LPRC - CrimeScience – The Weekly Review – Episode 208 Ft. David Thorp (Cobb County PD)

Episode Date: July 8, 2025

In this episode of the CrimeScience Podcast, LPRC's Director of Research, Cory Lowe, sits down with David Thorpe from the Cobb County Police Department. The conversation explores real-world crime prevention strategies, the role of law enforcement partnerships, and the importance of data-driven approaches in reducing crime.

Hi everyone and welcome to Crime Science. In this podcast, we explore the science of crime and the practical application of this science for loss prevention and asset protection practitioners as well as other professionals. Hello everyone, my name is Corey Lowe and I'm director of research at the LPRC and I'm joined by David Thorpe who is with the Cobb County Police Department. David, if you could just start off by giving us, tell us a little bit about yourself and your background. Yeah, absolutely. Thanks for having me, Corey. I've been with the police department for about 23 years now. Prior to getting in law enforcement, I actually did work in the retail space.

Shortly after getting out of the Marine Corps in the late 90s, I found myself needing a job while I was going to college up in the Boston area. So I wound up working for two separate retail, clothing retailers, about a year and a half for one, about two and a half years for the other and then I find my way down to Georgia about four and a half five years later and that's where I was introduced to policing and so I

started out as a patrol officer as most officers do and I really started to I guess have desire to do more with cases than just write incident reports and hand the incident reports over to detectives and so I began diving into on-scene investigations much more deeply and fortunately for me back then we had access to some pretty cool technology. It's hard to believe that about 18 years ago in 2007 our department was demoing some vehicle-borne cameras that were connected to a license plate recognition system. And I was able to use that technology to help identify and locate stolen vehicles, as well as doing some traditional investigations. So I really started to have a passion for technology-led policing back then and had

some success when I was transferred over to a few detective units. I wound up working for a property crimes detective unit at my local precinct after I had been with the department for about four or five years and really just started to cut my teeth there, get a lot more experience, and I was transferred up to the crimes against persons unit and I was assigned to the robbery unit. And I continued to use a lot of these technology driven policing methods, facial recognition, different LPR programs,

and had some significant success with it, as well as being introduced to some GPS tracking technology, which obviously comes in handy when you're working on a robbery unit during the daytime, bank robberies and all. And so I want to spend a significant amount of time in investigations and then spend some time on the road as a sergeant, helping develop and train officers in the use of some of this technology. I found myself back in an investigative unit, supervising some grand detectives.

Then I got promoted to lieutenant, went back to the road, and then in about seven or eight months, there was an option for me to come up to the real-time crime center and we were just developing an RTCC and looking to staff it. Due to some extenuating circumstances, they needed somebody with some depth of knowledge.

And I wound up getting transferred up to the real-time crime center and started within four days of being notified. So that's a pretty exciting time. And I look back now on the history with my department. And little did I know it at the time, but there were very deliberate steps getting me to this position. Just having a deep knowledge of different LPR systems and being able to have some success with them, as well as all the other integrated technology we use.

So I was very fortunate for that transfer. Four years later, I've been there this whole time. Awesome. Yeah, and we had the great fortune to have you come speak at Impact, and you talked about two case studies with GPS units, and those case studies were just absolutely amazing. It was a very, very well received presentation

at the conference. Now you've been with the RTCC for four years now. We're now partnered with the National Real-Time Crime Center Association. It's a partnership that's turning out to be fruitful, even though it's still pretty early days. turning out to be fruitful, even though it's still pretty early days. But how has your role with the RTCC evolved since you first joined them, you know, four years ago? How have things begun to change and what do you think are some of the greatest changes happening

in RTCCs? Well, for starters, when we first began the RTCC, we were solely focused on integrating a lot of the technology that we already had. Camera streams from municipal cameras, shared cameras from some other departments within our region. And really, little did I know back then how large the RTCC world could get or was. But I think in a word, I'll use the word exponential.

I think there's been exponential growth in public safety technology since I started four years ago in the RTCC. So initially, it was just bringing those camera streams, as I said, from our own county-owned assets and then branching out. And really the impact of an RTCC is not just, in my opinion, not just those camera streams that you own, but community partnerships, leveraging those partnerships to get integrated camera streams, and light up the map, if you will, and increase your footprint of community partnerships throughout your area.

