1 00:00:03,080 --> 00:00:05,960 Speaker 1: If you had to pick one thing that unites smart 2 00:00:06,000 --> 00:00:09,040 Speaker 1: cities infrastructure, it's the ability to communicate, right is the 3 00:00:09,080 --> 00:00:12,799 Speaker 1: ability to talk to things, things that generate data, and 4 00:00:13,160 --> 00:00:16,120 Speaker 1: ultimately the holy grail is if you can combine those 5 00:00:16,160 --> 00:00:21,120 Speaker 1: things that generate data into informed information with edge computing 6 00:00:21,120 --> 00:00:23,480 Speaker 1: and you can make real time decisions on that data 7 00:00:23,720 --> 00:00:27,240 Speaker 1: and influence the real world. That is where I think 8 00:00:27,280 --> 00:00:31,600 Speaker 1: we all want to be. Welcome to the restless ones. 9 00:00:31,840 --> 00:00:35,040 Speaker 1: I'm Jonathan Strickland. As you may know, I've spent the 10 00:00:35,120 --> 00:00:38,640 Speaker 1: last fifteen years covering technology and learning how it works, 11 00:00:38,960 --> 00:00:44,560 Speaker 1: demystifying everything from massive parallel processing to advanced robotics and 12 00:00:44,840 --> 00:00:49,080 Speaker 1: everything in between. Yet it's the conversations with some of 13 00:00:49,080 --> 00:00:52,280 Speaker 1: the most forward thinking leaders, those at the intersection of 14 00:00:52,320 --> 00:00:58,600 Speaker 1: technology and business that fascinate me the most. I think 15 00:00:58,640 --> 00:01:01,640 Speaker 1: the tech world has a few categories that can be 16 00:01:01,680 --> 00:01:06,360 Speaker 1: confusing to the mainstream. Artificial intelligence and machine learning are 17 00:01:06,400 --> 00:01:09,959 Speaker 1: two notable examples, and I would argue that another is 18 00:01:10,040 --> 00:01:14,959 Speaker 1: the concept of smart cities. What makes a smart city? 19 00:01:15,160 --> 00:01:19,240 Speaker 1: Our guest today, Tyler's Fetech has an answer. Tyler has 20 00:01:19,240 --> 00:01:24,560 Speaker 1: spent his career tackling major challenges through leveraging technology. Early on, 21 00:01:24,760 --> 00:01:27,919 Speaker 1: he worked on projects to improve the air quality in Colorado, 22 00:01:28,160 --> 00:01:31,640 Speaker 1: leading programs that developed markets for alternate fuels and other 23 00:01:31,760 --> 00:01:37,440 Speaker 1: vehicle technologies. He became an energy and transportation administrator in Denver, Colorado, 24 00:01:37,680 --> 00:01:41,839 Speaker 1: where he worked on projects to reduce transportation emissions. Now 25 00:01:41,959 --> 00:01:45,600 Speaker 1: he is working in Colorado Smart Cities Alliance, which aims 26 00:01:45,640 --> 00:01:48,560 Speaker 1: to bring together parties in the public and private sectors 27 00:01:48,760 --> 00:01:52,400 Speaker 1: to create solutions to real world problems. As you'll hear, 28 00:01:52,880 --> 00:01:58,240 Speaker 1: sometimes those solutions involves sophisticated technology, and sometimes they involve 29 00:01:58,280 --> 00:02:05,360 Speaker 1: a charmingly simple approach. First, I want to start off 30 00:02:05,400 --> 00:02:08,640 Speaker 1: Tyler by welcoming you to the Restless Ones. Thank you 31 00:02:08,720 --> 00:02:11,640 Speaker 1: so much for joining us today. Thanks for having me, Jonathan. 32 00:02:11,639 --> 00:02:14,799 Speaker 1: I'm really excited for the conversation. A question I'm always 33 00:02:14,880 --> 00:02:18,880 Speaker 1: curious about is when did you first start getting interested 34 00:02:19,120 --> 00:02:24,080 Speaker 1: in technology in general? So, I I really got interested 35 00:02:24,120 --> 00:02:26,600 Speaker 1: in technology when I was thinking about what I wanted 36 00:02:26,639 --> 00:02:28,519 Speaker 1: to do with my life. As I was graduating in 37 00:02:28,560 --> 00:02:31,160 Speaker 1: high school. I went to school for environmental studies and 38 00:02:31,200 --> 00:02:34,280 Speaker 1: political science and had a passion back in two thou 39 00:02:34,480 --> 00:02:36,320 Speaker 1: eight for trying to figure out how we were gonna 40 00:02:36,360 --> 00:02:39,800 Speaker 1: tackle this climate challenge. And I was also really interested 41 00:02:39,800 --> 00:02:43,480 Speaker 1: in cars at the time. My uncle's my dad all 42 00:02:44,200 --> 00:02:47,280 Speaker 1: big mechanics and have nice vehicles, and I have kind 43 00:02:47,280 --> 00:02:50,080 Speaker 1: of a photographic memory, so I can tell like every 44 00:02:50,080 --> 00:02:52,320 Speaker 1: car on the road, like make model, all that kind 45 00:02:52,360 --> 00:02:55,480 Speaker 1: of stuff. So my first job out of school was 46 00:02:55,520 --> 00:02:59,440 Speaker 1: as an intern working on alternative fuel vehicles the ability 47 00:02:59,480 --> 00:03:03,560 Speaker 1: for the electrification of transportation to help reduce emissions, and 48 00:03:03,639 --> 00:03:06,200 Speaker 1: so I got to learn about all of the incredible 49 00:03:06,240 --> 00:03:10,520 Speaker 1: technologies influencing the transportation space, which turns out are also 50 00:03:10,600 --> 00:03:14,360 Speaker 1: influencing pretty much everything in a city. So that's when 51 00:03:14,639 --> 00:03:17,280 Speaker 1: tech became really interesting to me as a tool for 52 00:03:17,360 --> 00:03:21,600 Speaker 1: solving problems. What actually brought you to the Colorado's Smart 53 00:03:21,600 --> 00:03:25,919 Speaker 1: Cities Alliance, So you know, I spent really my whole 54 00:03:25,960 --> 00:03:29,200 Speaker 1: career in this space, fortunately, and the first roles that 55 00:03:29,240 --> 00:03:33,080 Speaker 1: I had were in taking a specific technology and trying 56 00:03:33,120 --> 00:03:35,920 Speaker 1: to apply it to a specific problem. So I worked 57 00:03:36,000 --> 00:03:38,160 Speaker 1: for the City and County of Denver, where I got 58 00:03:38,200 --> 00:03:42,960 Speaker 1: to develop the strategy and and the goals for reducing 59 00:03:43,000 --> 00:03:46,640 Speaker 1: transportation emissions. And that was amazing because I got to 60 00:03:46,680 --> 00:03:51,840 Speaker 1: work with automakers and electric vehicle infrastructure providers to figure 61 00:03:51,880 --> 00:03:54,320 Speaker 1: out how we were going to accomplish these joint goals 62 00:03:54,560 --> 00:03:57,880 Speaker 1: together and then work on actually deploying the technology in 63 00:03:57,880 --> 00:03:59,760 Speaker 1: in the real world, in our city fleet, in our 64 00:03:59,760 --> 00:04:02,560 Speaker 1: city streets, and those sorts of things. And then I 65 00:04:03,000 --> 00:04:06,000 Speaker 1: got a chance to go to the Colorado Department of Transportation, 66 00:04:06,040 --> 00:04:08,960 Speaker 1: where I got to lead and start a program focused 67 00:04:09,000 --> 00:04:13,640 Speaker 1: on using connected and autonomous vehicle technologies to solve transportation 68 00:04:13,680 --> 00:04:17,640 Speaker 1: safety issues