Artificial Intelligent, The Ultimate Breakthrough Technology

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Artificial Intelligent, The Ultimate Breakthrough Technology

Greg Brunelle:    It’s not a criticism of any of the solutions we use now in emergency management because those are the solutions we have available to us. That’s the tech we’ve had available to us, but when you looked at, again, not to be Glib, but the spray paint on a map, for instance, to that paints and area, red for earthquake damage or blue for water exposure. It’s not doing hydrological and hydrodynamic coupling to really say, well, what’s it doing to the built environment?

Todd DeVoe:      Hey and welcome to EM Weekly and this is your host, Todd DeVoe speaking, and today we are talking about artificial intelligence and emergency management. We’re going to be discussing what is AI and how it helps EMs do our job. And I’m talking to Greg Brunelle from One Concern, which is one of the leading emergency management AI companies out there. Greg has an extensive background in emergency management and public safety and he’s from upstate New York. So you know, you can’t go wrong with a guy from upstate New York. Right?

Todd DeVoe:      So before we get into the interview, we need to talk about books. What book do you think belongs on an emergency managers bookshelf, and this is the question that we’re discussing over at EM Weekly’s Facebook group, so if you’d like to get into discussion, jump on Facebook and join the EM Weekly’s Facebook group and I’d like to hear what you have to say about what book belongs on the emergency managers bookshelf and this Thanksgiving coming up we will be discussing the top 10 books that won the vote over there and why they belong on that bookshelf. And I’d love to have your opinion as well.

Todd DeVoe:      So let’s get into the interview. Hey, I’m happy to have Greg Brunelle with me here today Greg, welcome to EM Weekly.

Greg Brunelle:    Hey Todd. Thanks so much for having me. I really appreciate it.

Todd DeVoe:      So Greg, let’s Kinda start off about you a little bit since you do have an extensive background in emergency management. How did you get into EM.

Greg Brunelle:    So in 1998 we had a really devastating ice storm that knocked out the power to South East Ontario and upstate New York for over 30 days. We’re really catastrophic. Four and a half inches of ice and I worked closely with those of us that could get into the hospital to help coordinate that response and really found that I had a knack for incident management. And as a result of that, the hospital put me in charge of an early version of emergency management in the hospital. And my first mission set was to coordinate us around y 2K. Got involved with that and then serendipitously, the next year, the county I was living with took the old Fire Coordinator’s office and the old Civil Defense office and merged it to create a new emergency management office. So I took a gamble, left the hospital and became deputy director for fire and emergency management for the county overseeing the fire services offered by the county, like the swift water team and Hazmat team, and coordinating the 911 center and trying to transform an aging civil defense program into a contemporary all hazards comprehensive emergency management program.

Took that job and started in June 26 of 2001 had my first LEPC meeting, which at that point was really focused on SARA title III our listeners would know, you know, that’s HASMAT was taking that to the all hazard space and the meeting was scheduled for 9:00 in the morning on 9/11. The leadership from military base in our county, the border patrol and others came to the EOC. And while we were very far removed, very far removed from the physical impacts of 9/ 11 that day we were in New York state. We’re a border county. We did have a big open military base. We did have to take some protective actions and of course like everybody in America, we didn’t know what else was going to happen and of course all of us in Emergency Management Experience that paradigm shift and that real adoption and creation of homeland security, which wound up to finding my career for awhile…

Todd DeVoe:      when you move from the public sector and now you’ve gone into a new adventure and the in the private sector with doing artificial intelligence. Tell me a lot about what your company’s doing right now and who you’re working with because there’s some pretty exciting names, on your company’s roster.

Greg Brunelle:    We’re really fortunate to have an incredible team pulled together and everybody, a lot of people say that about the organization they work with. We’re a small company, but rapidly growing and the brainpower here and the star power is just incredible. I joined one concern two and a half years ago as a senior advisor before truly a startup. At that point, the vision that Ahmad Wani, our founder has for global resilience, beginning of that local level and a transcending across the globe. To truly defining resilience and truly supporting resilience really caught my ear, caught my eye, and caught my heart and I wanted to be part of this with artifact would, would what One Concern is doing… Let me start there, what One Concern is doing is for the first time ever bringing real artificial intelligence in particular machine learning directly to emergency management and all of the public safety critical infrastructure and stakeholder groups that support emergency management.