It's a different challenge for every agency. We have about 770,000, 780,000 residents within our county. We share a lot of law enforcement responsibility with six or seven different police agencies. When you think about almost 800,000 residents over 345 square miles in our county, that's really one of our largest challenges, is getting access to streams, building partnerships, and then maintaining those partnerships because they do require maintenance, they do require

frequent communication. Technology is great, but oftentimes things go down, devices get unplugged, properties change hands. And so it really requires a lot of hands-on time. And so fortunately we have somebody on staff, you know, RTCC that focuses on that. So nowadays it seems like there's a lot of different technology that at some point in the past was disconnected from the RTCC.

And now I think we're starting to see the importance of seeing everything on one map to allow us to respond to things much more quickly. Some of the access points that we have to this data are standalone, and they do not incorporate into the RTCC. However, the more tabs or the more Cloud-based services you have that are open separately,

it makes it very difficult to see everything in relation to one another. The FBI, I think, states something like 70 or 75 percent of crimes are committed with the direct or indirect use of a vehicle. And so access to our Department of Transportation traffic cameras is imperative for the success of anything we do really in the RGCC, not just for us, but also to support and serve the community. Because cameras capture direction of travel for vehicles, they capture all sorts of attributes about the vehicle, and then using that in

conjunction with our license plate recognition cameras, we can usually identify a vehicle or a registered owner pretty quickly. So managing all those different cameras, managing all those different integrations is one of the biggest challenges we have, but it's a good challenge to have. Yes, it is. Just thinking back, right now at the LPRC, we're really focused on building out our fusion platforms. And what I'm referring to here is, we're calling them fusion platforms. There's a lot of different ones, but there's Axon, Fuses, Motorola Command Central,

Wear, Flock OS, even 3SI's direct dispatch and Seagraph from Genitech. Those are some fusion platforms. And what they do for both retail and law enforcement is they fuse together all these sensors so that instead of looking at all these different. So that instead of looking all these different tabs and windows, it's all in a single pane of glass or as close

to a single pane of glass and you can get so that you can not be distracted by going to have to switch between tabs or windows. But then it's also there also fused to platforms because they can fuse together both private businesses and the public sector law enforcement and other agencies. It's it's very difficult on audio to do this, but it's it's like you have this overview. So say you've got that vehicle

that's moving down the highway and you've got a GPS tracker in that vehicle. At the same time, you can start getting LPR hits and opening up the traffic camera feeds and all of that. So it's pretty exciting times in my opinion. Are you all using the fusion platforms at your RTCC, right? We do, we've got a FUSIS by AXDON is our contracted vendor and we have several different license plate recognition companies that that dump LPR data into their. Yeah, excellent.

What are you seeing your common pain points today? What are your greatest challenges in RTCC work? But I think. I kind of touched on it just before just before we started talking about the different fusion centers, but one of the largest challenges is is getting integrations for a smaller agency that may not be the challenge, but I will tell you for our agency that is one of the challenges getting integrations, keeping them. Another challenge for us is we in law enforcement, we are here to serve, we're here to provide that service to the community. And sometimes our budgets lack, you know, I talked about the advent of, or the invention of all these different technologies and how things

have been growing exponentially. Now, it's like a kid walking into a candy store. You see all these things you want. You just can't afford them. And so we have to be diligent about how we use technology. We've had to sunset some technology that we just don't see a big impact on or it's not making an impact for our department and thus it's not making an impact for the community. And so we've had to pivot a little bit. So, you know, as an agency, I can tell you law enforcement is obviously a government entity and things can move very slowly. So budgets don't automatically inflate quickly. It's a struggle to try to get the technology that you want to help support the community.

And so in summation, I'll say that sometimes we're slow to react and slow to adapt and adopt new technology because there's just so much out there right now. And ultimately, when one vendor or one technology partner sees success in the marketplace with another vendor, oftentimes there is a large overlap. And so now one vendor who used to produce ABC widgets, now sees another vendor producing, you know, XYZ widgets, and they want to start dabbling in that. And so there's a lot of crossover, there's a lot of overlap in what technologies are available, and not every partner produces something that we need across the spectrum. And so having the ability to talk to different vendors, talk to different technology partners,

get demos and trial periods for these products is imperative for our success and to ensure that we're actually procuring something that we need and we're not simply just keeping up with the Jones next door because what suits our agency and our department in our community may not necessarily be a good choice for somebody else and ultimately vice versa. So those are the three things that I would point to as those pain points. Yeah, I can definitely see all of that.

