How Your Routine Becomes A Profile

Your routine is more revealing than you think, and it’s not because you’re doing anything wrong. We dig into pattern of life analysis, the real-world method used to understand a person by studying repeated behavior over time. What used to require weeks of patient surveillance can now be accelerated by automated systems, including license plate readers and camera networks like Flock, turning daily movement into something that can be searched, sorted, and used to predict where you’ll be.

We walk through how a pattern is built step by step: collecting basic data points, establishing a baseline, spotting anomalies that signal change, identifying associations between people who keep showing up together, and finally making predictions. Along the way, we keep it practical and personal, using a two-week self-audit to show how commutes, errands, restaurants, and regular stops create a “creature of habit” map that someone else can exploit.

Then we move beyond street cameras into the digital layer: phone location history, Google Timeline, Bluetooth scanning that may keep running even when you think Bluetooth is off, and photos that can carry EXIF metadata with GPS coordinates. We also cover smart home devices, connected vehicles, purchase patterns, and fitness trackers as persistent sources of behavioral data that can reveal when you’re home, where you go, and what you do.

We close with the balance that matters most: awareness without paranoia, and small OPSEC adjustments that reduce predictability without turning your life upside down. Subscribe, share the show, and leave a review, then reply with one routine you’re going to vary this week.

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Transcript

Emails After The Flock Episode

SPEAKER_00 0:02

You are listening to the Common Sense Practical Prepper. Montered by Duct Tape. The real Duct tape. It fixes everything except that decision. Good evening, Mr. and Mrs. America. From border to border, coast to coast, and all ships at sea. Here is your host, Keith.

SPEAKER_01 0:21

Everybody, this is Keith, and you're listening to the Common Sense Practical Prepper Podcast for July 17th, 2026. And normally I don't do back-to-back episodes, but I want to go ahead and do this one because I talked about something last night and I got a few emails about it. So let's go ahead and dive in. So the Flock Camera episode dropped about 24 hours ago. And I received about six emails in my inbox about last night's episode. A few folks emailed me that they actually went to the website, I believe it's dflock.com or dot org, I'm not sure, dflock something. And they actually looked at camera locations and how they would be covered or tagged, whatever you want to call it, on their way to work. And a couple people reached out that they were familiar with the cameras and they had already kind of done that on their own, just in their daily travels. Oh, there should be one here on the corner. Oh, look, there it is. There should be one over here by the mall. Yep, yep, the website was correct. And I also mentioned something about pattern of life analysis. And two people, no, I'm sorry, three people reached out and asked me what exactly is pattern analysis or pattern of life analysis.

What Pattern Of Life Really Means

SPEAKER_01 1:50

So let's go ahead and dig into it. Because this is not science fiction. I do not have my tinfoil hat on at the moment. I took it off just for this podcast. Oh, I think puberty just hit me there for a second. I took it off just for this podcast. This is not Alex Jones territory or anything like that. This is a real intelligence discipline, I guess you could call it, that I used as a detective much more low-tech compared to what we have going on now, and that military and government analysts use every single day here in the States, overseas, what have you. So whether you realize it or not, this does apply directly to your daily routine. So what does pattern of life analysis actually mean? So pattern of life, sometimes called, I guess, POL for short, it's a study of a person's routine, their behaviors over time that builds a predictive model of who they are, what they do, and where they go. That's it. Okay. Again, no tinfoil hat required. It's observation plus time equals understanding. So when I was working cases, if we had a suspect that we could not get close to, we would do the old school surveillance. We would sit in a car, not for an hour, not for a day, but at times, off and on for several weeks. We would log when the suspect left their house, where they went, how long they were there, did they go to work? Did they go to this address? Okay, ABC 123 Main Street. Okay, now who lives there? And how are they associated with that person that lives on Main Street? Tuesday morning, they leave for work about 6 45. They make this left turn, this right turn, they go to this particular gas station, they get coffee, and then they go to work. Thursday evening about 7 p.m. They go to a residence on Oak Street that happens to be their girlfriend's residence, and they stay till about 11. And every Thursday, that is the pattern. The person we're watching goes to the girlfriend's house every Thursday about 7 and leaves about 11. So that's a pattern of life. And that's what matters. We didn't need to tap a phone, no search warrants. We didn't have to read anybody's emails. The pattern told us everything that we needed to know. Where they worked, who they were seeing, when they were vulnerable, when their house was empty, and when they were alone. Now multiply that with automation and AI. That's what cameras, GPS data, and digital tracking do. They conduct pattern of life analysis at machine level speed on everyone all the time, and police officers and detectives do not have to be sitting in a car drinking really bad gas station coffee waiting for the suspect to do something. So let's tie this in and make it a little more personal.