across the state. And through both of those roles, 69 00:04:17,640 --> 00:04:19,919 Speaker 1: as well as five years I spent before with the 70 00:04:19,920 --> 00:04:24,840 Speaker 1: Department of Energy, I got to understand that partnership is 71 00:04:24,880 --> 00:04:28,880 Speaker 1: a huge part of deployment of technology. If you have 72 00:04:28,920 --> 00:04:30,600 Speaker 1: the best tool in the world, if you can't get 73 00:04:30,600 --> 00:04:33,440 Speaker 1: it to market, if you don't have a supportive environment, 74 00:04:33,720 --> 00:04:35,400 Speaker 1: if you don't have the partners that you need to 75 00:04:35,480 --> 00:04:39,160 Speaker 1: deploy those things, which turns out more and more government 76 00:04:39,200 --> 00:04:41,680 Speaker 1: is one of those partners that are needed. It's really 77 00:04:41,680 --> 00:04:43,880 Speaker 1: really hard for those tools to see the light of day. 78 00:04:44,000 --> 00:04:46,400 Speaker 1: And so the Colorado Smart Cities Alliance was created to 79 00:04:46,440 --> 00:04:51,880 Speaker 1: try and bake the marketplace for local government innovation. So 80 00:04:51,960 --> 00:04:53,760 Speaker 1: I thought that this was the perfect place for me 81 00:04:53,839 --> 00:04:56,240 Speaker 1: to grow what I had done day to day for 82 00:04:56,279 --> 00:04:59,960 Speaker 1: specific agencies into a nonprofit model that helps lots of 83 00:05:00,040 --> 00:05:03,120 Speaker 1: different governments solve lots of different problems with lots of 84 00:05:03,160 --> 00:05:07,000 Speaker 1: different tools. You have touched on so many things that 85 00:05:07,120 --> 00:05:09,880 Speaker 1: I love to talk about on this podcast, and we'll 86 00:05:09,920 --> 00:05:13,040 Speaker 1: be touching on the more throughout the conversation. One thing 87 00:05:13,080 --> 00:05:17,359 Speaker 1: I definitely wanted to get from you, Tyler, is what 88 00:05:17,560 --> 00:05:20,440 Speaker 1: your definition of a smart city is, because it's a 89 00:05:20,560 --> 00:05:23,440 Speaker 1: term that we see very frequently, and I think a 90 00:05:23,480 --> 00:05:29,320 Speaker 1: lot of people have varying ideas on what that actually means. 91 00:05:30,120 --> 00:05:32,200 Speaker 1: I spend a lot of time talking about this question, 92 00:05:32,680 --> 00:05:35,200 Speaker 1: and I think it's good. I think the industry is 93 00:05:35,240 --> 00:05:40,720 Speaker 1: plagued by the desire to define a smart city. I'm 94 00:05:40,760 --> 00:05:44,200 Speaker 1: actually going to steal a colleague's definition, Emily Royal from 95 00:05:44,200 --> 00:05:46,520 Speaker 1: the City of San Antonio. You know, she said at 96 00:05:46,520 --> 00:05:50,760 Speaker 1: a conference recently that smart cities use emerging tech for good, right, 97 00:05:50,880 --> 00:05:55,120 Speaker 1: and most simplistically, I think that is true. But to 98 00:05:55,240 --> 00:05:58,440 Speaker 1: do that well, we believe and we define smart cities 99 00:05:58,480 --> 00:06:02,880 Speaker 1: as an organization by needing a process for applying that 100 00:06:03,000 --> 00:06:07,599 Speaker 1: technology to solve a specific problem. And that process, we believe, 101 00:06:07,720 --> 00:06:12,240 Speaker 1: usually involves innovation, meaning you have to do something new. 102 00:06:12,800 --> 00:06:16,159 Speaker 1: If you're using technology or data to do the same thing. 103 00:06:16,560 --> 00:06:19,599 Speaker 1: It's not necessarily, in my opinion, that hard to do. 104 00:06:19,680 --> 00:06:22,520 Speaker 1: There's lots of tech that's involved in everything. So taking 105 00:06:22,560 --> 00:06:25,080 Speaker 1: a risk and trying something new, there needs to be 106 00:06:25,120 --> 00:06:27,680 Speaker 1: some sort of technology that is the tool that you 107 00:06:27,720 --> 00:06:30,880 Speaker 1: are approaching that innovation with. And then usually there's some 108 00:06:30,880 --> 00:06:35,279 Speaker 1: sort of data element to informing a decision that hopefully 109 00:06:35,360 --> 00:06:38,479 Speaker 1: is generating an innovative or new results. And so that's 110 00:06:38,520 --> 00:06:42,320 Speaker 1: my best attempt. But I actually I don't feel the 111 00:06:42,400 --> 00:06:45,039 Speaker 1: need to define smart cities. I think the diversity of 112 00:06:45,080 --> 00:06:49,640 Speaker 1: definition is part of the beauty of it. Generally speaking, 113 00:06:49,680 --> 00:06:53,440 Speaker 1: what are some of the benefits that come along with 114 00:06:53,480 --> 00:06:56,600 Speaker 1: this creation of smart cities? What what are some of 115 00:06:56,640 --> 00:06:59,880 Speaker 1: the outcomes that we're hoping to see through this in 116 00:07:00,040 --> 00:07:05,680 Speaker 1: corporation of technology into our cities. So I think that 117 00:07:06,440 --> 00:07:09,159 Speaker 1: there is a misconception that the smartest cities are those 118 00:07:09,240 --> 00:07:11,480 Speaker 1: that are the most connected or that have the most 119 00:07:11,480 --> 00:07:15,040 Speaker 1: technology or the most data. Instead, I think that those 120 00:07:15,040 --> 00:07:18,040 Speaker 1: with the best approaches to solving a problem are the 121 00:07:18,080 --> 00:07:22,000 Speaker 1: smartest cities. It really depends on the problem that the 122 00:07:22,200 --> 00:07:26,080 Speaker 1: city chooses to prioritize. To apply the process to most 123 00:07:26,080 --> 00:07:29,160 Speaker 1: smart cities target issues important to everyday quality of life, 124 00:07:29,280 --> 00:07:34,000 Speaker 1: like transportation safety and efficiency, air quality and climate change, 125 00:07:34,560 --> 00:07:38,760 Speaker 1: public safety, accessibility, digital divide right. Those are all issues 126 00:07:38,800 --> 00:07:42,440 Speaker 1: that technology can help solve. In cities are using technology 127 00:07:42,520 --> 00:07:46,480 Speaker 1: to improve it's really hard to define the exact benefits 128 00:07:46,480 --> 00:07:48,320 Speaker 1: that come from the creation of a smart city until 129 00:07:48,360 --> 00:07:51,200 Speaker 1: you define the problem you're solving. Grand Junction here in 130 00:07:51,240 --> 00:07:54,240 Speaker 1: Colorado on the Western Slope has very different issues than Denver. 