I think in retail specifically, since we work on the loss prevention side of things, I think one of the challenges that I've seen between real time crime centers on the retailers is kind of the scope with which each works. You know, you're with Cobb County and

so you've got to interface with all these different businesses, you know, you're with Cobb County and so you've got to interface with all these different businesses. You know citizens, you know all these all these different organizations, things like that. On the other hand, you know, a retailer like Target or Walmart might just have a few locations in your area and thousands of locations elsewhere that they have oversight for. So Walmart might just have a few locations in your area and thousands of locations elsewhere that they have oversight for. Sometimes what I've seen is that there's a disconnect between

your folks who are doing the community outreach and trying to get people integrated or talking to people at the store level when it's the very top of the organization that you really have to be talking to to get the integrations to happen. So can you speak a little bit more to that and how that creates challenges with working with some of the more technologically advanced retail companies that have some really cool stuff, but getting with the right people can be very difficult. Absolutely. Sometimes the analogy I use is like a puzzle. Sometimes you find the right piece in that box and it just goes together easily. Other times you could be searching for hours for that one specific piece of that jigsaw puzzle.

It takes a lot of effort in some cases to get that piece in the right place. I will tell you that we have waited patiently for up to 18 months working with a retail partner at a shopping plaza to incorporate with them. But ultimately, not everybody is aware of what a real-time crime center does. In the grand scheme of things, RTCCs are fairly new. Some of the large agencies have been around for 10 or 12 years operating with a real-time crime center, maybe even 20 years, but these smaller agencies don't have the wherewithal or even the space for that RTCC.

And so community knowledge is just not there. And so that is one of the challenges of trying to get, excuse me, an integration is that at the ground level, when you walk in the front door to a brick and mortar retailer, whether it's a small local or regional retailer, or even a large nationally known retailer, you're working with them every single day to prevent shoplifting and organized retail crime and to increase safety and security.

And they want to partner with the police department, right? I mean, just like you said, it's a one-to-one conversation, and they couldn't think of anything better to partner with the police department because they have a passion for the same things that we do. Then at some point in the conversation, the concept of an RTCC and what it means travels up the chain on their side, and it gets lost in translation or it dies on the vine. Working with our, not just retail partners, but working with these, as you said, fusion center companies,

these RTCC companies, their technology companies, to have larger conversations with corporate leaders, whether it be legal or loss prevention or asset protection, is very important. So, you know, thinking of it as kind of a one-two punch, we are operating at the ground level, and they are operating oftentimes at the corporate level. And between both conversations, we've seen pretty good success. But obviously, it can be frustrating to see people in a retail environment wants a partner, and then somebody winds up shutting it down because they're, like I said, there a something that's lost in translation, or somebody conjures up the idea of surveillance. And in most real time crime centers, I can tell you in ours, specifically, we're really incident based. So when an incident happens, that's when we start accessing the cameras. But I think I remember one conversation that we had on teams call with you a while back was the

question that you would pose to a retailer is, can we have access as a law enforcement agency to all your cameras all the time, every day, all day? And the overarching response was a one word answer, no. If you want a two word answer, you're going to have to bleep it out. But it, no. Right, if you want a two word answer, you're gonna have to bleep it out, but it was no. And then fast forward to a hypothetical incident. Well, it's what if a shooting happens or what if there's a missing child

or what if you have violence at your store? Would you want officers to immediately be able to access that to develop information in real time? And the answer is a polar opposite. It's a 100% absolutely. Well, where do we meet in the middle? And so success stories certainly speak volumes in sharing those success stories. And once one retailer has some success in that sharing of video, identification of a suspect, appreh identification of a suspect,

apprehension of a suspect, they're gonna start seeing some of those lost numbers go down, the shrink numbers go down, and hopefully they're sharing that information. And through just natural organic conversations, and obviously I have to highlight LPRC, I was very impressed with the conversations that I had down there at the impact

conference and the integrated conference a few months ago. And a lot of conversations that we had locally in RPD post-conference came directly from conversations we had at that conference and some of the success stories that we shared. So those are the things that are the challenges for us. But I think as more retailers come online, then it will be an obvious choice, an obvious solution for these other retailers. So it's the, you know, I always use the term FOMA, right? The fear of missing out. When you see somebody else having success with it, you want to have that same success. And so it's a national inclination that once word gets around, that we'll partner with

them. Excellent. Those partnerships are absolutely essential to success of real time crime centers. At the LPRC we're always talking about intelligence building. You can't do it with everything being in silos and we were talking about technologies earlier. Personnel and people and organizations having those that those connections between organizations is just just absolutely essential.