Greg Brunelle:    So Ahmad experienced several tragedies as he was growing up. He experienced a catastrophic earthquake in Kashmir where he grew up in 2005 and wound up, as a, as a physical engineer coming to the United States to continuous studies at Stanford. And when he went back in 2013 to get engaged. Actually his family survived, thankfully a catastrophic flooding events. And there’s no exaggeration to the story. The dams that failed flooded his village for more than six days. And during that time, he and his family with very late minute last minute notice from law enforcement were able to get up on the roof and they spend six days in the attic and on the roof of their house while they, you know, they, the deleuze continued around their village. They survived that the family across the street had recently had a wedding and therefore had leftover apples and bread that they were tossing to them.

Unfortunately, that family was lost in that flood. Ahmed had already committed himself to life safety engineering to bring contemporary can computational power and the emerging technology of artificial intelligence, machine learning to help the first responder and emergency management community to truly build resilience. But obviously, as you can imagine, this reinvigorated and solidified for him that vision. So He created One Concern, One Concern is to save lives and build resilience. And I joined as an advisor, as I said a couple of years ago, and for our series a, you know, I joined the company full time doing global engagement, particularly here in North America with public safety community. We have been so honored to bring in some incredible names and capabilities in this space. First of all, the development team here is, you know, bar none, some of the most brilliant people working in AI right now.

I’m physically right now sitting in our offices and university ave here in Palo Alto about five blocks away from Stanford University. We pull from all of the large universities around the globe, to support the development side. But technology is only as good as the practical application, right? So in order to translate the brilliant algorithms, the brilliant capabilities to practical application, we’ve been able to recruit and bring onto the team names that everybody knows, like Craig Fugate, former administrator of FEMA for seven and a half years under Mr Obama and widely recognized as a global expert in emergency management. I’m not just recognize, but still to this day actually to this minute traveling around the globe speaking on this topic. I had someone once say to me, and I’ve never known this to be true. No one cares more or knows more about emergency management thing. Craig Fugate.

And when he learned what we were doing, in particular the power, and we’ll talk more about this later, I’m sure the power of our application as it relates to mitigation, how can we stop the disasters we can stop and the impacts from them and how can we lessen the impacts that we can’t, you know, for disasters. We can stop. Craig said, I’m on board. I want to be on the, you know, I want to be on this team and he’s not just hanging his name on this company. He’s working here at least 50 percent of the time. So I’m so honored to work with and for Craig. Most of my work week. We’ve also run on Jim Featherstone former management director for the city of Los Angeles, again, nationally and internationally known expert. I’m a couple of other names that some of us may not be as familiar with, but the work they’ve done, people know Judith Roden, who invented the 100 resilient cities concept, the Rockefeller Foundation, when she was president there. Judith’s on our board. I’m Andrew Name, who is the godfather of Ai and America, artificial intelligence. He had been to the Google brain, one of our senior advisors. It’s just really an incredible group of people and I’m just so honored to bear witness to this emerging capabilities.

Todd DeVoe:      So this is great. You guys have a really fine team there for sure. And so now you’re taking the concepts of, of what you’re putting together a and we’ll get into that in a second and then you have your team here that’s really able to put the practical application of what you’re putting together. Now I, you know, before we had this interview, obviously I went onto the One Concern a webpage and took a look at some of the stuff that you guys are doing and I know you guys have some stuff in the, works as well, but I know right now it’s sort of a flood map if you will. And I know you wanted to do some additional maps as well if you want to get into those. So how does it work on the practical application as an emergency manager? How do I make that into my eoc and how does it help me? On a daily basis.

Greg Brunelle:    Absolutely. In fact, just this morning I spent my day today in San Francisco, Department of Emergency Management, EOC supporting their exercise. They’re either using our solution for that. They were doing a catastrophic earthquake scenario, focus on Mass care and just amazing team in San Francisco. We’re so lucky to have them as an early partner. Absolutely, man. Absolutely. That’s what what he needs it. It’s a first glance. What are we providing you, your. You’re getting a map. What we’re providing is highly accurate, highly reliable, hyperlocal damage assessment, predictive analysis. That’s machine learning. We’ll talk more about that predictive analysis of what’s going to happen when the ground shakes, the water flows and very soon if there’s a fire and then all the other hazards to follow on and intermingling these hazards right together to see the cascading consequences, to see the first four secondary, tertiary impacts of a disaster, but whereas you brought up a good point, isn’t it?

