

Ask HN: Is this a stupid business idea? - midas007

Reward more&#x2F;less anonymous people for watching security footage in basically real time to catch shoplifters and report other incidents.  An average large store with 20 cameras would produce 30.4k hr &#x2F; month, which could be reduced with algorithms.  Say $1k USD &#x2F; month would be a reasonable charge if it could shown that it saves this much with loss prevention.<p>Is anyone doing this?  What are the sales barriers, issues in this space?<p>Edit: Similar, but different compared to https:&#x2F;&#x2F;schneier.com&#x2F;essay-327.html
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vitovito
Lots of positive comments in here, but I think you probably need to learn how
loss prevention works in stores of all sizes, first. The way you're phrasing
your value proposition says you don't understand that.

Here's why: I think you're making unwarranted assumptions about the purpose
and value of all those security cameras.

In a lot of cases, it's not to catch shoplifters. It's just to collect
evidence. That's why security officers in stores aren't supposed to touch or
give chase to offenders. It's also often to collect evidence against the
_employees_. An employee has opportunity to steal a lot more than a visitor
does, that's why bank tellers and cashiers have cameras pointed at their
hands, not at the customer.

Second, loss is built into a retail business model. It's going to happen. It's
unavoidable. The only goal of loss prevention is to keep it from happening
more than it happens to other stores like yours. There may not be any
incentive to stop an additional $1k/mo. of loss if you're already at or below
average, because you're not compensated or rewarded based on that.

Third, I think you're overestimating the "real-time" nature and the quality of
your video, here. Ever seen a video of a pickpocket on YouTube? Or in the
movies? Where they have to slow-mo it so you can even tell something happened
at all? A decent shoplifter isn't going to get noticed by a grainy, analog,
CCTV camera, whether watched by machine learning, an average Joe, or a trained
security officer.

And in your machine learning + crowdsourcing situation, you're processing data
in real-time, using ML to look for what? Someone touching the merchandise and
putting it in their pocket isn't very different from someone touching the
merchandise and putting it in their basket, when your CCTV camera is 300 lines
of resolution and in black and white and 50' away.

How long does it take for an analog CCTV camera video to get to the back room
of the store (10ms?), get compressed (hardware MPEG4? 100ms?), sent over the
internet to your cloud for distribution to your workers (20 video streams *
0.5mbit/sec. for 360p MP4 with no audio, that means the store has to upgrade
to 10mbit dedicated upstream to your servers, and we'll say 500ms latency),
decompressed and analyzed in "real time" (< 100ms? 500ms? this is your
necessary core competency right here) and then flagged and either trimmed and
sent as a specific video clip to users on home connections in non-US
countries, or streamed as part of an ongoing video stream (another 500ms
latency plus download time to the user), and then wait for the user to respond
(5000-10000ms?), and then you go and notify the store. That's 10+ seconds,
best case, assuming you're able to do _any_ kind of decent analysis on
compressed CCTV feeds, and the security guy still has to get up and go to
where the incident happened, all the way across the store. In ten seconds, the
shoplifter is _nowhere near_ where they were when the video was originally
taken. In reality, you're talking 30 seconds to a minute. In that time, they
might have left the building already.

And then maybe you realize you can't do anything useful with CCTV, and you
need to get retailers to upgrade to HD video. Now you have 20 1080p streams,
plus the new cameras, plus adding ethernet wiring throughout the store (since
the analog feeds just ran over cheap coaxial cables), meaning you need a store
with 70mbit upstream. That's a really, really expensive upgrade for only
$1k/savings a month. That might be a lot more than you save them.

Or maybe this means you need hardware on the premises to do the algorithm, and
it only sends it upstream when it detects an issue. This actually makes your
latency worse, because now a store sticks with their crappy 0.5mbit upstream.
And, now you don't get a lot of video to analyze yourself to improve your ML
and CV. Shoplifters will learn what your algos can detect and not detect and
just avoid those movements and now you're not saving anyone any money.