The Two-Week Routine Reality Check

SPEAKER_01 4:58

So think about your last two weeks. So think about if you can remember, I can't tell you what I had for lunch, but try if you can. Think about the last two weeks. What time do you leave for work each morning or each afternoon? Do you leave within a 15-minute window each time you go to work? Probably yes. I do. Do you take the same route to work? Depending on traffic, I have three different ways I can get to work. What about the grocery store? What about the hardware store? What did you order when you went to a restaurant? Was it the same as you ordered last Saturday when you went to this particular restaurant? Your pizza from Domino's, Pizza Hut, wherever. Do you get the same pizza all the time? So here's an exercise. You can grab a piece of paper or or you can just do it mentally. Write down or recall your weekly routine. Every recurring trip, every regular stop, every habitual pattern, morning routine, your commute, where you eat lunch, if you stop somewhere on the way home from work, weekend errands. Do you go to a particular cafe on Saturday? Do you then go to tractor supply like I do to get chicken feed or cat food? Do you go to Home Depot because they have a sale on two by fours or some new handy gadget that you have to have? That's what analysts see after watching you for two weeks, except they probably have more detail than you write down or that you are able to recall because you don't even notice half of what you do that's considered a pattern. So most people are creatures of habit, myself included, not being judgy at all. But when your habits are observable and recordable, that becomes intelligence. And intelligence is leverage. So who actually does this and why do they do it? All right, let's take a burglar. A competent burglar just does not pick a house at random. They watch, they learn when you leave, when you come home, whether the house is empty on Wednesday afternoons. Your pattern tells them the safest window to hit your home. Stalkers. This is one of the more common threat scenarios for everyday people, especially women. A stalker does not need sophisticated tools, they just need patience in your routine. Skip tracers or bondsmen, bounty hunters, whatever you want to call them, and private investigators. People who find people for a living. They study patterns. Where does the subject get gas? Where do they eat? Creatures of habit are always easy to locate. Corporate competitors. In the business world, competitive intelligence teams track executive movements. Where are they flying? What facilities are they visiting? Are they meeting with regulators? Are they meeting with a potential new client? Perhaps it's the other company's competition. They're vying for a new contract. And yes, law enforcement and all the alphabet government agencies. From local narcotics units to federal counterterrorism, pattern of life is a standard tool. It is used because it works. Now we tie that in with last night's episode. The flock cameras, the license plate readers, they automate the hardest part of pattern of life collection. That is the watching. The cameras watch 24-7, they never get bored, they don't have to go to the bathroom, and they never miss a license plate. What used to take two weeks in a car with the thermos of really bad gas station coffee now takes a database query and about four seconds. How do analysts build a picture? So now that we know what a pattern of life is, but how does an analyst actually go about taking a pile of raw information, raw data, and turn that into a profile? So we'll walk through the way that I was taught, the way that I did it for quite some time. So step one is the collection. You gather data points, time, location, direction, duration. That's it. No judgment, no analysis yet. You're just logging. Suspect left home at 650. Tuesday left at 645. Wednesday left at 652. You're just building a raw data