It’s a flood map. Right, and there’s a lot of great companies that are that can produce a flood map. Some of the technology that we use in emergency management and you know, having, having been director of operations for New York State Emergency Management, we flood pretty regularly. so I’m familiar with flood maps, right? And some of them nobody’s fault. It’s older technology. It’s just what we have available to us. I call it blue spray paint on a map, right? We think the water’s going to go, all right, well let’s layer in some other stuff and see what’s in that blue spray paint that we just put on there. It’s not dynamic. It’s static, right. What we’re doing is because of the. We were at the nexus, now all of us are at this nexus. This company in particular is now leveraging the nexus in that nexus is there’s so much data and information out there that we’re now able to pull in seamlessly.

Okay. From literally thousands of different data sets from thousands of different databases. Our particular solution relies on both open source as well as proprietary information. So we do spend some money getting that proprietary information, but you know, in different settings we all hear about all the data that’s collected about us. Well, it’s also collected about our cars and our homes and in our towns and villages and cities. So we pull all of that together, number one. So the amount of data we had that we could pull together. We’re at the crossroads. We can do that now. The computational power available to us, right? If we looked at a Moore’s law curve and, and how we’ve gone from the Atari when I was a kid up to the raspberry Pi now, which you know, you can buy for $65 and have all this computing power, you know, your iphone has 10 times the computing power of a, of a GPS satellite.

I mean it’s just incredible. So we’re housed on the aws cloud and when our solution runs literally lights up millions of servers and that computational power is just unprecedented. The third area that we’re at this nexus with is now a maturation and an access to decades of a mature science and research in areas like building an engineering right in environmental. How does, how does, how does the natural environment behave when a disaster happens, and because we’ve been taking emergency management seriously for the past 30 or 40 years, there’s a lot of data out there. Well, what happened to this river bed when that flash flood came through so we can go out and in fact we do at one concern deploy people right after disasters to go in and capture a imagery and hyperlocal data to say those buildings behave the way our solution predicted, and other models predicted, did the natural environment behave the way that it was predicted that it would, when water float across it.

And then you apply machine learning that teaches the computer right to learn and think more smarter, more smartly in the future. You bring all of this together and that’s why and how we’re able to provide that hyperlocal highly accurate output. So we say it’s just a map. Well, certainly it’s presented in a map like form and there’s other components to it and be happy to walk anybody through our solution anytime, of course, because that’s what I do, but what you’re getting right now in the jurisdictions where we are deployed in our seismic solution for earthquake is what’s deployed right now in several jurisdictions, so right now in the cities where we’re deployed, if the ground shakes without any human intervention whatsoever, within 30 minutes, the map will turn on in their EOC self populate and at greater than 80 percent accuracy, it will display at the sub block level, the level of damage to the buildings, so walking into that EOC, what that emergency operations manager is able to do, right, and then all and they’re all their stakeholders is immediately have a highly accurate hyperlocal shared situational awareness is what’s going on in my operating environment.

Now what happens next is you’re going to get information. You’re going to be using drones. We’re using street cams. Were using a. you’re going to get killed reports, radio reports from firetrucks, will patrol cars just calling in and saying, no, the Brunel household is collapsed, right? Or this a tenement building. It’s not collapsed. What would the EOC operator can then do is going and it’s a very simple user interface type in and say one, two, three main street. That actually is a collapse where machine learning kicks it. It takes that enriched data and it recalculates the entire built environment, but it doesn’t do that blindly. It’s reconsidering those thousands of data elements that it did to generate the first map and applying it across the entire built environment, so with a couple of dozen data elements added over the next, whether it takes you 20 minutes to get that reliable valid data from the field or a couple of hours, you’re moving your accuracy into that upper 80 and lower 90 percent.

I’ve worked a lot of major disasters. I’ve had the opportunity to work with incredible teams in New York in particular, but I’ve also been deployed around the country a little bit. The biggest challenge, one of the biggest challenges we have right after something untoward happens, even if it’s a notice event like a hurricane, is trying to figure out how bad is bad, what’s going on. So I knew we had tens of thousands of homes touched by the ocean after Hurricane Sandy. This wasn’t Katrina. The water didn’t come in and stay, so I know this was. The water came in and left. How bad was that damage where the homes shifted off their foundation to the water, sit on it for six hours or six days. Could families occupy those homes? It took weeks of finally getting building inspectors out on the ground to do it. Point by point, data inspection, a home inspection and building inspection to figure out exactly what we’re livable structures and what shouldn’t be. With a solution like this, you’re able to achieve that in many cases in a couple of hours.

Todd DeVoe:      That’s amazing right there. I mean that’s gonna. That’s gonna make a huge difference in getting the proper damage assessment up to the local level to the county for the county to the state. And the state to the federal government to really start having resources coming in and a in a much timely manner.