131 00:07:54,680 --> 00:07:58,360 Speaker 1: They don't have transportation congestion like Denver does, and so 132 00:07:58,440 --> 00:08:01,280 Speaker 1: it's up to them to prioritize it. When I was 133 00:08:01,360 --> 00:08:04,240 Speaker 1: at the City of Denver, we prioritize two issues we 134 00:08:04,280 --> 00:08:06,560 Speaker 1: knew were important to quality of life in our city, 135 00:08:06,800 --> 00:08:10,840 Speaker 1: public health and transportation safety. And for public health, air 136 00:08:10,920 --> 00:08:14,560 Speaker 1: quality was a huge primary concern. We are entering into 137 00:08:14,560 --> 00:08:17,560 Speaker 1: severe nonattainment for ozone here in the Denver metro region 138 00:08:18,080 --> 00:08:21,440 Speaker 1: and it's actually impacting you know, people of color and 139 00:08:21,840 --> 00:08:26,160 Speaker 1: people who have been inequitably served by infrastructure for a 140 00:08:26,240 --> 00:08:28,480 Speaker 1: very long time. So we decided we wanted to tackle 141 00:08:28,520 --> 00:08:32,559 Speaker 1: that issue. Today, the city has a robust program using 142 00:08:33,000 --> 00:08:36,920 Speaker 1: forty IoT air quality sensors to provide real time hyperlocal 143 00:08:36,920 --> 00:08:39,640 Speaker 1: air pollution information to the public so that they can 144 00:08:39,679 --> 00:08:43,480 Speaker 1: take informed actions on how to protect themselves and also 145 00:08:43,880 --> 00:08:48,199 Speaker 1: advocate for better air quality and different infrastructure. They've also 146 00:08:48,280 --> 00:08:52,200 Speaker 1: deployed on the transportation side technologies that can detect and 147 00:08:52,200 --> 00:08:56,320 Speaker 1: communicate vulnerable road users and intersections and extend traffic light 148 00:08:56,400 --> 00:08:59,000 Speaker 1: timing and real time to allow for people to cross. 149 00:08:59,320 --> 00:09:02,760 Speaker 1: They're also used seeing micromobility data to inform where the 150 00:09:02,800 --> 00:09:07,280 Speaker 1: safest and least safe parts of their infrastructure are in 151 00:09:07,400 --> 00:09:10,840 Speaker 1: order to improve them. And so that's one example how 152 00:09:11,120 --> 00:09:15,480 Speaker 1: the everyday person would benefit from those things. Understanding if 153 00:09:15,480 --> 00:09:18,240 Speaker 1: it's safe to breathe and go for a run, Understanding 154 00:09:18,320 --> 00:09:21,360 Speaker 1: if it's safe across the intersection. Those are very real, 155 00:09:21,400 --> 00:09:24,360 Speaker 1: tangible things that in the case of Denver, they chose 156 00:09:24,400 --> 00:09:27,080 Speaker 1: to prioritize. And speaking of benefits, I also wanted to 157 00:09:27,120 --> 00:09:31,320 Speaker 1: know what the impact of smart city strategies are on 158 00:09:31,480 --> 00:09:37,040 Speaker 1: local economies and businesses. Sure the impact of smart cities 159 00:09:37,160 --> 00:09:41,520 Speaker 1: on local economies and businesses is significant. Right, the technologies 160 00:09:41,520 --> 00:09:45,200 Speaker 1: of today are shaping the infrastructure of tomorrow, and infrastructure 161 00:09:45,240 --> 00:09:49,679 Speaker 1: quality is essential to business and to local economies. You know, 162 00:09:49,720 --> 00:09:54,240 Speaker 1: the technologies themselves have enormous consequences for individual people like 163 00:09:55,080 --> 00:09:58,800 Speaker 1: who has access to the fastest internet, where are electric 164 00:09:58,840 --> 00:10:01,360 Speaker 1: vehicle chargers located, and the cleaner air that they can 165 00:10:01,400 --> 00:10:04,880 Speaker 1: provide to the local community, Where do people have convenient, 166 00:10:04,880 --> 00:10:09,000 Speaker 1: affordable access the transportation. Those are all very real things 167 00:10:09,000 --> 00:10:13,400 Speaker 1: that technologies are influencing where those will be available tomorrow, 168 00:10:13,559 --> 00:10:16,600 Speaker 1: and those technologies are also driving economic growth, right And 169 00:10:16,640 --> 00:10:19,320 Speaker 1: many of the biggest tech companies that I'm sure you've 170 00:10:19,320 --> 00:10:23,080 Speaker 1: had on this podcast are heavily dependent on access to 171 00:10:23,160 --> 00:10:26,880 Speaker 1: government in some way. Five G providers need to identify 172 00:10:26,920 --> 00:10:31,439 Speaker 1: their infrastructure. Micromobility companies need access to safely ride in 173 00:10:31,480 --> 00:10:35,360 Speaker 1: the city, right of way, right share companies need access 174 00:10:35,400 --> 00:10:38,559 Speaker 1: to streets and curb space, and you know, electric vehicle 175 00:10:38,600 --> 00:10:41,800 Speaker 1: companies need adequate connection to the electricity grid and charging areas. 176 00:10:41,880 --> 00:10:45,560 Speaker 1: And so this impact trickles all the way down the 177 00:10:45,559 --> 00:10:48,880 Speaker 1: supply chain. Makers of chips have a huge interest in 178 00:10:48,920 --> 00:10:52,280 Speaker 1: smart cities because the products they make are going to 179 00:10:52,320 --> 00:10:55,080 Speaker 1: go into the products that are operated on five G 180 00:10:55,280 --> 00:10:58,560 Speaker 1: and go into cars. And so I don't think governments 181 00:10:58,640 --> 00:11:03,920 Speaker 1: understand the role that they have to play in seeding 182 00:11:04,320 --> 00:11:08,839 Speaker 1: the future of economic growth and infrastructure just by having 183 00:11:08,880 --> 00:11:12,559 Speaker 1: an opportunity to partner and test and be good partners, 184 00:11:13,040 --> 00:11:15,600 Speaker 1: because if they aren't, it's going to happen to them, 185 00:11:15,760 --> 00:11:17,840 Speaker 1: and if they are, they have a chance to influence 186 00:11:18,080 --> 00:11:22,439 Speaker 1: what tomorrow's infrastructure looks like. And one of the technologies 187 00:11:22,480 --> 00:11:24,840 Speaker 1: you just mentioned, obviously one of the ones that we 188 00:11:24,920 --> 00:11:28,120 Speaker 1: are really excited about on this podcast, the five G 189 00:11:28,520 --> 00:11:33,560 Speaker 1: connectivity technology. I foresee that as being a pretty key 190 00:11:33,600 --> 00:11:37,080 Speaker 1: component to a lot of smart city strategies moving forward. 191 00:11:37,640 --> 00:11:42,720 Speaker 1: The ability to have fiber connectivity but not be tethered 192 00:11:42,760 --> 00:11:46,640 Speaker 1: to fiber, and to have high band with low latency 193 00:11:47,000 --> 00:11:50,240 Speaker 1: that can enable so many other different technologies. Do you 194 00:11:50,280 --> 00:11:52,240 Speaker 1: see five G as being one of those sort of 195 00:11:52,280 --> 00:11:57,240 Speaker 1: foundational technologies for for smart city strategies moving forward? I 196 00:11:57,240 --> 00:12:00,360 Speaker 1: think it absolutely could be if there was a bust 197 00:12:00,520 --> 00:12:04,360 Speaker 1: an equitable displacement of a true five G network that 198 00:12:04,480 --> 00:12:09,000 Speaker 1: has low, mid, high spectrum, edge computing, you know, all 199 00:12:09,040 --> 00:12:12,480 Speaker 1: of the things that it takes to actually enable the latency, 200 00:12:13,040 --> 00:12:17,920 Speaker 1: the densification of infrastructure that can be enabled. Yes, that 201 00:12:17,960 --> 00:12:22,600 Speaker 1: would be transformative. Right We are in the process of 202 00:12:22,800 --> 00:12:26,600 Speaker 1: trying to launch our own five G network downtown that 203 00:12:26,640 --> 00:12:29,679 Speaker 1: would be a private, fully built out five G network 