WEBVTT 1 00:00:00.590 --> 00:00:10.940 For 2 00:00:13.840 --> 00:00:14.080 Yeah 3 00:00:14.080 --> 00:00:14.900 thank you very much 4 00:00:14.900 --> 00:00:18.100 I think I try to speak without the microphone 5 00:00:18.100 --> 00:00:19.000 Please let me know 6 00:00:19.000 --> 00:00:20.390 particularly in the background 7 00:00:20.440 --> 00:00:21.920 If if IT's too large 8 00:00:21.920 --> 00:00:26.730 IT's not loud enough just to indicate to me to be louder 9 00:00:27.200 --> 00:00:28.640 I'm very glad I must say 10 00:00:28.640 --> 00:00:29.200 um 11 00:00:29.200 --> 00:00:32.540 given this opportunity to teach today here 12 00:00:33.030 --> 00:00:36.010 And as i've already been introduced 13 00:00:36.010 --> 00:00:43.520 i'm coming from private university and I want before I dive into this topic of the smart city 14 00:00:43.850 --> 00:00:49.930 I want to give a little bit more of a background after this nice introduction of this gun 15 00:00:50.290 --> 00:00:51.250 Um 16 00:00:52.070 --> 00:00:54.320 you find again what has been said 17 00:00:54.320 --> 00:00:56.190 I just want to add um 18 00:00:56.190 --> 00:01:00.800 that i'm building up a new research group on urban environmental governance 19 00:01:01.010 --> 00:01:03.350 And that's the topic I I focus on 20 00:01:03.860 --> 00:01:05.580 And um 21 00:01:05.580 --> 00:01:13.320 i've also got a background in science and technology studies which brought me actually from geography to this topic of the smart city 22 00:01:14.900 --> 00:01:17.260 And the reason um 23 00:01:18.600 --> 00:01:20.360 that has also been said already 24 00:01:20.500 --> 00:01:27.030 The reason why why I came here to china for the first time is the a project um 25 00:01:27.030 --> 00:01:32.580 that has also already been mentioned on smart cities in europe and china 26 00:01:32.790 --> 00:01:36.700 And we had a project meeting in ningbo just last week 27 00:01:37.250 --> 00:01:38.150 And uh 28 00:01:38.150 --> 00:01:41.050 I want to give you a little background on this project 29 00:01:42.110 --> 00:01:43.730 So the the objective 30 00:01:43.730 --> 00:01:52.070 the overall objective of the project is to study a smart and eco urbanism when it comes together 31 00:01:52.070 --> 00:02:02.060 the ambition of municipal administrations and other actors to become a smart city or to develop a smart city and to develop an eco city at the same time 32 00:02:02.060 --> 00:02:05.810 So we look at this interplay of those two agendas 33 00:02:05.810 --> 00:02:06.630 if you want 34 00:02:07.190 --> 00:02:08.750 And um 35 00:02:08.980 --> 00:02:12.600 this has to do with positioning cities with competition 36 00:02:12.600 --> 00:02:20.350 but also we want to look at the implementation and material changes and institutional changes and um 37 00:02:20.350 --> 00:02:23.730 the means that we have as a team is 38 00:02:23.730 --> 00:02:24.000 um 39 00:02:24.000 --> 00:02:29.440 to compare cases in china and europe and not only um 40 00:02:29.440 --> 00:02:31.820 european versus chinese and also chinese 41 00:02:31.820 --> 00:02:40.490 those chinese and that versus u k united kingdom cases and german cases with branch spaces and so on 42 00:02:41.790 --> 00:02:45.040 And we also compare not only cities as such 43 00:02:45.280 --> 00:02:51.190 we understand them as containers of city projects an eco city projects 44 00:02:51.520 --> 00:02:57.590 And we also compare was on the individual projects against each other because uh 45 00:02:57.590 --> 00:02:59.130 and urban development here 46 00:02:59.130 --> 00:03:01.270 And there's a new app developed there 47 00:03:01.270 --> 00:03:03.970 And those projects are what we are interested in 48 00:03:03.970 --> 00:03:09.240 but also how they build up a broader agenda for particular city 49 00:03:11.810 --> 00:03:15.820 So the specific objects are objectives 50 00:03:15.820 --> 00:03:17.500 It should say objectives 51 00:03:17.500 --> 00:03:17.880 um 52 00:03:17.880 --> 00:03:22.430 is to identify patterns in the governance of those processes 53 00:03:22.790 --> 00:03:28.270 the governance of the projects and of the overall development of the city 54 00:03:29.060 --> 00:03:32.470 and also explore potential for learning 55 00:03:32.720 --> 00:03:36.200 And I think that made the european uh 56 00:03:36.200 --> 00:03:39.070 finders give us the money that we said 57 00:03:39.070 --> 00:03:45.040 We want to look learn how low earning can happen across cities 58 00:03:46.000 --> 00:03:46.820 And of course 59 00:03:46.820 --> 00:03:52.140 we also want to come to policy recommendations with regard to the governance of the projects 60 00:03:52.140 --> 00:04:00.080 And the overall process is also with regard to framework conditions that are favorable of smart equal development 61 00:04:02.390 --> 00:04:03.150 So 62 00:04:03.150 --> 00:04:03.470 um 63 00:04:03.470 --> 00:04:06.650 just a few