Greg Brunelle:    It really is. It’s not a criticism of any of the solutions we use now in emergency management because those are the solutions we have available to us. That’s the tech we’ve had available to us, but when you look at, again, not to be Glib, but the spray gun out or map for instance, that it paints scenario, read for earthquake damage or blue for water exposure. It’s not doing hydrological and hydrodynamic coupling to really say, well, what’s it doing to the built environment? Not considering how the flow of this water. Maybe changing those rivers and two rivers become one in real time so you understand it and then validating with dynamic data and so it just doesn’t give us that capability right away. And when we want to respond, when our obligation as public safety leaders is to respond with the best tools that we can as fast as we can to save lives.

When the public expectation is that we’re using most contemporary solutions to come in and save lives and then alleviate suffering, right? That’s. That’s our goal too, is to save those lives that we can save it, to alleviate suffering. Suffering here defined as the immediate who needs a place to stay hot meal, who needs medical care to the suffering that comes a week later when you’re still out of your home or six months later. The. There were many moments after Sandy to use that example again, that that were heart wrenching for me, but it was probably three months after Sandy had been living in this hotel on long island and I came downstairs and there was a group of dads and moms with their elementary school aged kids standing in the lobby of the hotel and the local school districts had come out with a bus schedule because this was their home now and these parents were figuring out how the bus was going to pick up their kids everyday at school and it was really heart wrenching for me to to see how those families had been transformed.

Those lives had been transformed by this now our solution, because it does run predictive analysis, jurisdiction, consumer can run simulations as much as they want and see highly accurately, hyperlocal, what’s going to happen the next time I get four inches of rain or 12 inches of rain or whatever amount you want to do, what’s going to happen when I have these earthquakes happens and they can run hundreds and hundreds of these solutions and see the repetitive loss and then we’ve engineered into the solution the ability to point and click and make mitigation mitigative changes so you can point and click on a neighborhood in say I want to retrofit these houses to earthquake standards and then run the simulation again and it calculates the cost benefit analysis for you so you can see how you’re buying down your lats. What if I put a berm over here or a subterranean water management solution over there? How does that buy down my impacts against my critical infrastructure when neighborhoods, because the best time obviously to minimize those impacts is on those days when it’s sunny and 72 hours.

Todd DeVoe:      Right? And you know, I mean, on a side note too, I mean obviously the United States right now is putting a lot of money into mitigation and, and to be able to have a proper plan to be able to spend money wisely. I come from the school, a fiscal conservative guy who says if I’m going to spend the taxpayer’s dollar, I want to be able to justify that to them. I’m 100 percent. I don’t want to be spending money just because. And I think a tool like this allows us to have a better sense and where we’re going to spend money in a proper way to make sure that our taxpayers’ dollars go the furthest. Do you agree with that or am I off base?

Greg Brunelle:    No, I think you’re 100 percent correct. And I think that there’s, you know, most people in our industry are doing a really good job of trying to achieve that goal. But we’re limited because what we do typically now is four, oh, four, four, six hazard mitigation money. And for Fema, we asked are some jurisdictions have worth the state level or the county level, but towns and villages and cities and what are the mitigation projects you want to do? First of all, it’s very expensive to identify mitigation projects. Yeah, so the limited dollars you have are going to figuring out what you should do. Well, with our tool you can get about 80 percent of the way they’re figuring out what you should do and what at least what solutions have the greatest return on investment or ROI probabilistic. Why to minimize or eliminate the risk to your citizens.

So right there you’re saving dollars. The other neat thing that we’re able to do is we’re able to show those mitigation efforts are coordinated. The impacts will have across the entire natural environment. So after Sandy, after Irene and Lee as well, you know, Governor Cuomo did a phenomenal job with a project called New York rising and it was a bringing in community development block grant, disaster recovery dollars, which is a relatively new thing in the disaster space for it. We’re, we’re seeing that a lot of by Congress after disasters now, it’s been around for awhile, but we’re using it for resilience focus, longterm recovery new jurisdictions, and it gives. The nice thing about those dollars is it gives a lot of freedom of action to the elected leaders into emergency managers. It’s not just rebuild it and rebuild the wastewater treatment facility a little bit stronger.

It’s what do you want to do to support your community and mitigate. Right? So with those dollars , you know, we have 122 communities in New York state that we were doing mitigative projects, mitigation projects, but it wasn’t considering, you know, how does the mitigation project in this town affect the natural disaster in the town next door, right? Where the solution now like this, you can look across and say, Hey, you could, you know, if you, if you fix the shoreline here, you exacerbate or eliminate problems in the next two towns as well. So you can consider across the built environment. Again, it’s just this nexus of computing and data power and you know, the brilliance of some of the people working behind it have committed their lives knowing their careers to creating proprietary, uh, artificial intelligence and machine learning algorithms that are focused on this.