204 00:12:30,120 --> 00:12:32,800 Speaker 1: for the testing and development of new products and the 205 00:12:32,840 --> 00:12:35,640 Speaker 1: support of startup companies, so that we could give access 206 00:12:35,679 --> 00:12:38,520 Speaker 1: to what that actual five G network will be five 207 00:12:38,559 --> 00:12:41,040 Speaker 1: ten years from now and give cities access to it 208 00:12:41,080 --> 00:12:44,240 Speaker 1: as well to understand the benefits, so that the fiber 209 00:12:44,280 --> 00:12:49,000 Speaker 1: investment cities are making today are informed by you know, well, 210 00:12:49,040 --> 00:12:52,200 Speaker 1: maybe you won't need fiber five ten years from now. 211 00:12:53,240 --> 00:12:57,160 Speaker 1: I assume then that connectivity in general obviously becomes like 212 00:12:57,280 --> 00:13:02,000 Speaker 1: the the glue that holds together these various technologies to 213 00:13:02,360 --> 00:13:06,080 Speaker 1: enable the solutions that we expect for these cities of 214 00:13:06,080 --> 00:13:09,679 Speaker 1: the future. Absolutely. Yeah. I mean, if you had to 215 00:13:09,720 --> 00:13:13,199 Speaker 1: pick one thing that unites smart cities infrastructure, it's the 216 00:13:13,240 --> 00:13:16,319 Speaker 1: ability to communicate, right is the ability to talk to things, 217 00:13:17,080 --> 00:13:20,920 Speaker 1: things that generate data, and ultimately the holy grail is 218 00:13:20,960 --> 00:13:24,880 Speaker 1: if you can combine those things that generate data into 219 00:13:24,920 --> 00:13:27,960 Speaker 1: informed information with edge computing and you can make real 220 00:13:27,960 --> 00:13:31,480 Speaker 1: time decisions on that data and influence the real world. 221 00:13:32,520 --> 00:13:34,360 Speaker 1: That is where I think we all want to be. 222 00:13:38,640 --> 00:13:41,360 Speaker 1: Conventional thinking says you have to pay more to get 223 00:13:41,360 --> 00:13:44,160 Speaker 1: more I want the world, But Team Obile for Business 224 00:13:44,280 --> 00:13:47,880 Speaker 1: uses unconventional thinking to deliver premium benefits for better r 225 00:13:47,920 --> 00:13:51,439 Speaker 1: o I from customized five G solutions to three sixties support. 226 00:13:51,679 --> 00:13:54,520 Speaker 1: We help you reach your business goals right now. I 227 00:13:54,679 --> 00:13:58,599 Speaker 1: want it now, innovating to improve business today and tomorrow. 228 00:13:58,960 --> 00:14:02,400 Speaker 1: That's unconventioned of thinking from T Mobile for business capable 229 00:14:02,400 --> 00:14:04,400 Speaker 1: device required covers not available in some areas. Some US 230 00:14:04,640 --> 00:14:12,800 Speaker 1: require certain planter features C mobile dot com. One of 231 00:14:12,800 --> 00:14:14,640 Speaker 1: the things I really wanted to talk to you about 232 00:14:14,960 --> 00:14:20,240 Speaker 1: was automated vehicles. So I'm curious to hear from you. One, 233 00:14:21,040 --> 00:14:25,040 Speaker 1: what's kind of the state of affairs on automated vehicles? 234 00:14:25,680 --> 00:14:28,600 Speaker 1: Where do you kind of assess where we are on 235 00:14:28,640 --> 00:14:33,880 Speaker 1: that scale? And Two? What are your thoughts about how 236 00:14:33,920 --> 00:14:36,960 Speaker 1: automated vehicles are going to play a role in our lives. 237 00:14:37,040 --> 00:14:38,720 Speaker 1: Do you think that that's going to be more of 238 00:14:38,760 --> 00:14:42,320 Speaker 1: a sort of a public transit kind of mode and 239 00:14:42,480 --> 00:14:46,560 Speaker 1: less of a privately owned vehicle. I certainly hoped that 240 00:14:47,640 --> 00:14:53,119 Speaker 1: automation comes to public transit before it comes to individual garages. 241 00:14:53,880 --> 00:14:56,720 Speaker 1: The industry talks about safety as as the main benefit 242 00:14:56,760 --> 00:15:00,800 Speaker 1: of autonomy, maybe efficiency. There are patent benefits there, but 243 00:15:00,880 --> 00:15:03,200 Speaker 1: in my opinion, one of the biggest benefits to automation 244 00:15:03,240 --> 00:15:05,360 Speaker 1: of public transit is the ability to lower the cost 245 00:15:05,400 --> 00:15:08,960 Speaker 1: of transportation and to provide it to more people, and 246 00:15:09,040 --> 00:15:11,520 Speaker 1: to do so in a shared way, because we can't 247 00:15:11,560 --> 00:15:15,640 Speaker 1: provide more transportation to more people on the same infrastructure 248 00:15:15,720 --> 00:15:18,680 Speaker 1: if we don't do it more efficiently. The only way 249 00:15:18,680 --> 00:15:22,280 Speaker 1: to do that is to connect to an existing transportation 250 00:15:22,400 --> 00:15:26,640 Speaker 1: system that moves people and goods more efficiently. The individual vehicles. 251 00:15:27,120 --> 00:15:29,480 Speaker 1: The leaders in the autonomous vehicle space are really in 252 00:15:29,800 --> 00:15:32,800 Speaker 1: two areas right now. One is in trucking, and that 253 00:15:33,000 --> 00:15:36,640 Speaker 1: is probably the first place that people will really interact 254 00:15:36,760 --> 00:15:40,920 Speaker 1: with highly automated vehicles. They may not even know it. 255 00:15:41,240 --> 00:15:43,560 Speaker 1: The truck next to them, you know, is likely driving 256 00:15:43,600 --> 00:15:45,520 Speaker 1: itself for at least parts of the route or maybe 257 00:15:45,560 --> 00:15:51,520 Speaker 1: even entire sections. And then robotaxis that model eventually, if 258 00:15:51,520 --> 00:15:55,680 Speaker 1: it's profitable. Public transportation is definitely something that they talk 259 00:15:55,760 --> 00:15:58,520 Speaker 1: about wanting to solve. But I see a lot of 260 00:15:58,520 --> 00:16:02,800 Speaker 1: individual people hiring their individual vehicle to come and pick 261 00:16:02,840 --> 00:16:05,200 Speaker 1: them up and going to wherever they want. And in 262 00:16:05,200 --> 00:16:07,880 Speaker 1: that case, you're not moving to people, you're moving one person. 