So that's what we've been trying to do at the connections between organizations is just absolutely essential. That's what we've been trying to do at the LBRC is bring together the real-time crime centers and the retailers so that we can have these higher level discussions to make some of this happen. Sure. I think that the future is bright for real-time crime centers. I hope so. I want to talk about-

I think so. real time crime centers. I want to talk about a few of the technologies that you are, were you seeing the most success? What some of those are? And can you describe some of the successes that you had with some of the technologies that you've been using? Yes, absolutely. I will say really the bread and butter of our real-time crime centers is any integrated camera. It doesn't just have to be an LPR camera, but it could be a camera from a DVR or an NVR and a retailer or other business. LPR is obviously a big component. And then one other technology that we've had a lot of success with is GPS tracking technology. As you mentioned earlier, in my presentation, I shared two success stories we've had with two separate technology companies that do GPS.

And what's great about the GPS technology is, and I'm thinking about this not just from a law enforcement angle, but also from that time when I was in retail, a little short story is that I was a retail manager and we had apprehended a shoplifter. And that shoplifter was in the office with me. We had escorted him into the office and he wound up pulling a knife on me. And so that's not a place that anybody wants to be. And so shoplifters and organized retail crime suspects can turn violent in an

incident once they know they've been caught. And the great thing is that in modern retail establishments, nobody has to actually confront the suspect. That GPS device, if it's stolen, when it's stolen, either on one item or it's simply on an item, and there are 100 items that are stolen in a large-scale smash and grab, it'll ask for the apprehension to take place as far from the store as possible at a time and location that's convenient and safe for not just law enforcement, for the suspect's apprehension, and also for any bystanders. So the GPS tracking technology is really great. And again, we've had success with it. The two success stories I shared were with large retailers

where there were some women that had come in and bear hugged, you know, a rack of clothes. And they're always after one particular brand, whatever's popular and whatever's, you know, selling on the open market. And so they came in, scooped up a bunch of property, and then fled. And using the GPS tracking technology is great. I remember working as a robbery detective tracking

die packs and stolen cash from banks 15, 20 years ago. And we didn't have LPR back then. We didn't have integrated cameras with our DOT. So we had no idea what vehicle these guys were in. So the integrated technology is a layer on top of the GPS technology. So it allows us to build information and we can use those two technologies in concert with one another. And then you've got LPR, not just the DOT cameras, but you've got the LPR footage, you've

got a crystal clear image in most cases of the vehicle, the attributes of the vehicle, and hopefully the license plate. And so in both of these instances with these GPS tracking technology companies, we were able to identify the vehicle. We were quickly able to receive photographs from the retailer, because this relationship, if you will, Corey, has already been established through a partnership, and so I'll call it a digital handshake.

The retailers want to see success, the GPS tracking companies want to see success, and we certainly in law enforcement want to see success. And so that digital handshake is imperative and it's already established. And when something's stolen, everybody knows what to do. So in a traditional law enforcement environment, it could be days, if not weeks

before we get images of the suspects because somebody's not in the store to provide them or the district loss prevention manager is on vacation or away and they can't access it. So for us to have a picture of the suspects fleeing the store with what they're wearing. It's almost like a immediate show up or a lineup. You've got information that you now convey to an officer. So in both of these cases, we wound up sharing information, working with license plate recognition software to identify intersections and cameras from the store to two or three jurisdictions away, 15-20 miles, we're able to corroborate information, get that information out to officers and apprehend them and in most cases recover the merchandise. And then

that's just the tip of the iceberg though. We're able to not just identify them, but now all of those retailers that these suspects have been targeting know who these people are. Those retailers share the information through that intelligence sharing platform. And all of a sudden, all the retail incidents across a region starts to light up, and you start connecting the dots and understand that these women have been targeting several stores in a metropolitan area over the past two or three months, and then those cases can go from being unsolved to solved. So that's just a high-level view of what some of those success stories are.