Todd DeVoe:      Yeah, I know growing up in upstate New York and on the Hudson River, you know, every year we always had those floods coming out and you know, when you’re, the Henry Hudson Park was going to flood and we knew that those areas down there, we’re definitely gonna flood, you know, and, but we never knew how bad, you know, Albany had some serious flooding going on because of the ice and melting. And this is kind of cool that this would be able to predict that and to be able to mitigate those issues prior to, in saving, those hundreds of thousands of dollars in the, in the recovery costs. This is an amazing piece of product that is created. If you guys have not seen it, really go over to the one concern, website, check it out. There’s some demo videos that you can find that really cool to look at. How do you see getting this product into the EOC, how, how does it, how’s it gonna work for

Greg Brunelle:    You know, the capability that we’re bringing in and I want it back up in a second to the difference between AI based software solutions versus what we’re all familiar with, which is, you know, self portrait of last 20 years. So what we’re doing is we’re working with early adopters of the solution right now to validate the solution which are models have been validated and we validate for every flood, for every fire. Earthquake validated with over well over 200 earthquakes around the globe now, dozens of floods. So we look for early adopters, particularly innovative emergency management programs who are looking to partner with us to identify opportunities to improve the solution as well. Historically with a SAS, right? A software as a solution, what you’re getting there, you’re getting a prepackaged solution. So somewhat, you know, is a kind of equip. I say, you know, for the last 20 years we’ve had software salesman walking in the door saying, you know, here’s, here’s what we can offer you.

A lot of it’s good stuff, but it’s just older technology now. It’s older technology at the time, well cutting edge, a lot of it’s xl spreadsheet based and if we needed a software to achieve a mission, like an incident management software solution for our EOCs you know we do an RFP, we pick the best of the three, typically the least expensive of the three adopt it and then we’d jam our solutions, our operations to fit into that solutions capabilities, right? Contemporary Computing Power, contemporary software solutions, not just at one concern but elsewhere. When you’re talking about user interface like that, customization should be pretty simple. You know that it should not cost, nor should it not be a challenge for jurisdiction. To have a user interface that’s really meets your needs. That is, you know, it should be really intuitive if you and I can download an APP with a game we’ve never played right now in 30 seconds on our phones and literally two minutes later.

I understand how to play that. The things that we’re doing, you know, whether it’s shared situational awareness, mission assignments, logistics management, those are the things that should be pretty intuitive user interface as well. The other thing too is artificial intelligence and machine learning based solutions are really looking to say to you, what’s the challenge you’re trying to. You’re trying to solve, right? What’s the question you need answer. That’s what AI and ml does is that answer’s complex questions, so what AI can do is any decision that a human makes that takes us a series of decisions that are less than a second ultimately come to that answer. Ai Can typically automate that. Now I say that that gives people a moment of pause because they’re like, oh no, use robots in the EOCs. No, not at all. What we’re talking about is identifying what are the complex questions that an executive has to make an EOC quickly that rely on disparate data and information streams that can be brought together and then through the power of machine learning gives you a highly accurate predictive outcome. So you can say, okay, I do need 14 shelters open and these are the locations where it’s most likely that I’m going to have a safe buildings to open the shoulders.

I want to teach my classes. I tell my students that if you have 80 percent of the information, that’s a good. That’s a lot of information to make a decision, you know, and it seems like we’re getting closer to a, to having way more information than we’re making decisions on, on now with, with using a product such as a One Concern. That is phenomenal right there. That’s a paradigm shift in how we do business, isn’t it?

Greg Brunelle:    It absolutely is. And what we need to work with the emergency management community, and this is something like Mr Fugate and I and others are working on is what are those key questions that an executive and EOC manager, a lead operator incident commander needs to have answered quickly that the data information is out there that we can pull in very quickly to inform that decision faster so that we’re not spending all day after a no notice in particular trying to figure out how bad is bad, why would we do right now? And then how can I share that across all of my stakeholders, the level of community to achieve unity of effort as quickly as possible. And I’ve fortunately no, we’re talking a lot about what we’re doing today, right? You know, silicon valley and artificial intelligence and machine learning as you can imagine.