263 00:16:08,280 --> 00:16:10,160 Speaker 1: And in a lot of cases you're gonna have vehicles 264 00:16:10,200 --> 00:16:13,600 Speaker 1: driving around that have zero occupants in them at all. 265 00:16:14,120 --> 00:16:17,280 Speaker 1: And so then what is the point of infrastructure to 266 00:16:17,280 --> 00:16:20,080 Speaker 1: to move vehicles and not people? And so a lot 267 00:16:20,120 --> 00:16:21,880 Speaker 1: of the work we've been doing is trying to solve 268 00:16:22,480 --> 00:16:27,960 Speaker 1: the barriers to using today's highly automated vehicles in a 269 00:16:27,960 --> 00:16:31,920 Speaker 1: transit or micro transit environment. When you're looking at these 270 00:16:31,920 --> 00:16:35,520 Speaker 1: solutions and you're trying to get buy in from various 271 00:16:35,880 --> 00:16:39,560 Speaker 1: parties to look at possibilities of how you can use 272 00:16:39,600 --> 00:16:44,160 Speaker 1: these technologies to do things like support public transportation, what 273 00:16:44,240 --> 00:16:47,240 Speaker 1: are those conversations, like, I mean, are they remarkably different 274 00:16:47,280 --> 00:16:50,320 Speaker 1: when you're talking to say, the private sector versus a 275 00:16:50,440 --> 00:16:56,320 Speaker 1: city government agency. Absolutely, those conversations are always different. To 276 00:16:56,400 --> 00:16:59,920 Speaker 1: do it right, to understand the problem and to find 277 00:17:00,080 --> 00:17:04,040 Speaker 1: a way to co develop the solution takes time, It 278 00:17:04,119 --> 00:17:08,480 Speaker 1: takes investment of resources, and it's not easy, and both 279 00:17:08,520 --> 00:17:10,600 Speaker 1: the public and the private sector are not used to 280 00:17:10,680 --> 00:17:13,679 Speaker 1: doing those things together. What we're trying to do is 281 00:17:13,760 --> 00:17:16,520 Speaker 1: create more of a bridge so that before you're developing 282 00:17:16,520 --> 00:17:19,000 Speaker 1: that scooter and throwing it on our streets, like, let's 283 00:17:19,040 --> 00:17:21,359 Speaker 1: have a conversation about how we could do that in 284 00:17:21,359 --> 00:17:23,760 Speaker 1: the most beneficial way for both of us. Let's co 285 00:17:23,880 --> 00:17:27,120 Speaker 1: develop a program together, and then we'll maybe give you 286 00:17:27,800 --> 00:17:30,200 Speaker 1: exclusive access to our right of way because you worked 287 00:17:30,200 --> 00:17:32,600 Speaker 1: with us in order to do this right. Well, can 288 00:17:32,640 --> 00:17:34,560 Speaker 1: you tell me a little bit about some of your 289 00:17:34,640 --> 00:17:37,880 Speaker 1: success stories. I would love to hear about some projects 290 00:17:37,920 --> 00:17:41,199 Speaker 1: that kind of stand as a model toward finding that 291 00:17:41,240 --> 00:17:46,320 Speaker 1: collaborative process and finding implementations that make a real difference. Sure, yeah, 292 00:17:46,359 --> 00:17:48,600 Speaker 1: I would love to We've been around for about five 293 00:17:48,680 --> 00:17:52,080 Speaker 1: years as a nonprofit organization and we've been working for 294 00:17:52,240 --> 00:17:54,440 Speaker 1: five years to find that model that can work. And 295 00:17:54,920 --> 00:17:56,960 Speaker 1: you know, we have a couple of success stories for sure. 296 00:17:57,040 --> 00:18:01,280 Speaker 1: One is cities have a tremendous to desire to a 297 00:18:01,400 --> 00:18:05,240 Speaker 1: decarbonized the transportation sector but also be lower the cost 298 00:18:05,320 --> 00:18:09,880 Speaker 1: of housing and lower the cost of energy just generated buildings. 299 00:18:09,920 --> 00:18:12,840 Speaker 1: And there's a technology called vehicle to grid or the 300 00:18:12,880 --> 00:18:16,919 Speaker 1: ability for a vehicle to charge a building or the 301 00:18:16,960 --> 00:18:20,080 Speaker 1: grid as opposed to the grid charging just the vehicle. 302 00:18:20,320 --> 00:18:23,199 Speaker 1: And for a long time the technology didn't exist in 303 00:18:23,240 --> 00:18:26,760 Speaker 1: order for this to really happen. About two years ago, 304 00:18:27,359 --> 00:18:30,280 Speaker 1: we were approached by a company called Formata Energy that 305 00:18:30,600 --> 00:18:34,359 Speaker 1: has the first UL approved bi directional d C fast 306 00:18:34,440 --> 00:18:36,800 Speaker 1: charger and they were looking for partners to really test 307 00:18:36,840 --> 00:18:40,200 Speaker 1: this with and in exchange for a free charger, if 308 00:18:40,440 --> 00:18:44,480 Speaker 1: the jurisdiction paid for the install then they could be 309 00:18:44,680 --> 00:18:46,880 Speaker 1: a beta testing partner. And we were able to find 310 00:18:46,920 --> 00:18:50,919 Speaker 1: two partners here with Fermata to do that testing. And 311 00:18:50,960 --> 00:18:53,919 Speaker 1: now we're finding that this technology with one charger and 312 00:18:53,960 --> 00:18:57,280 Speaker 1: one vehicle can shave three a month off of the 313 00:18:57,280 --> 00:19:01,679 Speaker 1: average electricity bill for a commercial building, which is massive. 314 00:19:01,760 --> 00:19:04,160 Speaker 1: Imagine if you had five or ten of those chargers 315 00:19:04,160 --> 00:19:06,120 Speaker 1: with vehicles plugged in at the right time of day. 316 00:19:06,200 --> 00:19:08,959 Speaker 1: And so we're using that to do analysis on what 317 00:19:09,000 --> 00:19:10,920 Speaker 1: that would mean for the whole grid if we were 318 00:19:10,920 --> 00:19:14,760 Speaker 1: to to robustly deploy that and avoid sinking a bunch 319 00:19:14,800 --> 00:19:18,960 Speaker 1: of money into stationary battery storage. So that's one I 320 00:19:19,000 --> 00:19:22,720 Speaker 1: would say. One of our our favorite models that we 321 00:19:22,840 --> 00:19:26,359 Speaker 1: found is, you know, instead of just working with one city, 322 00:19:26,480 --> 00:19:29,200 Speaker 1: why not work with a bunch and find the city 323 00:19:29,240 --> 00:19:33,320 Speaker 1: with the best problem to partner the solutions with. And 324 00:19:33,359 --> 00:19:36,800 Speaker 1: so we run this annual innovation challenge where we get 325 00:19:36,880 --> 00:19:41,040 Speaker 1: multiple governments. This year we have about ten. These are cities, counties, 326 00:19:41,480 --> 00:19:44,400 Speaker 1: state agencies, and they all have a problem like how 327 00:19:44,400 --> 00:19:47,600 Speaker 1: do we improve the resilience of our infrastructure or how 328 00:19:47,640 --> 00:19:52,080 Speaker 1: do we improve the safety of our transportation system, and 329 00:19:52,119 --> 00:19:54,280 Speaker 1: we invite ideas from all over the world from different 330 00:19:54,280 --> 00:19:57,040 Speaker 1: companies of how they could solve that problem with technology 331 00:19:57,080 --> 00:20:01,720 Speaker 1: and data, and then we facilitate the matchmaking between the 332 00:20:01,800 --> 00:20:06,080 Speaker 1: jurisdiction and those companies and it streamlines the whole process. 333 00:20:06,280 --> 00:20:08,800 Speaker 1: If there's a cost to the solution, it enables the 334 00:20:08,840 --> 00:20:12,120 Speaker 1: jurisdiction to buy it directly and we've generated a lot 335 00:20:12,160 --> 00:20:16,320 Speaker 1: of our projects through that process. Excellent. So I assume 336 00:20:16,400 --> 00:20:20,400 Speaker 1: that data collection and analysis must play a crucial role 337 00:20:21,160 --> 00:20:24,080 Speaker 1: in any strategy and the fact that we're in an 338 00:20:24,080 --> 00:20:27,800 Speaker 1: era now where the ability to collect and analyze data 339 00:20:27,920 --> 00:20:31,680 Speaker 1: at enormous scale has to be a huge benefit as well. 340 00:20:31,760 --> 00:20:35,720 Speaker 1: Is that correct? Yes, data is a part of our future, right. 