How Analysts Build Predictions From Data

SPEAKER_01 10:17

set. Step two, the baseline, and this is important. After seven to ten days, you start to see a rhythm. You can separate a routine from deviation. It's pretty easy to notice a deviation from someone's normal routine. The person leaves for work between 6.45 and 7 on weekdays. They go south on U.S. Route 1. They return between 530 and 6.15. That's the baseline. So that's the normal behavior for this particular person. Step three, identification of any anomalies. Once you know what normal looks like, anything that breaks out or is different stands out like a neon sign. Subject left at 4 a.m. on a Wednesday. That is a break from the normal routine. Subject drove 90 miles to a location they've never been to before. Subject made three stops in two hours when they normally make one. So that's a flag. That's just a difference from their normal routine. So that is automatically flagged as a break in the routine, and then that'll be investigated later. And here's what a lot of people don't understand when it comes to these anomalies. Anomalies are more valuable than the routine because the routine tells you who they are, or in many cases, who you are if you're talking about yourself. The anomalies tell me what you're up to. Something has changed, and now I, if I'm the person putting the profile together, I want to know why there was a change in your pattern. Step four, very important, association. This is where it can go in several different angles and provide some very powerful information. You overlay one person's pattern with another. Two people who have no known connection at the time keep showing up at the same location within the same time window. That's an association. You don't need to wiretap anybody, you don't need to get a confession. The pattern tells you that they're connected. So when I had a chance to work some narcotic cases, we would see the same vehicle show up at three different known locations within a single week. The vehicle was never at these locations before. We didn't need an informant to tell us this person was now in the network. The movement data told us what we needed to know. And step five, prediction. So this is the end game of a pattern analysis. Once you have enough data, you can predict where someone will be and when. So if I know that you go to a storage unit every other Friday between 4 and 5 p.m., I can be there waiting. Or I can be at your house knowing you won't be there. So here's the thing this entire process used to be manual, very labor intensive. It used to require a human being with a clipboard, a camera, and a lot of patience. Today, you guessed it, automated systems do steps one through four without any human involvement. The algorithm flags the anomalies, the database builds the associations, and analysts only get involved at step five, and sometimes not even then. So when I tell you that infrastructure matters, this is what I mean. It's not just that the cameras are watching, it's that the entire analytical framework that I just described can now run at scale. Thousands of cameras capturing hundreds of thousands of data points every single second. And everyone is on this network. So let's talk about phones, internet, social media, the digital layer, the digital footprint that you are broadcasting that you may not know. Last episode, I talked about physical countermeasures, varying your roots home, varying your roots to work, being aware of cameras. So I'm not going to repeat all that. If you haven't had a chance to listen to the flock episode, go back and listen to that one. You'll get more context. But today I want to talk about the digital pattern of life because most people don't realize how much they broadcast without even coming close to one of the cameras. All right, your cell