There’s what we can do today. And then I’ve gotten to of course, peek behind the curtain and see what we’re going to be able to do and two years in, five years and beyond. And it’s really incredible. The power, you know this. We’re on the verge of five g in this country that will start rolling out and so select cities later this year, early next year, but within two or three years we’ll all have five g on our phones. That’s really going to kick off the Internet of things. There’s going to be an enormous amount of censoring that and information out there that is going to require much less of a Wifi pipe, if you will. Right. To get information and that’s gonna inform and give us a much more immersive in realistic understanding of our operating environment and various Ios sees in realtime. So adopting technology like this really allows us to then inform it better later. So that makes sense.

Todd DeVoe:      Oh yeah, for sure. It really does a, I mean, I think I like technology. I think it’s great and I always thought about my daughter who’s, she’s just, she’s just getting into kindergarten and when she was three, she already knew how to use an iphone, an ipad. She knows how to log on and find the things that she wanted to do and do the games, you know. So I think the generations coming up behind us and this is intuitive for them using technology, understand how to use it. I mean, you know, using Google maps for instance, you know, when I, when I first started out as working in the field as a medic, you know, we had to use a Thomas Guide to get everywhere we needed to go, you know, and then now you have gps and it’s got to tell you left, right, right.

Left, right. And you’re in the fastest route and around traffic, you know. So, you know, as we see technology moving forward, even in the field, I can’t imagine how, how great it can be moving forward in the EOC, especially with this predictive technology that’s there. I mean right now we’re relying upon a GIS to get us, you know, damage assessment and it’s really clumsy, you know, and so we’re always predicting more damage in the area that are maybe really is and we have to go and readjust it and becomes a problem later on. But that’s what it is. But the GIS doesn’t give us a predictive movement of that, of that disaster, such as a fire or flood.

One Concern, AI & EMGreg Brunelle:    GIS is great. I mean spatial tools are fantastic and I think, I know me personally, right? And I think many of us emergency management, we sort of late to the game with GIS. We had GIS experts and specialist center or like I’m not just a map, I couldn’t do more than, you know, and, and never really took full advantage and you know, now I think more and more people are spatial representation of what’s going on is critically important. It’s now applying that AI and ml back into it so that it’s dynamically updating. So you’re pulling in those different in data and information streams and it’s reducing the human level of effort in order to get that information in. So we’re not manually, oh, they’ve got a data set over here. I need somebody who’s got to type it in and I appreciate we, you know, people use apis or what have you to bring an information set that up ahead of time.

But we’re on cusp as emergency managers as an industry of having such innovative and immersive information in front of us. So the, you know, the example I use because I teach a lot on AI and ML for public safety, sort of agnostic concerns. What is it, what does it mean? What’s the future look like? And a couple of the examples I use, and you probably know this, some people may not remember the 1982 movie war games.

Todd DeVoe:      Oh yeah.

Greg Brunelle:    So you know, when, when the, the true stories, when northcom norad rather, excuse me, norad went and saw war games. They came out of them, they said hey, we don’t have a wall of screens like that. We need that. And we spent a and then you know, so they did that. But we in emergency management and spent a lot of time building walls with screens. Right.

And, and that’s good. That’s helpful. It ensures a level of shared situational awareness around the all of the stakeholders in the EOC in the last 10 years or so in particular, it’s a lot of you should be. Oh, you any the emergency management committee, you should be. Should be looking at these traffic camps you should be looking at these police gives you should be, and let’s back up even further. You should be watching local news now used to be watching all the national news and the weather channel and you should now be displaying now the Internet’s here. You should be displaying the weather maps up there. Now it’s getting tougher for us. You should be looking at youtube and facebook and twitter and all of the other sort of periscope, all the other social media. You should be. You should. Now we’re adding drones. Now.

The human brain can only absorb so much information at once. I mean there’s literally a limit on what we can bring in, consume and then make an output. Now we take pride in our industry that we make very difficult decisions with less than perfect information in highly stressful, less than ideal conditions. That’s if you’re not cut out to do that. This isn’t the industry for you and that is a genuine source of pride and a deserved source of pride for emergency managers. That said, the amount of information and the expectations from our elected leaders, from our public that we are capturing all of that information and we’re consuming it is a 100 percent right. It’s like up there, they’re just expecting it. We, I’ll try to be agnostic about this and just say I chased a lot of silly tweets in my disaster response days.