341 00:20:35,840 --> 00:20:41,359 Speaker 1: It is absolutely a resource. And just like infrastructure is, 342 00:20:42,040 --> 00:20:45,399 Speaker 1: you know, a physical thing that cities manage and have 343 00:20:45,560 --> 00:20:49,000 Speaker 1: to to use in order to benefit the public, data 344 00:20:49,160 --> 00:20:52,560 Speaker 1: is becoming a part of that infrastructure, a digital infrastructure. 345 00:20:53,160 --> 00:20:57,199 Speaker 1: But data is much different than a physical asset and 346 00:20:57,800 --> 00:21:01,960 Speaker 1: it requires new sorts of digital infrastructure to manage well, 347 00:21:02,600 --> 00:21:05,800 Speaker 1: and most cities haven't figured it out quite yet. A 348 00:21:05,840 --> 00:21:08,320 Speaker 1: lot of companies have, but they're using their data for 349 00:21:08,400 --> 00:21:11,600 Speaker 1: different means how to figure out which markets are best 350 00:21:11,680 --> 00:21:14,919 Speaker 1: and how to push products. Governments need to use it 351 00:21:14,960 --> 00:21:19,120 Speaker 1: for a very different reason to solve a real world problem, right, 352 00:21:19,160 --> 00:21:22,639 Speaker 1: and unfortunately, governments have a lot of data. One of 353 00:21:22,640 --> 00:21:25,760 Speaker 1: our our partners always says we're both drowning in data 354 00:21:26,160 --> 00:21:29,639 Speaker 1: and suffocating without it, Meaning they have so much data 355 00:21:29,680 --> 00:21:32,400 Speaker 1: already at their fingertips, they just don't have the platforms 356 00:21:32,440 --> 00:21:35,359 Speaker 1: to activate that data and to get information from it. 357 00:21:36,119 --> 00:21:38,520 Speaker 1: Most systems don't talk to each other, and so they 358 00:21:38,520 --> 00:21:40,359 Speaker 1: can't use the data they have, and then there's a 359 00:21:40,400 --> 00:21:43,320 Speaker 1: lot of data they don't have. Right, Denver didn't have 360 00:21:43,440 --> 00:21:45,439 Speaker 1: local air quality information. They had to go out and 361 00:21:45,480 --> 00:21:48,160 Speaker 1: get it and use technology to get it and bring 362 00:21:48,200 --> 00:21:51,200 Speaker 1: it to the people. One anecdote I'd love to share 363 00:21:51,359 --> 00:21:54,040 Speaker 1: to really bring this all home. One of our partners 364 00:21:54,119 --> 00:21:58,159 Speaker 1: is a light our sensor manufacturer and they're working with 365 00:21:58,160 --> 00:22:01,080 Speaker 1: the city, and the city had this is you where 366 00:22:01,359 --> 00:22:03,600 Speaker 1: there's a really dangerous intersection, but they didn't know why 367 00:22:03,640 --> 00:22:07,000 Speaker 1: it was dangerous. So they installed this light our sensor 368 00:22:07,200 --> 00:22:11,720 Speaker 1: and we're able to identify near miss accidents with pedestrians 369 00:22:11,880 --> 00:22:15,560 Speaker 1: or with other cars, and they could narrow down the 370 00:22:15,600 --> 00:22:18,080 Speaker 1: exact time of day, and they were all happening at 371 00:22:18,080 --> 00:22:20,200 Speaker 1: the same time of day, and so they went out 372 00:22:20,200 --> 00:22:21,639 Speaker 1: there at this time of day and turns out the 373 00:22:21,680 --> 00:22:26,199 Speaker 1: sun glare was blinding people and they couldn't see it. 374 00:22:26,240 --> 00:22:28,439 Speaker 1: And so the solution was not the lighter, but was 375 00:22:28,520 --> 00:22:32,639 Speaker 1: to plant trees in front of where the sun is 376 00:22:32,680 --> 00:22:35,679 Speaker 1: at that time of day and dramatically improved the issue. 377 00:22:35,680 --> 00:22:38,680 Speaker 1: And so that type of data is what can be 378 00:22:38,880 --> 00:22:43,600 Speaker 1: available to make cities proactive in solving a problem before 379 00:22:43,680 --> 00:22:46,439 Speaker 1: it gets someone killed. I'm glad that that was a 380 00:22:46,480 --> 00:22:50,159 Speaker 1: positive example of a root kit being installed. That's a 381 00:22:50,240 --> 00:22:56,200 Speaker 1: terrible tech joke. But but but getting getting more serious 382 00:22:56,240 --> 00:22:58,680 Speaker 1: and more to the point about this, I think that 383 00:22:59,040 --> 00:23:02,560 Speaker 1: you've brought up some real interesting perspectives. I imagine a 384 00:23:02,560 --> 00:23:07,400 Speaker 1: lot of governments have data in silos, and they're probably 385 00:23:07,440 --> 00:23:10,720 Speaker 1: based on a lot of legacy systems. Because governments typically 386 00:23:10,800 --> 00:23:16,240 Speaker 1: don't have an aggressive schedule too maintain an update systems. 387 00:23:16,359 --> 00:23:18,239 Speaker 1: They'll rely on the system for as long as they 388 00:23:18,280 --> 00:23:22,280 Speaker 1: possibly can until something goes wrong, and so it's not 389 00:23:22,359 --> 00:23:25,200 Speaker 1: as simple as saying the information is out there, let's 390 00:23:25,200 --> 00:23:28,120 Speaker 1: just make use of it. So I imagine one part 391 00:23:28,160 --> 00:23:30,800 Speaker 1: of strategies has to be how can we work with 392 00:23:30,880 --> 00:23:36,160 Speaker 1: governments to come up with processes where we can harness 393 00:23:36,280 --> 00:23:39,439 Speaker 1: this information that we know we have, but yet do 394 00:23:39,520 --> 00:23:42,520 Speaker 1: it in a way that also makes us good stewards 395 00:23:42,560 --> 00:23:47,240 Speaker 1: of information. Clearly, when you're talking about government information, security 396 00:23:47,280 --> 00:23:51,000 Speaker 1: should be very front of mind, and to be able 397 00:23:51,040 --> 00:23:55,720 Speaker 1: to be a trustworthy guardian of information would, I think 398 00:23:55,800 --> 00:23:59,960 Speaker 1: be absolutely critical. So I feel like part of the 399 00:24:00,040 --> 00:24:03,439 Speaker 1: collaboration really is to work almost like a consultant with 400 00:24:03,560 --> 00:24:09,480 Speaker 1: governments to help judge what are the right pathways forward 401 00:24:09,920 --> 00:24:13,920 Speaker 1: to take advantage of this information you have in the 402 00:24:13,960 --> 00:24:18,000 Speaker 1: most responsible way possible. Yeah, jurisdictions need to really figure 403 00:24:18,040 --> 00:24:21,639 Speaker 1: out what is the role of government owning certain solutions 404 00:24:21,640 --> 00:24:24,719 Speaker 1: and the data that come from him, versus partnering and 405 00:24:24,760 --> 00:24:28,360 Speaker 1: giving access to a private partner to own and operate 406 00:24:28,400 --> 00:24:32,480 Speaker 1: Because governments are limited on their capacity and their understanding 407 00:24:33,000 --> 00:24:36,800 Speaker 1: on their funding, companies are not. And you also have 408 00:24:36,880 --> 00:24:39,600 Speaker 1: data that's only useful when it's aggregated outside of the 409 00:24:39,600 --> 00:24:43,080 Speaker 1: scale of the jurisdiction. Air Qualities one example of that. 410 00:24:43,600 --> 00:24:46,320 Speaker 1: When I was at Sea Dot, we had a very 411 00:24:46,440 --> 00:24:51,000 Speaker 1: large contract with Pana Sonic to develop a software as 412 00:24:51,000 --> 00:24:54,760 Speaker 1: a service platform that could make sense of the connected 413 00:24:54,840 --> 00:24:57,680 Speaker 1: vehicle data that we wanted to collect from the roadway. 