But if we have time, I'll tell you about another success story we had that didn't involve the GPS tracking. So let me know if you have any questions about those two scenarios I just told you. No, I think those are amazing wins. I'd love to hear about the next one here about sales volume. Yes. amazing wins. I'd love to hear about the next one here about sales volume. Yes, so this happened about two years ago and really it's one of the things that retailers need to do and law enforcement real-time primary centers need to do is establish that data pipeline. Certain information that's conveyed to a law enforcement agency is important. A lot of times,

a retailer, whether it's a mom and pop retailer, a small regional retailer may not know that the local police department has all these additional resources now in a real-time primacenter, three or four people working together, not just officers out in the field working together, but two or three people sitting next to each other working in concert with one another. And getting information out is important. So in this particular case, it was a computer digital electronic store, and they were familiar with this offender.

The offender was wanted from a previous, for a previous theft. And the manager employee got on the phone and relayed specific information about that, who the person was, what he or she was wearing. And when they were confronted, the suspect then left. And so they hopped into a vehicle and it was a brown or black Chevy Malibu. And so the first thing we did at that point was get on some of our DOT cameras. We accessed them and I could see the vehicle leaving the parking lot. And so I continued to access cameras down that surface street, down that corridor. I think I accessed three cameras. Traditionally, an officer's going to get dispatched to the store. But if you put a dot on the map, if you get on the radio and say, hey, that vehicle is leaving, you're confirming what happened. You're giving real-time

information to that officer. And even though there's no GPS tracking technology in this case, it was the correct, accurate accurate relevant information being relayed from the retailer to law enforcement and then us doing something with that in real time. And so over the course of about two minutes, we access four or five cameras. I updated the officers to where the vehicle was going. And now I've got a dot on the map where this officer is going to go. Like that old phrase that Wayne Grespie has often quoted as saying, don't skate to where the puck is, skate to where the puck is going. So previously the officer goes to the store and he's going to take a report and that's not exciting

and then he's going to turn the case over to a detective and that detective is going to be three or four days behind because that's just the nature of the beast. But in this case, I was able to tell the officer where the vehicle was in real time within a matter of milliseconds of it passing an intersection. And the officer got behind the vehicle and put information out on the radio that he was there. And then he made a traffic stop. And now we can safely apprehend that suspect about three miles from the store. The officer can wait for backup to detain him and you've identified the suspect, you've fulfilled your commitment to the community, you've fulfilled your commitment, you've essentially closed the loop and you have restored an incident and a retailer back to its original upright position, right? I mean, you've completed the project.

And so relevant real-time information is important, and accurate information from the retailer is important. Yes. So that's actually where I was wanting to go next. In loss prevention and ORC investigations, the focus for the last couple of years has been on increasing. Increasing. The collection or improving the collection of intelligence about organized retail offenders and groups.

And you know that's made those cases actionable, but for prosecution because all that's happening on the investigation side, not on the real time response side. When we're thinking at the at the LPRC, we're very interested in, you know. Yes, we want actionable intelligence, but the question that at the next question is actionable by who right? We want to get the right intelligence to the right people at the store level. We want to get the right intelligence to the right people at law enforcement. And then we also want to get the right intelligence to the right people in investigations. Right. So, you know, if we have that real time intelligence and, you know, there's all these factors to drive law enforcement response. You know, law enforcement to take a call for service much more seriously and going to have a better

response if they know. What's going on? Whether there's something's actually they come from responding to the call right? No one wants to waste their time and shut to something that one's no one's enthusiastic about that, but if they're getting information directly from a colleague at the law enforcement and law enforcement, that's something they there's a little bit more credibility to that. Right? When they say hey, skate to this this place,

because this is where the offenders going that's much more actionable and probably going to be much more fruitful to them. Officers are just as rational as anyone else in those regards. So very good stuff there. What other factors do you think drives law enforcement or do you know drives law enforcement response? I mean, when you get two calls, what are the things that are making you say or making law enforcement

say I'm going to respond to this one versus this one? Well, first and foremost, any call that comes into an emergency communication center, a 911 center, is going to be triaged. And we have, as most agencies, if not all, have priority responses. Something that's a threat to life, something that's an emergency is going to be prioritized much higher than an average alarm call. And so think of four boxes, if you will.

