watch them. A computer
scientist at her university, Professor Shmuel Peleg,
told me he tried to create a solution for her: He
would take a long video and condense the interesting
activity into a short video clip.</p>
<p>His solution failed: It only worked on stationary
cameras, and the student’s video camera was moving
when she filmed her family.</p>
<p>Peleg soon found another use case in the surveillance
industry, which relies on stationary cameras. His
solution became BriefCam, a video analytics firm that
can summarize video footage from a scene across time
so that investigators can view all relevant footage in
a short space of time.</p>
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<p>Using a feature called Video Synopsis, BriefCam
overlays footage of events happening at different
times<a
href="https://www.youtube.com/watch?v=fISfDd35sXU">
as if they are appearing simultaneously. </a>For
example, if several people walked past a camera at
12:30 p.m., 12:40 p.m., and 12:50 p.m., BriefCam will
aggregate their images into a single scene.
Investigators can view all footage of interest from a
given day in minutes instead of hours.</p>
<p>Thanks to rapid advances in artificial intelligence,
summarization is just one feature in BriefCam’s
product line and the rapidly expanding <a
href="https://www.aclu.org/report/dawn-robot-surveillance">video
analytics industry</a>.</p>
<p>Behavior recognition includes video analytics
capabilities like <a
href="https://www.youtube.com/watch?v=QcCjmWwEUgg">fight
detection</a>, emotion recognition, fall detection,
loitering, dog walking, jaywalking, toll fare evasion,
and even <a
href="https://www.securitysales.com/news/milestone-disruption-innovation-mips/slideshow/2/">lie
detection</a>.</p>
<p>Object recognition can recognize faces, animals,
cars, weapons, fires, and other things, as well as
human characteristics like gender, age, and hair
color.</p>
<p>Anomalous or unusual behavior detection works by
recording a fixed area for a period of time — say, 30
days — and determining “normal” behavior for that
scene. If the camera sees something unusual — say, a
person running down a street at 3:00 a.m. — it will
flag the incident for attention.</p>
<p>Video analytics systems can analyze and search across
real-time streams or recorded footage. They can also
isolate individuals or objects as they traverse a
smart camera network.</p>
<p>Chicago; New Orleans; Detroit; Springfield,
Massachusetts; and Hartford, Connecticut, are some of
the cities currently using BriefCam for policing.</p>
<h3>To Search and Surveil</h3>
<p>With city spaces blanketed in cameras, and video
analytics to make sense of them, law enforcement
agencies gain the capacity to record and analyze
everything, all the time. This provides authorities
the power to index and search a vast database of
objects, behaviors, and anomalous activity.</p>
<p>In Connecticut, police have used video analytics to
identify or monitor known or suspected drug dealers.
Sergeant Johnmichael O’Hare, former Director of the
Hartford Real-Time Crime Center, recently <a
href="https://www.youtube.com/watch?v=lDC3EVAMvYI">demonstrated</a>
how BriefCam helped Hartford police reveal “where
people go the most” in the space of 24 hours by
viewing footage condensed and summarized in just nine
minutes. Using a feature called “pathways,” he
discovered hundreds of people visiting just two houses
on the street and secured a search warrant to verify
that they were drug houses.</p>
<p>Video analytics startup Voxel51 is also adding more
sophisticated searching to the mix. Co-founded by
Jason Corso, a professor of electrical engineering and
computer science at the University of Michigan, the
company offers a platform for video processing and
understanding.</p>
<p>Corso told me his company hopes to offer the first
system where people can “search based on semantic
content about their data, such as, ‘I want to find all
the video clips that have more than 3-way
intersections … with at least 20 vehicles during
daylight.’” Voxel51 “tries to make that possible” by
taking video footage and “turning it into structured
searchable data across different types of platforms.”</p>
<p>Unlike BriefCam, which analyzes video using nothing
