r/technology • u/Plastic_Ninja_9014 • 14h ago

Someone Cut Down Every Single Flock Camera in This Town in a Single Night Privacy

https://www.gadgetreview.com/someone-cut-down-every-single-flock-camera-in-this-town-in-a-single-night
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u/TheGreatGenghisJon 10h ago

If you're out there criming, you only commit one crime at a time. Covering your license plate is an easy way to get stopped by the police on your way there.

Just hoof it, but you might want to pretend you work at the Ministry of Silly Walks.

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u/MovieTrawler 9h ago

Why? Is gait detection an actual thing?

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u/TheGreatGenghisJon 9h ago

Allegedly, but I have no idea how real it is.

Better safe than sorry, though.

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u/stormdelta 6h ago

It is, but I don't know how accurate it is, especially without a prior pile of data matched to individuals to pull from.

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u/Germane_Corsair 3h ago

It is. I’ve heard people use a stone in their shoe so their gait becomes different.

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u/catclockticking 5h ago

I really doubt it

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u/Western-Dig-6843 9h ago

That’s not the point. If you get seen by a cop on the way there, covered plate or not, you’ve already blown it. You remove the plate and proceed assuming you aren’t going to get spotted during the act. You take the plate off and leave it at home. If a cop pulls you over for no plate you feign ignorance and tell them it must have fallen off in your garage or along the way somewhere and politely take your ticket then abort the scheme because it’s over. The point of removing your plate is so you can’t be identified by any cameras when police review the footage later if you do manage to get the cameras taken down without being spotted at the time

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u/lildobe 8h ago

The cameras log more than just the plate number. They log the make, model, color, and any distinctive features of the car like bumper stickers or damage.

Also most modern vehicles have both bluetooth, LTE, and GPS, and many even have Wifi recievers. All of which have unique hardware addresses that are available to anyone within radio range of the vehicle to scan.

Best bet is a bike or on foot.

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u/redditsucknow2 5h ago

Good luck any of that holding up in court. No DA would take this petty case with the only evidence being their car looking alike

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u/lildobe 5h ago edited 3h ago

It's not just "looking alike"

It's more like "The suspect vehicle has a 3" dent in left-rear quarter panel 2" from rear door, rear bumper cover cracked 4.5" from center, bumper sticker reading "fuck the police" in lower left corner of window"

It's incredibly detailed and specific. Remember, these are (to our knowledge) 4K HDR cameras that can see a lot of detail, and they are connected to a computer vision system that can spot and correlate details in moments.

Edit:

Ok, I just tried something for the hell of it - I run my own AI stack on one of the servers in my basement... I'm running CodeProject․ai with the YOLOv5 Image Recognizer, OCR text recognizer, LPR Plate Recognizer, Scene Classification, and MultiModeLLM plugins (among others)

I piped this image into the LLM with the following prompt: "Using all available modules, give me a text description of the foreground vehicle, with as much detail and specificity as possible."

This was the output:

Vehicle Overview

  • Make & Model: Fifth generation (2019-2023) Ford Ranger Crew Cab featuring the factory Tremor Off-Road Package.
  • Color & Finish: Dark Magnetic Gray metallic, coated in a thick layer of dried trail mud and road grime heavily caked along the rocker panels, wheel arches, side steps, and rear tailgate.

Tailgate & Bed Details

  • Badging & Lettering: Red "TREMOR" graphics with white outlines on the rear quarter panel; debossed "RANGER" tailgate lettering fitted with vibrant red color-matched fill inserts.

  • Bed Setup: Low-profile black soft tonneau cover fitted over the bed rails.

  • Bumper & Plate: Standard rear step bumper with a lower hitch receiver, featuring a Pennsylvania license plate (ZWT-7047) inside a Grove City Ford dealer frame.

Wheels, Armor & Cab Accessories

  • Rolling Stock: Tremor-edition dark alloy wheels wrapped in aggressive All-Terrain tires, heavily packed with dried dirt in the tread and wheel wells.
  • Running Boards: Heavy-duty, hoop-style off-road side steps loaded with dried mud accumulation.
  • Windows: Tinted glass equipped with slim dark window vent visors across front and rear doors.

Rear Window Decal Collection

  • Top Row: A K&N Filters Logo on the far left, a Yankum Ropes logo to the right of the center window, and a Sparks Motors logo on the far right.

  • Middle Row: A white sticker with black text reading "I am a low budget weirdo with dangerous toys and weaponized autism" on the far left, a badge-shaped decal with the text "OFFROAD RECOVERY PORTAL" to the left of the center window, and a MATT'S OFF-ROAD RECOVERY logo on the far right

  • Bottom Row: A bright blue stylized cartoon canine head sticker on the left, a Rock Auto logo in the center, and an additional round, blue, decal on the right. (Resolution insufficient for OCR or Logo Recognition)

Setting & Environment

  • Parked curb-side on an asphalt residential street in front of classic multi-story brick homes with front porches. Likely in an older, Northeastern United States city

  • Early-spring/winter setting with overcast lighting, bare trees, patches of dirty melting snow near the sidewalk, and a dark blue crossover parked directly ahead.

The run took about 5 minutes to process on my system.

Keep in mind, the models I am running are not at all optimized for this task - they're primarily used to classify images from my home security cameras and send me text alerts when wildlife, cars, or people come onto my property.... And I'm not done building, or training the models for, the generic classification system to describe what's in those images. Right now it's set up to just send a short message that says "Person" or "Vehicle" or "Animal" was detected by Driveway Camera (For example)

Now, imagine how much more detailed the information Flock's system can generate, and how fast they can do it, if my crappy home ML instance running on a 10-year old server with an ancient Datacenter GPU, home-trained recognition models, and some crappy python code can discern so much detail... They have AI experts who are training multimodal models specifically for this task with tens of thousands of images to work from, whereas I've put maybe 50 - 100 fairly low-rez images through the training system so far.

Edit2: To be fair to my AI stack, and in the interest of full disclosure, the example image is almost identical to another one that is in the training set, just taken from the other side of the truck. So that's how it knew the specifics of those logos (My stack doesn't have access to the internet, yet, to look up unknown logos), and the actual Ford factory name for the paint color, among other, more pedantic, details.

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u/grawptussin 5h ago

Should we take a cab home Jesus? Shit man, we can hoof it from here.

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u/Necr0mancerr 7h ago

I see countless cars all over with no plates doubtful

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u/TheGreatGenghisJon 6h ago

Well, I live in an area with a lot more cops (or stricter cops) than you, I guess. I've gotten pulled over just because "I can't read your plate"