Your Digital Pattern Of Life

SPEAKER_01 15:12

phone. A lot of this goes without saying. Even if you're not using it, your phone is constantly checking in with cell towers, wireless access points, and Bluetooth beacons. Google Timeline. If you have an Android or use Google Maps, they have a record of everywhere that you've been, timestamped, going back years. So go look at it. It's under your Google account timeline. Most people have never checked it. You will be either disturbed, amazed, blown away, or perhaps a little bit of all three. And here's another quick one that most people don't know. When you swipe down and toggle Bluetooth off on your phone, it is not fully off. Both Android and iPhone keep something called Bluetooth scanning running in the background for location accuracy. It's still pinging nearby devices and Bluetooth beacons. Retail stores, airports, smart billboards, they all pick up those pings. You have to go into your actual settings, location settings on an Android, privacy and location settings on an iPhone, and disable Bluetooth scanning separately. It's a second switch that most people never see. And I did not realize this until I started researching tonight's episode. There are all sorts of websites out there that will help you lock down your cell phone, Android, iPhone, help you lock down your home internet. So you can just, dare I say it, you can go to Google or DuckDuckGo, whatever your favorite search browser is, or YouTube, and just look for websites that show you how to make your phone, your home internet more secure. There are a dime a dozen, so they're definitely out there. Taking photos with your phone. Every photo you take with your phone has what's called EXIF data. It's an acronym, EXIF. And that data is embedded in it. When I was a detective, I did computer forensics. Most people do not disable the exif data or the GPS coordinates, date, and time, and the device model of the phone when they take the photographs. If you don't disable that, it's available to be seen. When I was a detective and I did the computer forensics, a lot of people didn't do that. So when I did the forensics on the computer and I found their photographs, I could see the exif data and see exactly down to the square meter where the person was when they took a particular photo, date, time, what have you. So you post a photo of your garden on social media. You want to show off all your cucumbers and tomatoes. You've just broadcasted your exact coordinates. Now, some platforms strip that data away and some don't. So I'm not saying that somebody's going to go to your Facebook page and right-click the photo and find out exactly where that was taken. There are programs that can be run against those photos to extract that exif data. Smart home devices, this is a big one. Your smart thermostat, which I have, changes your temperature at 6:30 a.m. because you set a schedule. You turn the lights on at 7 p.m. right before you get home. Your ring doorbell logs every motion event. Your garage door opener logs open and close times. All of the data is in someone's cloud, and it all says the same thing. Here is when the person is home. Here is when they leave, and here is when they come back. Connected vehicles. If your car was made after 2018, it's probably been collecting and transmitting data. GPS location, speed, braking patterns, destinations are now entered into navigational systems. That's captured. Some manufacturers sell this data to third parties. There's been reporting on this. Your car is a rolling data collection device, and most people have no idea. Purchase patterns. This is one I was aware of. Loyalty cards, credit card statements, Amazon purchase history. If you buy 200 pounds of rice, 50 cans of freeze-dried food, and a water filtration system in the last month, that's a pattern. It doesn't matter that you drove three different routes to three different stores. If you paid with the same credit card every time, the financial data reconstructs what the cameras missed. And again, this is being done without your knowledge. And I'm not saying there's people that are sitting out there data mining this, but it's all being captured. Fitness trackers and wearables. Your Garmin Watch, Fitbit, Apple Watch, what have you. They log GPS routes on your runs, your bike rides, and your hikes. I was aware of this story. People have had their military-based layouts exposed because soldiers were running laps with their GPS watches and the data was public on Strava, S T-R-A-V-A. This has actually happened. So if you're out hiking on your property and wearing a GPS watch, that route is logged. Again, I'm not saying someone is waiting for you to take a hike or a run so they can grab it. What I'm saying is that data is logged and it's kept. So here's my point. The physical cameras we talked about last time, that's just one layer. But the digital layer is often more detailed, more persistent, and more accessible than just the cameras. An analyst with access to your digital footprint does not need a camera. Your devices are doing the surveillance for them. So when you think about pattern of life, just don't think about what a camera sees. Think about what your phone knows, what your car knows, and what your thermostat knows, or the smart meter on your house, your electric meter. And think about what your purchase history might say. So that's the full picture, and that's what's being assembled, not necessarily by a person sitting in a room that's watching you, but by systems that collect it all and make it searchable for whoever has access later. So there's a balance between awareness and paranoia. So I'll pump the brakes for a second because I know how this sounds to some people, and I want to be very transparent about the balance. You cannot live your life in a state of constant counter-surveillance. That's not living. That's exhausting, unsustainable, and you'll drive yourself bananas. The goal here is not to disappear, the goal is informed awareness. I may have just coined that phrase. Informed awareness. I like that. So think of it as like locking your car doors. Every time you go to the store,

Awareness Without Living Like A Spy

SPEAKER_01 22:31

every time you lock them, you don't think somebody's going to steal your car then. Every time you park your car, you're not like, oh, I better lock my car because somebody's going to steal it today. But you lock it because it's a reasonable precaution that doesn't cost you anything. Pattern awareness is the same idea. Small, sustainable adjustments that reduce your predictability without turning your life upside down. Most of us are not high-value targets for surveillance, I understand. But the infrastructure that makes mass pattern analysis possible does not distinguish between a high value target and you and I. It collects everything and then sorts it out later. So my point is simply this: know that your routine is observable, understand what it reveals, and make conscious decisions about what level of predictability you are comfortable with broadcasting. So you're not paranoid for locking your doors, and you're not wearing a tinfoil hat for just varying your route to the range, to the gun store, to Costco, or wherever. So I'll wrap it up. Pattern of life analysis is not a conspiracy theory. It's a real discipline used by real people to learn real things about targets. And thanks to automated surveillance, it's being applied to everyone, whether you know it or not. Your job isn't to live like a spy or not Jason Born. Your job is to know your patterns, understand what your patterns reveal, and make smart adjustments that protect your OPSec, your operational security. So next time you leave your house, ask yourself: if someone was watching me, what would they learn? That question alone will change how you think about your routine. All right, I'm going to put my tinfoil hat back on because I'm done with this podcast. If you want to reach out, practical prep podcast at gmail.com. Again, I'm on the Twitters, prep underscore podcast. So if you tried that two-week pattern exercise and found something that surprised you, I would love to hear about it. Send me an email and let me know. All right, folks, as always, please be careful out there. Take care of one another, bury your routes to work, and until next time.

SPEAKER_00 25:01

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