I'm not saying it's a bad idea, I'm just saying it sounds like there might be
a lot you haven't considered.

~~~
notahacker
I think your comments on retail are spot on, but I think the real opportunity
is probably in security detecting unwanted intruders (especially where
orthodox motion or heat sensors are ineffective or inappropriate). That's got
to be relatively easy to monitor using ML, especially if you have Mechanical
Turkers to vet false positives.

People do get paid to watch security videos remotely and send appropriate
warning messages. If it's for the private sector it wouldn't be difficult to
outsource their job to _five_ people in India at a profit.

------
DanBC
It feels like a good idea.

How do you stop me signing up with 20 accounts and just running the feeds
while I'm sleeping?

I'm watching some footage. I see someone clearly stealing something. What do I
do?

I watch all the footage but I miss people stealing stuff. What do you do?

I watch the footage and say that I see someone stealing something, but they
haven't stolen anything. What happens then?

But it feels like a good use of lots of people.

One thing that might be handy is to gather all the footage where someone has
been seen Stealing something and analyse that footage. If you gather the
footage for a town you may find some prolific thiefs. Supplying the footage
with that thief in to the police would be good.

There might be a problem offering the service in some regions because of
privacy laws - but I guess you're using surveillance cameras for surveilance
so it's not a problem? You might need to ask someone who knows about data
protection laws if you offer this to the UK.

But I like the idea!

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gregcohn
One of the realities with surveillance systems is there they create so many
hours of footage, per camera, that it's impossible to watch them all. This is
a good idea if: \- you can find ways to get the watchers cost-effectively
(rewarding them per incident noticed is a good idea, but if the system works
as a deterrent incidents per camera-hour will go down over time); \- you can
algorithmically compress viewing time \- you can find high-value applications
and verticals.

~~~
ballard
ML scoring of footage of customers near product, increasing and multiple
watchers during peak times. The other service would be actively testing
watchers with varying levels of red team exercise difficulty.

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myersgp
Here's an idea to prove they're watching the videos...at intervals, you
display a unique ID to each feed, that the monitor has to enter on a keyboard.
The interval should vary, as should the position on the screen. But the UID
should appear on everyones feed at the same time; this should prevent one
person from monitoring more than one feed at a time. You could/should have
every feed monitored by more than one person. The feds could be run slightly
out of sync/delayed, but still with the ID displayed at the same actual time.
Therefor is someone was distracted by having to enter the ID, and missed
someone shoplifting, another person wouldn't be.

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blooberr
Your idea will work. I used to work in video surveillance and there was a
company doing "video analytics" for shopping retention. The trick was they had
a large amazon turk-like operation in Brazil.

~~~
ballard
Watchers in Appalachias, Eastern Europe, Malaysia, Africa might scale.

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vincie
Your idea will only work if you can control the anonymous watchers. How would
you know if they actually watched the footage properly? One way to do it that
comes to mind is the captcha way - give the watcher two segments, one of which
is know to contain a reportable incident. If they report the one with the
reportable incident, then it is probable that they watched the other one
properly as well.

~~~
lucozade
Or you could video them and pay for someone to watch the videos.

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carlosdp
Something else to consider which I don't think has been brought up: will the
footage that users see have faces?

It's easy enough to solve these days, I believe, by just liberally pre-
processing to blur the faces out, but I could definitely see that privacy
concern coming up. Seems like a solid idea.

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semmem1
Love the idea, would be a fun if you paid for each person you caught stealing
and nothing otherwise. When I'm bored and there is nothing on TV, I can just
turn on your app and pretend to be a security guard. Maybe you can even have
an API that would let users make applications that track people stealing.

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mobiuscog
It has been tried before in the UK: [http://www.itpro.co.uk/627418/cctv-
service-internet-eyes-goe...](http://www.itpro.co.uk/627418/cctv-service-
internet-eyes-goes-live)

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ballard
There are these large stores in the US where it seems like everyone but me is
three finger discounting soda and donuts.

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wusatiuk
i guess that this idea could work out very well, if you can get the costs low
and the "catch-rate" high. :)

~~~
ballard
Finders fee per incident perhaps.

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ballard
Are there any existing patents on this?

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badgercapital
But sooo much streaming?

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skelsey
Have you read REAMDE?

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badgercapital
hahaha awesome idea!