but its own software, Voxel51 offers an open platform
which allows third parties to add their own analytics
models. If the platform succeeds, it will supercharge
the ability to search and surveil public spaces.</p>
<p>Corso told me his company is working on a <a
href="https://techcrunch.com/2019/08/08/voxel51-raises-2-million-for-its-video-native-identification-of-people-cars-and-more/">pilot
project</a> with the Baltimore police for their
CitiWatch surveillance program and plans to trial the
software with the Houston Police Department.</p>
<p>As cities start deploying a wide range of monitoring
devices from the so-called internet of things,
researchers are also developing a technique known as <a
href="https://www.rand.org/pubs/research_reports/RR2619.html">v</a><a
href="https://www.rand.org/pubs/research_reports/RR2619.html">ideo
</a><a
href="https://www.rand.org/pubs/research_reports/RR2619.html">a</a><a
href="https://www.rand.org/pubs/research_reports/RR2619.html">nalytics
and </a><a
href="https://www.rand.org/pubs/research_reports/RR2619.html">s</a><a
href="https://www.rand.org/pubs/research_reports/RR2619.html">ensor </a><a
href="https://www.rand.org/pubs/research_reports/RR2619.html">f</a><a
href="https://www.rand.org/pubs/research_reports/RR2619.html">usion</a>,
or VA/SF, for police intelligence. With VA/SF,
multiple streams from sensors are combined with video
analytics to reduce uncertainties and make inferences
about complex situations. As one example, Peleg told
me BriefCam is developing in-camera audio analytics
that uses microphones to discern actions that may
confuse AI systems, such as whether people are
fighting or dancing.</p>
<p>VMSs also offer smart integration across
technologies. Former New Haven Chief of Police Anthony
Campbell told me how <a
href="https://www.youtube.com/watch?time_continue=7&v=JJSNQoIvvkY">ShotSpotters</a>,
controversial devices that listen for gunshots,
integrate with specialized software so when a gun is
fired, nearby swivel cameras instantly <a
href="https://sixtechsys.com/the-hawkeye-effect-recognized-again-for-its-innovative-software">alter
their direction</a> to the location of the weapons
discharge.</p>
<p>Officers can also use software to lock building doors
from a control center, and companies are developing
analytics to alert security if <a
href="https://www.eblockwatch.co.za/posts/watch-the-future">one
car is being followed by another</a>.</p>
<h3>Toward a “Minority Report” World</h3>
<p>Video analytics captures a wide variety of data about
the areas covered by smart camera networks. Not
surprisingly, the information captured is now being
proposed for predictive policing: the use of data to
predict and police crime before it happens.</p>
<p>In 2002, the dystopian film “Minority Report<i>”</i>
depicted a society using “pre-crime” analytics for
police to intervene in lawbreaking before it occurs.
In the end, the officers in charge tried to manipulate
the system for their own interests.</p>
<p>A real-world version of “Minority Report” is <a
href="https://www.vice.com/en_us/article/7xmmvy/why-does-hartford-have-so-many-cameras-precrime">emerging</a>
through real-time crime centers used to analyze crime
patterns for police. In these centers, law enforcement
agencies ingest information from sources like social
media networks, data brokers, public databases,
criminal records, and ShotSpotters. Weather data is
even included for its impact on crime (because “bad
guys don’t like to get wet”).</p>
<p>In a <a
href="https://www.accenture.com/_acnmedia/pdf-94/accenture-value-data-seeing-what-matters.pdf">2018
document</a>, the data storage firm Western Digital
and the consultancy Accenture predicted mass smart
camera networks would be deployed “across three tiers
of maturity.” This multi-stage adoption, they
contended, would “allow society” to gradually abandon
“concerns about privacy” and instead “accept and
advocate” for mass police and government surveillance
in the interest of “public safety.”</p>
<p>Tier 1 encompasses the present where police use CCTV
networks to investigate crimes after-the-fact.</p>
<p>By 2025, society will reach Tier 2 as municipalities
transform into “smart” cities, the document said.