They were unfounded just because somebody said, oh, somebody is tweeting about this. It’s like, right, but we have no other validation of that, but we better just go and put manpower behind investigating it’s reality, so we’re getting overwhelmed. Overwhelmed at our EOCs, so our EOCs now look like the war games room with all these big giant screens and all this information. There’s really cool stuff that companies are doing now with interactive dashboards and that’s what I call the minority report screen, right? That’s the gloves on and he touches it, moves information around. That’s awesome. Still a lot of information we’re moving towards with the application of Ai and ml is Tony Stark’s lab, that immersive 3D environment because once we bring in Vr at some point virtual reality, excuse me, you know you’re really immersed in real time and there is secondary and tertiary analysis going on.

One of the cool things we’re doing with a couple of our jurisdictions right now is critical infrastructure interdependency, predictive analysis. If you lose x, then y happens. Now. Emergency managers of course know first order effects. Hey, if I lose that substation is it goes underwater. I’m going to lose that hospital in that school and I know my jurisdiction and that’s going to be a loss of a lot of capability or a capability. Right? But we know that there are a tertiary and beyond order effects that now we can map and AI and ML can help say, by the way, if you don’t fix x, then that fifth or seventh order effect is going to kick in and become a problem on day three and here’s what else it touches and flag that for you. Those are a few things. Doesn’t allow us to miss things because we’re so focused on the now or the next two hours of now that we’re not thinking three days out. I personally, I think we’ve all experienced that. It also helps us with others make the case for here’s why this prioritization of Mr. mission assignment is key because this is how this ties into that. And then when we pre disaster, get into mitigation, we can show harden this thing over here because it touches all of these other things. That makes sense.

Todd DeVoe:      Going back to what you’re saying regarding what the public expects and part of it is that they’ve all played with things that can be helpful. Such as like, you know, my son, he has those AI goggles, right? And you’re interacted with movies and things like this and there’s, there’s applications that are there that, that he can see and then, you know, so we go, hey, why? Why can’t we do this with drones to see what’s going on in the world? You know, you know, we used to have to rely upon, like you said, the local news and, and uh, now we have the fire stick or the apple tv where we could plug it in and not have to worry about local news and just see footage from people that are out there doing there thing, you know.

So you’re right there in the public expects things. We’re just talking about. We had a fire here locally in my jurisdiction right where I work. And the residence were asking why didn’t we have better fire maps, you know, and we had good maps, you know, go going back to that, you know, but they wanted to know why we didn’t have better ones because they’ve seen on the movies where they can, where they can manipulate them and predict where they’re moving and stuff like this. And we have to say, well we’re not there yet, but maybe we are there. We may be, are there with, with One Concern.

Greg Brunelle:    We’re always going to be a few years behind the, behind the movies. Right? So that’s the art of the possible. And then it takes a fierce practically apply and develop and apply it. And also, you know, government to be honest, you know, we, we tend not to be early adopters of technology buying a fleet of cars for your, for your police department. You’re not preordering Tesla 3s, you know, you’re buying Crown Vics because they’re there, they’re tried, they’re tested, they’re on somebody’s backdrop contract and they’re, they’re reliable. Right? T hat’s a good thing because in government, one of our, you know, one of our key responsibilities is to be a good steward of the people’s money, but at the same time we have to be innovative with people’s money and we have to identify where is the most bang for my buck, where just my greatest return on investment. And to your point, I think we as a society, we as a species are getting, oh, it’s technology. It’s not scary. It’s not confusing. I may not understand how it works, but you know, I’ve been using this thing in my hand for five years, 10 years now. So I get it that it’s okay. You know, that that emerging, confusing technology is, is, is okay and reliable and, and we’re learning this together, so yeah, that is the hope is that we can become more rapid adopters of emerging technology.

Todd DeVoe:      So if somebody wanted to get ahold of you to learn about what you guys are doing over there at One Concern, how could they find you?

Greg Brunelle:    You know, I’d love to chat with anybody the any point and they can email me at or they can call my cell anytime. 518-944-5920. And I’m sure you’ll make that available through your website. That’s 518-944-5920. And also the www. website. It’s really important to us as a team here. It’s critically important to our founder group and our development group, that we are interacting regularly and actively with the emergency management, public safety community, that that’s the difference. We know building this ship with them while we’re all selling together, not coming up with a solution and saying, here’s the finished product, here’s what we’re going to do. It’s what are the challenges we have today, what are the challenges we’re going to have tomorrow?