And every time a call comes in, the dispatcher has a choice to make about what the call is and which box that's going to fit in. We're not talking about the type of call, whether it's a theft or a burglary. We're talking about the priority. So they put it in one of those four boxes, if you will, and based on the totality of circumstances from that now-owned call, the totality of circumstances from that now-owned call. Has it just occurred? Did it occur previously? Oftentimes, retailers have policies and protocols where they're not to call for an hour.

That can really change the response of an officer and just an entire shift. If the crime is in progress, well, then obviously the suspect is on scene. Think of it as solvability factors. Our detectives operate in solvability factors and oftentimes, by design, if there are not enough solvability factors in a case, the case will not get assigned because there's just so much legwork

that would have to be done. And most of that work would be not fruitful. And so is the suspect on scene? Is there a good description of them? Are they currently offending? Have they previously offended? All those things again make a difference. And so what I love about the real-time environment is that to me it doesn't matter what the offender is doing. It could be a shooting or an armed robbery or it could be

somebody who just shoplifted some crest white strips or a bottle of Windex. To us, since we are essentially one step removed from that environment, all that's just the cameras no matter what. And so we can see a lot of impact, not just in the violent crime, but we can see a lot of impact in smaller crime

because that still affects retailers. It affects large retailers, it affects mom and pop retailers. And so for us, it really doesn't matter what the priority of the call is. We can still access the same data sets and provide the same information if you've stolen $10 or if you've committed a heinous felony and injured a person and then fled. So for me, that's that's one of the exciting things is there's always work to be done.

We're just not sitting around waiting for the big show or waiting for some heinous criminal event to occur. We can we can do a lot with many of the calls for service. Thank you very much. So so far we've covered, you know, history. So starting off with your background and some case studies and you know the types of things that you're doing today at the RTCC. Now I want to talk about where things are going in the, you know, about where things are going and the opportunities and partnerships and technologies that you're most excited about. So let's just start with technology. Is there anything out there that you've seen that is just like, oh, this is going to just change the nature of real-time crime center work if this really scales? Anything that comes to mind in terms of technologies you're excited about? So I will tell you about two things that I'm excited about.

One, and I know a lot of people talk about it, and it's kind of painting with a broad brush, but AI and artificial intelligence and the machine learning aspect, that's been in a lot of this technology for a number of years. But what's great about it is it's becoming more accurate. If my suspect in a call for service is driving a red pickup truck, I want to be able to identify which cameras in a matter of

20 minutes have picked up a red pickup truck that matches that description. And so in real-time environments, accessing camera streams, you know, one after another can be very cumbersome, and it can be slow because you access it, you have to make a determination if the vehicle that you're looking for already passed that point, you can rewind it, and then meanwhile you have to worry about accessing another camera stream. So obviously having somebody else to assist you is imperative to the success of that incident. So AI and being able to identify the path that a vehicle took, attributes of the vehicle,

and provide me with a bunch of different pictures so I can identify, you know, that has to be, to me, that has to be a human element involved. It's not just AI saying, go stop this vehicle. It's saying, hey, we come through X amount of video and deductive reasoning and the algorithms tell us that it's going to be one of these five vehicles. And then the human element comes in.

And then what AI has just done is done searches that would take a human, probably 10, 15 minutes to do in a small scenario, much longer in a large-scale scenario maybe. Now you've got this buffet of options and you look at all the attributes and there's something about the vehicle that's gonna stick out. And so we also talk about AI in the realm of security and safety and if you've got a pharmacy

that closes down at eight o'clock at night, there should be nobody in there at one o'clock in the morning and this AI can tell me whether or not there's a person in the building. can tell me whether or not there's a person in the building. And so that immediate report to a human in a real-time crime center or law enforcement agency, that will generate access to camera feeds. And then we can corroborate whether or not somebody's actually in the business. We talked about priorities before. That's the difference between an alarm and we'll find out what happens when we get there and a response which is, hey, there's somebody actually in the

store. And then all the other things that are connected, LPR, DFT cameras, all those would be populated with the same information, the height of the person, whatever they're wearing. And so that search capability is very important. And so the other thing I'll say that I'm really excited about is just there are a lot of siloed assets out there, not just that we don't have access to, but even within our own law enforcement agency that we have to access. And so having a technology that brings all those together allows us to make decisions much quicker. It puts that buffet of options in front of us in a matter