Businesses and public institutions, like schools and
hospitals, will plug camera feeds into government and
law enforcement agencies to inform centralized,
AI-enabled analytics systems.</p>
<p>Tier 3, the most predictive-oriented surveillance
system, will arrive by 2035. Some residents will
voluntarily donate their camera feeds, while others
will be “encouraged to do so by tax-break incentives
or nominal compensation.” A “public safety ecosystem”
will centralize data “pulled from disparate databases
such as social media, driver’s licenses, police
databases, and dark data.” An AI-enabled analytics
unit will let police assess “anomalies in real time
and interrupt a crime before it is committed.”</p>
<p>That is to say, to catch pre-crime.</p>
<h3>Rise of the Video Surveillance Industrial Complex</h3>
<p>While CCTV surveillance began as a simple tool for
criminal justice, it has grown into a
multibillion-dollar industry that covers multiple
industry verticals. From policing and smart cities to
schools, health care facilities, and retail, society
is moving toward near-complete visual surveillance of
commercial and urban spaces.</p>
<p>Denmark-based Milestone Systems, a top VMS provider
with half its revenues in the U.S., had less than 10
employees in 1999. Today they are a major corporation
that claims offices in over 20 countries.</p>
<p>Axis Communications used to be a network printer
outfit. They have since become a leading camera
provider pushing over $1 billion in sales per year.</p>
<p>BriefCam began as a university project. Now it is
among the world’s top video analytics providers, with
clients, it says, spanning <a
href="https://www.briefcam.com/company/press-releases/briefcam-achieves-exponential-growth-demand-surges-award-winning-video-synopsis-deep-learning-technology/">over
40 countries</a>.</p>
<p>Over the past six years, Canon purchased all three,
giving the imaging conglomerate ownership of industry
giants in video management software, CCTV cameras, and
video analytics. Motorola recently acquired a top VMS
provider, Avigilon, for $1 billion. In turn, Avigilon
and other large firms have purchased their own
companies.</p>
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<p>The public is paying for their own high-tech
surveillance three times over.</p>
</blockquote>
<div data-reactid="221">
<p>Familiar big tech giants are also in on the action.
Lieutenant Patrick O’Donnell of the Chicago police
force told me his department is working on a
non-disclosure agreement with Google for a video
analytics pilot project to detect people reacting to
gunfire, and if they are in the prone position, so the
police can receive real-time alerts. (Google did not
respond to a request for comment.)</p>
<p>Video monitoring networks inevitably entangle and
implicate a whole ecosystem of vendors, some of whom
have offered, or may yet offer, services specifically
targeted at such systems. Microsoft, Amazon, IBM,
Comcast, Verizon, and Cisco are among those enabling
the networks with technologies like cloud services,
broadband connectivity, or video surveillance
software.</p>
<p>In the public sector, the National Institute of
Standards and Technology is <a
href="https://www.nist.gov/news-events/news/2017/06/nist-awards-385-million-accelerate-public-safety-communications">funding</a>
“public analytics” and communications networks like
the First Responder Network Authority, or <a
href="https://theintercept.com/2018/07/29/firstnet-att-surveillance/">FirstNet,</a>
for real-time video and other surveillance
technologies. FirstNet will cost $46.5 billion, and is
being built by AT&T.</p>
<p>Voxel51 is another NIST-backed venture. The public is
thus paying for their own high-tech surveillance three
times over: first, through taxes for university
research; second, through grant money for the
formation of a for-profit startup (Voxel51); and
third, through the purchase of Voxel51’s services by
city police departments using public funds.</p>
<p>With the private and public sector looking to expand
the presence of cameras, video surveillance has become
a new cash cow. As Corso put it, “there will be
something like 45 billion cameras in the world within
a few decades. That’s a lot of (video) pixels. For the
most part, most of those pixels go unused.” Corso’s
estimate mirrors a <a
href="https://www.fastcompany.com/40450867/in-less-than-five-years-45-billion-cameras-will-be-watching-us">2017
forecast</a> from New York venture capital firm LDV,
which believes smartphones will evolve to have even
more cameras than they do today, contributing to the
growth.</p>
<p>Companies that began with markets for police and
security are now diversifying their offerings to the
commercial sector. BriefCam, Milestone, and Axis
advertise the use of video analytics for retailers,
where they can monitor foot traffic, queue length,
shopping patterns, floor layouts, and conduct <a
href="https://www.briefcam.com/solutions/consumer-behavior-and-experience/">A/B
testing</a>. Voxel51 has an option built for the
fashion industry and plans to expand across industry
verticals. <a href="https://motionloft.com/">Motionloft</a>
offers analytics for smart cities, retailers,
commercial real estate, and entertainment venues.