414 00:24:57,760 --> 00:25:01,640 Speaker 1: Because we're not software developed verse, we can't develop that. 415 00:25:02,160 --> 00:25:04,199 Speaker 1: So to make use of the technology, we had to 416 00:25:04,200 --> 00:25:07,520 Speaker 1: work with them. And so many d ot s across 417 00:25:07,520 --> 00:25:09,840 Speaker 1: the country are trying to do it on their own. 418 00:25:09,920 --> 00:25:15,040 Speaker 1: They're trying to use interns and contractors to piece mail 419 00:25:15,080 --> 00:25:18,840 Speaker 1: together the software that can save people's lives. But I 420 00:25:18,880 --> 00:25:20,639 Speaker 1: think what a lot of them are finding is that 421 00:25:20,680 --> 00:25:25,359 Speaker 1: it's really hard to maintain a piece of software like 422 00:25:25,400 --> 00:25:27,720 Speaker 1: the private sector does if there's not a profit motive 423 00:25:27,800 --> 00:25:30,960 Speaker 1: to do it. That's a huge part of the smart 424 00:25:31,040 --> 00:25:35,000 Speaker 1: cities industries complexity is what's the role for government, what's 425 00:25:35,040 --> 00:25:37,480 Speaker 1: the role for the private sector. There has to be 426 00:25:37,520 --> 00:25:41,560 Speaker 1: an opportunity to monetize certain data because without it, we're 427 00:25:41,560 --> 00:25:43,480 Speaker 1: never going to get to the scale of the infrastructure 428 00:25:43,520 --> 00:25:47,760 Speaker 1: required to really tackle the issue itself. Right, How can 429 00:25:47,840 --> 00:25:52,680 Speaker 1: you enter into a partnership with the private sector knowing 430 00:25:52,800 --> 00:25:54,840 Speaker 1: that the whole goal of the private sector is to 431 00:25:55,160 --> 00:26:00,359 Speaker 1: monetize something in order to return value to stay holders, 432 00:26:00,359 --> 00:26:04,760 Speaker 1: whether it's privately held or publicly held, versus trying to 433 00:26:04,840 --> 00:26:09,240 Speaker 1: solve actual civil problems in a city. You know, we've 434 00:26:09,240 --> 00:26:11,800 Speaker 1: talked a bit about a real world example, and I 435 00:26:11,880 --> 00:26:15,320 Speaker 1: love it. The real world example of finding this intersection 436 00:26:15,359 --> 00:26:18,840 Speaker 1: and finding the actual root cause of these traffic accidents, 437 00:26:18,840 --> 00:26:24,360 Speaker 1: and learning that the solution wasn't technology, it was literally 438 00:26:24,440 --> 00:26:29,439 Speaker 1: providing shade so that sunlight was not blinding drivers. I 439 00:26:29,440 --> 00:26:31,800 Speaker 1: think that's a great wake up called to people who 440 00:26:31,800 --> 00:26:35,719 Speaker 1: are dieharded tech fans like myself that sometimes there are 441 00:26:35,760 --> 00:26:39,560 Speaker 1: other approaches that are far more effective. Can you give 442 00:26:39,680 --> 00:26:43,879 Speaker 1: us any other examples of how smart city approaches are 443 00:26:43,920 --> 00:26:48,280 Speaker 1: going to have a positive impact on, say, civilian life. 444 00:26:48,760 --> 00:26:50,639 Speaker 1: I struggled with this question only because there are so 445 00:26:50,680 --> 00:26:54,719 Speaker 1: many examples, and that's part of the challenge of of 446 00:26:54,800 --> 00:26:57,960 Speaker 1: the space. I think, is it one in five people 447 00:26:58,040 --> 00:27:00,159 Speaker 1: have some sort of disability in the United States, and 448 00:27:00,560 --> 00:27:03,520 Speaker 1: just navigating cities, getting from a to B if you're 449 00:27:03,520 --> 00:27:06,119 Speaker 1: in a wheelchair or if you're blind or visually impaired, 450 00:27:06,600 --> 00:27:10,520 Speaker 1: is really difficult. So we've done some work with accessibility 451 00:27:10,640 --> 00:27:13,800 Speaker 1: tech companies who there are so many ways that technology 452 00:27:13,800 --> 00:27:19,160 Speaker 1: can enable better site or better navigation of city environments, 453 00:27:19,440 --> 00:27:22,800 Speaker 1: whether you're mapping the conditions of sidewalks to get to 454 00:27:22,920 --> 00:27:25,600 Speaker 1: and from A to B or in one case, we've 455 00:27:25,600 --> 00:27:29,399 Speaker 1: worked with a technology to develop a navigation system for 456 00:27:29,520 --> 00:27:32,800 Speaker 1: indoor spaces for the blind and visually impaired. So if 457 00:27:32,880 --> 00:27:34,560 Speaker 1: you want to go to the museum or if you 458 00:27:34,560 --> 00:27:37,920 Speaker 1: want to go to the library, you can still experience 459 00:27:38,000 --> 00:27:40,800 Speaker 1: that space by knowing exactly where you are to the 460 00:27:40,840 --> 00:27:44,600 Speaker 1: centimeter and knowing what's around you and describing that environment 461 00:27:44,640 --> 00:27:47,320 Speaker 1: to you as you walk through it. And so that's 462 00:27:47,400 --> 00:27:50,880 Speaker 1: one way that whether you're able bodied, or if you're 463 00:27:50,920 --> 00:27:53,240 Speaker 1: young or you're old, you know, there's a lot of 464 00:27:53,240 --> 00:27:57,440 Speaker 1: technologies that can help the ease of access and around cities, 465 00:27:57,720 --> 00:27:59,480 Speaker 1: that can help people in a lot of ways. But 466 00:28:00,320 --> 00:28:02,440 Speaker 1: that's just one that I like to highlight because it's 467 00:28:02,480 --> 00:28:05,760 Speaker 1: one that people don't think about very often, right. I 468 00:28:05,800 --> 00:28:11,119 Speaker 1: think of augmented reality as any technology that enhances the 469 00:28:11,200 --> 00:28:14,680 Speaker 1: experience of you being in a physical place, and that 470 00:28:14,760 --> 00:28:19,920 Speaker 1: can include things like audio cues and even tactile feedback, 471 00:28:19,960 --> 00:28:23,480 Speaker 1: haptic feedback. That if you take that narrow view of 472 00:28:23,520 --> 00:28:25,920 Speaker 1: what augmented reality is and you're just thinking, oh, that's 473 00:28:25,920 --> 00:28:30,320 Speaker 1: smart glasses, you're really not tapping into the potential of 474 00:28:30,359 --> 00:28:34,119 Speaker 1: that concept, not just technology that's just the manifestation of 475 00:28:34,160 --> 00:28:38,880 Speaker 1: the concept, but the actual concept of enhancing the area 476 00:28:38,920 --> 00:28:41,760 Speaker 1: around you in some way, whether that might be for 477 00:28:41,960 --> 00:28:48,719 Speaker 1: entertainment purposes, educational navigation. The applications are limitless. Yeah, there 478 00:28:48,720 --> 00:28:50,719 Speaker 1: are so many cool ways you can use augmented reality. 