of seconds instead of this laborious long time, long-term searching by a human. And so we can do a lot more with less, much quicker in that environment. And so I'm excited about the AI being laid on top of some of these camera streams, and then also tying all those different disparate data sets together and being able to leverage small information that was kind of tucked away and that we didn't know about and have

that be relevant in a real time scenario. So I actually want to go back a few questions now. You're talking about tying things together in real time and the difference it makes to be able to see you know that that person who's at a chain drug store at 1 AM in the morning. That's not supposed to happen and go back to those response factors.

Well, what's going to drive a different response? So say you've got two chain drug stores. One you have sensors on the site that say someone's at this location there inside the building. Maybe maybe you know alarm has gone off and you've gotten notification of that versus another one where you have you know not only do you have the alarm, you know someone's in the building, but you also interior cameras showing what that person is

doing on the inside. How is that going to if you, you know, you've got one person to respond to one of these incidents, which one are you going to choose and why? Well, the answer is obviously easy, right? So we would wind up responding to the incident that clearly shows there's an offender in the store. The only person that potentially could be in the store at that or the pharmacy at that that late hour could be a cleaning crew. But with access, we know that they're there. You know, I mean, they can come in, they can enter certain key code on the keypad and then that that bypasses, you know, any, any AI. But if somebody But if somebody throws a big rock through the window, or the front glass door, that's going to generate response. And so it will be a much more heightened response. If we have units available, they would respond to the crime in progress because it's validated.

So there's an alarm company, I can't remember the name of it, but they've been advertising in the local area for years, and they always talk about their alarm systems, their key panels, or their alarm panels are actually have a,, you have an officer that responds. But if you can say, hey, we have live video, the alarm system says we have live video of a person that's actually in here taking silver off the mantle of the fireplace, then that's going to provide more information. Officers are going to get excited to respond. And the priority, ultimately, of the call for service is going to be much higher. And so, again, the answer for your question

is we're going to want to respond to the one that has the person in it. And so, ultimately, we just need just a little bit more information than we've had to make a difference. And the reason I brought that example up was because a couple of years ago, we were dealing with a group of gang members who were stealing Dodge products, and they were driving around in Challengers and Chargers and Durangos, and they were breaking into pharmacies at 1 o'clock and 2 o'clock in the morning. And we would get the alarm call and we would respond. And we inevitably would arrive to a pharmacy that had a broken window and all the pill bottles were gone. And it was always an uphill battle

to identify who these folks were. And just a little shift, just a two millimeter shift in the way we respond can really make a big impact in identifying three or four people. Now you've got a vehicle that's associated with them. And so we ultimately would share that information with our law enforcement partners and in this case a retailer and that would have an impact. Yes. So we've gone for a pretty good while now. I did want to mention one more thing that at the LPRC we're increasingly thinking in terms of this connect,

detect, affect web of where we're trying to connect all these sensors together and then being able to know where all of our sensors are relative to each other. And then finally, where all the personnel and people who can actually respond to an incident are. So not only in this case, having all these technologies tied together helps you to understand where the threats are

and things like that, but you can also begin to understand where the resources are relative to that threat. So if you have that rich intelligence about the crime in progress, and you know that there's a unit nearby, with all of that real time intelligence that you have about not only the threat,

but also the resources available to address the threat, you can really make those connections a lot quicker with that real time intelligence, right? Absolutely. Yeah, so that's, I think that that's where I wanted to wrap up today. David, it's been an absolutely fantastic conversation today. So thank you very much for joining us again.

We really appreciated having you at the Impact Conference to speak to all of our members there. And we're really looking forward to the work we're gonna continue to do with the National Real-Time Crime Center Association, of which you are an important part. So thank you very much, David. And thank you for joining us. You're very welcome.

Thank you for having me. I appreciate it. Thanks for listening to the Crime Science Podcast, presented by the Loss Prevention Research Council. If you enjoyed today's episode, you can find more crime science episodes and valuable information at lpresearch.org. The content provided in the crime science podcast

is for informational purposes only and is not a substitute for legal, financial, or other advice. Views expressed by guests of the crime science podcast are those of the authors and do not reflect the opinions or positions of the Loss Prevention