Other examples abound.</p>
<p>Public and private sector actors are pressing for a
world full of smart video surveillance. Peleg, for
example, told me of a use case for smart cities: If
you drive into the city, you could “just park and go
home” without using a parking meter. The city would
send a bill to your house at the end of the month. “Of
course, you lose your privacy,” he added. “The
question is, do you really care about Big Brother
knows where you are, what you do, etc.? Some people
may not like it.”</p>
<h3>How to Rein in Smart Surveillance</h3>
<p>Those who do not like new forms of Big Brother
surveillance are presently fixated on facial
recognition. Yet they have largely ignored the shift
to smart camera networks — and the industrial complex
driving it.</p>
<p>Thousands of cameras are now set to scrutinize our
every move, informing city authorities whether we are
walking, running, riding a bike, or doing anything
“suspicious.” With video analytics, artificial
intelligence is used to identify our sex, age, and
type of clothes, and could potentially be used to
categorize us by race or religious attire.</p>
<p>Such surveillance could have a severe chilling effect
on our freedom of expression and association. Is this
the world we want to live in?</p>
<p>The capacity to track individuals across smart CCTV
networks can be used to target marginalized
communities. The detection of “loitering” or
“shoplifting” by cameras concentrated in poor
neighborhoods may deepen racial bias in policing
practices.</p>
<p>This kind of racial discrimination is <a
href="https://www.vice.com/en_us/article/pa7nek/smart-cctv-networks-are-driving-an-ai-powered-apartheid-in-south-africa">already
happening</a> in South Africa, where “unusual
behavior detection” has been deployed by smart camera
networks for several years.</p>
<p>In the United States, smart camera networks are just
emerging, and there is little information or
transparency about their use. Nevertheless, we know
surveillance has been used throughout history to
target oppressed groups. In recent years, the New York
Police Department secretly spied on Muslims, the FBI
used surveillance aircraft to monitor Black Lives
Matter protesters, and the U.S. Customs and Border
Protection began building a high-tech video
surveillance “<a
href="https://theintercept.com/2019/08/25/border-patrol-israel-elbit-surveillance">smart
border</a>” across the Tohono O’odham reservation in
Arizona.</p>
<p>Law enforcement agencies claim smart camera networks
will reduce crime, but at what cost? If a camera could
be put in every room in every house, domestic violence
might go down. We could add automated “filters” that
only record when a loud noise is detected, or when
someone grabs a knife. Should police put smart cameras
inside every living room?</p>
<p>The commercial sector is likewise rationalizing the
advance of surveillance capitalism into the physical
domain. Retailers, employers, and investors want to
put us all under smart video surveillance so they can
manage us with visual “intelligence.”</p>
<p>When asked about privacy, several major police
departments told me they have the right to see and
record everything you do as soon as you leave your
home. Retailers, in turn, won’t even approach public
disclosure: They are keeping their video analytics
practices <a
href="https://www.aclu.org/blog/privacy-technology/surveillance-technologies/are-stores-you-shop-secretly-using-face">secret</a>.</p>
<p>In the United States, there is generally no
“reasonable expectation” of privacy in public. The
Fourth Amendment encompasses the home and a few public
areas we “reasonably” expect to be private, such as a
phone booth. Almost everything else — our streets, our
stores, our schools — is fair game.</p>
<p>Even if rules are updated to restrict the <em>use</em>
of video surveillance, we cannot guarantee those rules
will remain in place. With thousands of high-res
cameras networked together, a dystopian surveillance
state is a mouse click away. By installing cameras
everywhere, we are opening a Pandora’s box.</p>
<p>To address the privacy threats of smart camera
networks, legislators should ban plug-in surveillance
networks and restrict the scope of networked CCTVs
beyond the premise of a single site. They should also
limit the density of camera and sensor coverage in
public. These measures would block the capacity to
track people across wide areas and prevent the
phenomenon of constantly being watched.</p>
<p>The government should also ban video surveillance
analytics in publicly accessible spaces, perhaps with
exceptions for rare cases such as the detection of
bodies on train tracks. Such a ban would
disincentivize mass camera deployments because video
analytics is needed to analyze large volumes of
footage. Courts should urgently <a
href="https://digitalcommons.wcl.american.edu/cgi/viewcontent.cgi?referer=&httpsredir=1&article=1899&context=aulr">reconsider</a>
the scope of the Fourth Amendment and expand our <a
href="http://law.emory.edu/elj/_documents/volumes/66/3/levinson-waldman.pdf">right
to privacy in public</a><a
href="http://law.emory.edu/elj/_documents/volumes/66/3/levinson-waldman.pdf">.</a></p>
<p>Police departments, vendors, and researchers need to
disclose and publicize their projects, and engage with
academics, journalists, and civil society.</p>
<p>It is clear we have a crisis in the works. We need to
move beyond the limited conversation of facial
recognition and address the broader world of video
surveillance, before it is too late.</p>
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