479 00:28:50,720 --> 00:28:52,720 Speaker 1: But we've got a couple of companies, one that that 480 00:28:52,800 --> 00:28:56,480 Speaker 1: uses it to visualize new development. So if you're a 481 00:28:56,480 --> 00:29:00,000 Speaker 1: citizen and you're concerned about the new development happening across 482 00:29:00,200 --> 00:29:03,120 Speaker 1: the street, you can actually visualize it in real life 483 00:29:03,120 --> 00:29:05,280 Speaker 1: to see what it would look like and provide your 484 00:29:05,280 --> 00:29:08,560 Speaker 1: feedback that way. There's lots of very tangible ways that 485 00:29:08,920 --> 00:29:13,080 Speaker 1: governments or utilities can use these technologies if they're focused 486 00:29:13,160 --> 00:29:16,440 Speaker 1: on trying to do it right. And I think that's 487 00:29:16,480 --> 00:29:19,320 Speaker 1: the key is so many governments are just focused on 488 00:29:19,360 --> 00:29:22,200 Speaker 1: providing the services the way they are today. It takes 489 00:29:22,360 --> 00:29:25,800 Speaker 1: purposeful and intentional action and process to do it differently. 490 00:29:28,640 --> 00:29:31,480 Speaker 1: Before saying goodbye to Tyler, I had to ask him 491 00:29:31,760 --> 00:29:37,080 Speaker 1: one more thing, what is a project you personally are 492 00:29:37,240 --> 00:29:41,640 Speaker 1: very excited about? Well, our new five G project really 493 00:29:41,680 --> 00:29:45,080 Speaker 1: really excited about building a five G network that we 494 00:29:45,120 --> 00:29:47,680 Speaker 1: can use to test and develop products. We're gonna be 495 00:29:47,760 --> 00:29:51,840 Speaker 1: targeting startups and entrepreneurs that are owned or hire people 496 00:29:51,840 --> 00:29:56,200 Speaker 1: of color, Indigenous women, people that are underrepresented, including people 497 00:29:56,240 --> 00:29:59,680 Speaker 1: with disabilities, so that they have access to infrastructure to 498 00:29:59,720 --> 00:30:04,240 Speaker 1: do testing, to understand these technologies and to grow here 499 00:30:04,280 --> 00:30:07,680 Speaker 1: in Colorado. So we're gonna be beginning that work later 500 00:30:07,760 --> 00:30:10,800 Speaker 1: this year and are excited to start welcoming our first 501 00:30:10,840 --> 00:30:14,160 Speaker 1: companies hopefully in Q one of next year, and that 502 00:30:14,160 --> 00:30:17,280 Speaker 1: will really get us into this economic development space where 503 00:30:17,600 --> 00:30:19,600 Speaker 1: I think a lot of cities have an interest in 504 00:30:19,800 --> 00:30:23,200 Speaker 1: right being the home for a growing company and also 505 00:30:23,400 --> 00:30:27,000 Speaker 1: away for us to ensure that these solutions that are 506 00:30:27,000 --> 00:30:30,920 Speaker 1: influencing our infrastructure of tomorrow are being built by the 507 00:30:30,960 --> 00:30:33,920 Speaker 1: people that have been left behind by the infrastructure of today. 508 00:30:34,560 --> 00:30:39,120 Speaker 1: Excellent answer, Tyler, Thank you so much for joining us. 509 00:30:39,160 --> 00:30:43,800 Speaker 1: This has been a really informative and and fun conversation 510 00:30:43,880 --> 00:30:46,280 Speaker 1: for me. Yeah, I've really enjoyed it. Thank you for 511 00:30:46,320 --> 00:30:48,360 Speaker 1: digging into this topic with me, and I hope your 512 00:30:48,360 --> 00:30:56,360 Speaker 1: listeners enjoy it. Tyler Speedech opened my eyes when it 513 00:30:56,440 --> 00:30:59,880 Speaker 1: comes to smart cities. He has a realistic perspective on 514 00:31:00,040 --> 00:31:04,280 Speaker 1: what it takes to incorporate technological solutions into city infrastructure. 515 00:31:04,800 --> 00:31:07,440 Speaker 1: Any effort to do so is going to require a 516 00:31:07,480 --> 00:31:12,320 Speaker 1: lot of collaboration and innovation. The problems aren't necessarily simple, 517 00:31:12,400 --> 00:31:14,960 Speaker 1: and getting all parties on the same page can be 518 00:31:15,000 --> 00:31:18,680 Speaker 1: hard too, But the need for those solutions is apparent, 519 00:31:19,160 --> 00:31:23,440 Speaker 1: and the payoff of implementing them is incalculable. I think 520 00:31:23,440 --> 00:31:27,000 Speaker 1: of it as empowering citizens who then contribute to society, 521 00:31:27,320 --> 00:31:31,480 Speaker 1: at which point everyone benefits. I'm excited to learn more 522 00:31:31,520 --> 00:31:34,560 Speaker 1: about the five G network Tyler's team intends to build 523 00:31:34,640 --> 00:31:37,959 Speaker 1: as a testing ground for all sorts of other technologies. 524 00:31:38,520 --> 00:31:42,440 Speaker 1: I expect that foundation of connectivity will help produce some 525 00:31:42,600 --> 00:31:47,160 Speaker 1: amazing products. Some of those will likely become commercial products, 526 00:31:47,320 --> 00:31:50,000 Speaker 1: perhaps ones that don't actually have a real place in 527 00:31:50,080 --> 00:31:54,320 Speaker 1: smart city applications. Others might exclusively be useful for the 528 00:31:54,360 --> 00:31:57,640 Speaker 1: maintenance and operation of a city. As we've seen many 529 00:31:57,680 --> 00:32:01,360 Speaker 1: times throughout this series, it's connect to it that transforms 530 00:32:01,600 --> 00:32:06,400 Speaker 1: limited technologies into powerful tools. Having the ability to channel 531 00:32:06,440 --> 00:32:09,880 Speaker 1: large amounts of data with negligible delay is a real 532 00:32:10,000 --> 00:32:13,000 Speaker 1: game changer. I hope that Tyler's SPEEDEC and his team 533 00:32:13,000 --> 00:32:16,040 Speaker 1: are able to shepherd new technologies into the smart city 534 00:32:16,080 --> 00:32:20,560 Speaker 1: space that will ultimately make life better for citizens. Thanks 535 00:32:20,560 --> 00:32:23,240 Speaker 1: again to Tyler for joining the show and sharing his 536 00:32:23,320 --> 00:32:29,360 Speaker 1: experience and mission. Be sure to tune into future episodes 537 00:32:29,360 --> 00:32:32,000 Speaker 1: of The Restless Ones where I'll speak with other leaders 538 00:32:32,000 --> 00:32:34,880 Speaker 1: in the tech space to see what lessons they've learned 539 00:32:35,000 --> 00:32:43,720 Speaker 1: and their approach to leadership. I'll see you then. Tea 540 00:32:43,800 --> 00:32:46,240 Speaker 1: Mobile for Business knows companies want more than a one 541 00:32:46,280 --> 00:32:49,320 Speaker 1: size fits all approach to support. I want the world, 542 00:32:49,880 --> 00:32:53,440 Speaker 1: so we provide three sixty support customized to your business. 543 00:32:53,520 --> 00:32:56,800 Speaker 1: From discovery through post deployment. You'll get a dedicated account 544 00:32:56,800 --> 00:33:00,960 Speaker 1: team and expertise from solutions engineers and into street advisors 545 00:33:01,000 --> 00:33:06,640 Speaker 1: already right now, I want it now. Three six support 546 00:33:06,800 --> 00:33:11,040 Speaker 1: that's customized for your success. That's unconventional thinking from t 547 00:33:11,200 --> 00:33:12,040 Speaker 1: Mobile for Business