We have never been before so much an interdependent society. We have every aspect of what we do and in the last 10 years, 13, 14 years now in emergency management oriented, independent because we go to each other’s disasters. We learned from each other. We go to conferences together. You know, I left government after many years in government, five years ago I ran an emergency management practice for the large engineering firm and came to one concern a couple of years ago and I’ve had the opportunity now to travel around the country, hands on working some disasters, conferences, doing small projects, complex projects, the counties and cities and states across the country. You know, we’re a family and emergency management. It’s not that big of a family to be honest. Yeah. Will absolutely. There are hundreds of us who do this, but we know each other. We see the same faces, we see the stories.

We don’t Monday morning quarterback each other, you know, I wasn’t there, I didn’t make that decision. We want to learn from each other. Tomorrow it’s going to be me and I’m gonna want you and my EOC helping me out and I want you in my, you know, we understand together that the citizens of this country, individuals, family, children, regardless of what is going on in any other aspect of American society right now, nothing pulls us together more so than a disaster and I have never in my life to experienced whether I was at a single car, motor vehicle accident, a house fire 15 years ago for some of the largest, most complex disasters in this country’s history. I’ve never experienced the camaraderie, the familiarity and the love and support that comes when you’re standing shoulder to shoulder with your brother and sister, emergency managers. I know that that community is there.

I believe in the vision of resilience than Ahmed and this team is bringing and I know that together we can truly build a resilient world moving forward.

Todd DeVoe:      Okay, so I’ve got the toughest question of the day for you. What book or books would you give to somebody who’s interested in this topic?

Greg Brunelle:    So the very first book that I read on this was Artificial Intelligence and Machine Learning For The Absolute Beginner, and I highly recommend it because I cannot think of the author’s name, so forgive me. but I downloaded it on my kindle. I read it on a flight, I use it as a little bit of a Bible right now to align myself with terminology and concepts. That’s a, that’s regardless of whether it’s an emergency management or any other industry, you just learning about AI and ML which is going to define many industries for us.

That’s a great book. I just finished The Big One, you know, and I’m forgetting the doctor’s name. Who wrote that?

Todd DeVoe:      Lucy Jones.

Greg Brunelle:    Yeah, absolutely. Great Speaker. Just read her book. I didn’t know about the central valley flood back in the 18 hundreds. Absolutely fascinating. I’m headed to Sacramento to take the tour of the subterranean sellers that are still there. So those are two books that I recommend and then Judith Rodin’s book on resilience and Achieving Global Resilience is another one that I highly recommend.

Todd DeVoe:      Is there anything you’d like to say to the EM before we let you go?

Greg Brunelle:    I just want to thank everybody for work that they’re doing out there. I know that, again, thankless job, you know, nobody needs us until they need us and then they really need us. I’m so encouraged by the increased use of mutual aid around this country. I think one of the great ways we build local capacity is by using each other during disaste\rs, by bringing other emergency managers into our EOCs even just for a few days even to answer the phone, whatever it takes, but it’s working together that we built this industry. So I just want to thank everybody for the work they’re doing.

Todd DeVoe:      Well Greg, thank you so much for spending some time with us today and I really do appreciate it. And maybe we can get you out here again sometime.

Greg Brunelle:    Thanks so much Todd. Appreciate everything. Have a great night.

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4 thoughts on “Artificial Intelligent, The Ultimate Breakthrough Technology”

  1. I am a big fan of Artificial Intelligence and its possibilities in the world of Emergency Management. The potential use of its quick processing power in the EOC to process and display information in real time as well as give estimates on damages during a disaster would be an invaluable tool to the Incident Commander and staff. I truly believe this can be a big game changer in the future if it can be properly integrated!

  2. I am a big fan of Artificial Intelligence and its possibilities in the world of Emergency Management. The potential use of its quick processing power in the EOC to process and display information in real time as well as give estimates on damages during a disaster would be an invaluable tool to the Incident Commander and staff. I truly believe this can be a big game changer in the future if it can be properly integrated!

  3. Hello Todd DeVoe,

    Great Podcast! I’d just like to say how great One Concern is doing, incorporating AI machine learning, into the Emergency Management field. This definitely ranks One Concern on the leading edge of Emergency Management. However, while it’s housed on the aws cloud accessing millions of servers generating mass amounts of computational power… Has One Concern considered using “Quantum Computers” and “their computing power”? Particularly since quantum computing computers i.e “D-Wave” are at the pinnacle of our computing power which exceeds any present day super-computer/s.

  4. Hello!

    This topic was so interesting to me because of my fascination with technology. I have been researching A.I. for many years now and at one point in my life, was learning to code different types of algorithms for different pieces of technology. I think that A.I. could be so effective and useful in the world of emergency and I am glad that you guys are bringing it to light. Thank you for the great listen.


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