last words on this project 64 00:04:06.920 --> 00:04:07.720 Um 65 00:04:07.720 --> 00:04:09.130 it will last for three years 66 00:04:09.130 --> 00:04:10.900 We are through the first year 67 00:04:10.900 --> 00:04:15.940 First year has just been completed with this meeting last week in ningbo 68 00:04:16.260 --> 00:04:20.730 And actually the finding is a bit strange for european context 69 00:04:20.970 --> 00:04:23.950 IT's not the european commission finding us 70 00:04:24.230 --> 00:04:25.720 IT's not one agency 71 00:04:25.720 --> 00:04:27.250 but IT's actually many 72 00:04:27.530 --> 00:04:29.710 And you see here that um 73 00:04:29.710 --> 00:04:30.940 in the uk 74 00:04:31.860 --> 00:04:32.520 I think 75 00:04:32.520 --> 00:04:33.050 yeah 76 00:04:33.300 --> 00:04:35.450 in in unITed kingdom 77 00:04:35.450 --> 00:04:37.670 IT c s r c in the meadowlands 78 00:04:37.670 --> 00:04:39.580 IT's another dutch founder 79 00:04:39.770 --> 00:04:41.070 And um 80 00:04:41.070 --> 00:04:52.630 I appreciate funding of the german research funding association d f k and in time you'll see is n s f c and um 81 00:04:52.630 --> 00:04:53.510 the partners 82 00:04:53.510 --> 00:04:53.930 Um 83 00:04:53.930 --> 00:04:56.810 actually the lead partner is kings college in london 84 00:04:56.950 --> 00:05:00.650 And then we are from universities in nottingham 85 00:05:00.650 --> 00:05:01.150 ningbo 86 00:05:01.150 --> 00:05:01.810 china 87 00:05:01.810 --> 00:05:05.610 This is the chinese partner also in the netherlands 88 00:05:05.610 --> 00:05:09.460 It raised freiberg germany to lose westminster and cardiff 89 00:05:09.680 --> 00:05:11.800 So we have quite a large consumption 90 00:05:14.320 --> 00:05:15.190 So 91 00:05:15.190 --> 00:05:15.990 um 92 00:05:16.440 --> 00:05:17.100 well 93 00:05:17.290 --> 00:05:19.200 the talk of today 94 00:05:19.520 --> 00:05:20.560 as it has been said 95 00:05:20.560 --> 00:05:23.120 I would like to have two major parts 96 00:05:23.510 --> 00:05:28.880 One being really as i've been asked to talk about the smart city in germany 97 00:05:29.640 --> 00:05:30.490 uh 98 00:05:30.840 --> 00:05:32.130 and I said right away 99 00:05:32.130 --> 00:05:33.200 actually 100 00:05:33.430 --> 00:05:34.470 there's not that much 101 00:05:34.470 --> 00:05:34.810 You know 102 00:05:34.810 --> 00:05:37.570 there's nothing to show of um 103 00:05:37.570 --> 00:05:38.920 from german cases 104 00:05:38.920 --> 00:05:39.530 You know 105 00:05:39.730 --> 00:05:40.100 um 106 00:05:40.100 --> 00:05:41.900 I said I propose different topics 107 00:05:41.900 --> 00:05:42.830 but people said no 108 00:05:42.830 --> 00:05:43.070 no 109 00:05:43.070 --> 00:05:46.360 we want to learn about german smart city 110 00:05:46.810 --> 00:05:53.930 So and actually i'm i'm quite happy to talk about it because also what is going on and what is not going on is interesting 111 00:05:53.930 --> 00:05:54.640 I think 112 00:05:55.640 --> 00:05:56.150 Um 113 00:05:56.150 --> 00:06:04.140 so I I talk about this in the first step and then give some examples from two major cities in germany 114 00:06:04.140 --> 00:06:07.260 hamburg and munich in the north and in the south 115 00:06:08.210 --> 00:06:18.890 And then discuss on the priorities of those developments and the obstacles also for smart city smart eco city development in the cities 116 00:06:19.790 --> 00:06:21.410 And it will be the first part 117 00:06:22.120 --> 00:06:31.270 And then I also give two more cases of something that is not really smart city development 118 00:06:31.660 --> 00:06:39.490 but which I find also still very interesting and indicative with regard to urban development of today 119 00:06:40.450 --> 00:06:49.960 So I talk about actually the the district that i'm living at in fiber along and before give a case from the war area 120 00:06:49.960 --> 00:06:51.730 which is industrial area 121 00:06:51.860 --> 00:06:52.450 um 122 00:06:52.450 --> 00:06:53.450 in uh 123 00:06:53.450 --> 00:06:58.000 in bottom and the so called bottom innovation city 124 00:06:59.440 --> 00:07:01.080 And then finally reflects 125 00:07:01.870 --> 00:07:04.230 So that's that's the plan 126 00:07:04.800 --> 00:07:06.450 And right away 127 00:07:06.820 --> 00:07:07.910 smart city 128 00:07:07.910 --> 00:07:08.760 You know 129 00:07:08.760 --> 00:07:10.640 and you've heard many times 130 00:07:10.640 --> 00:07:13.400 That is a very important term nowadays 131 00:07:13.620 --> 00:07:15.100 And as an indication 132 00:07:15.100 --> 00:07:18.550 i've just looked at scientific publications 133 00:07:18.770 --> 00:07:23.670 So an indicator for me is how much it is written about in scientific journals 134 00:07:24.570 --> 00:07:29.970 So i've i've reviewed a big database of scientific articles 135 00:07:29.970 --> 00:07:31.080 science direct 136 00:07:31.140 --> 00:07:33.220 which is easily accessible 137 00:07:33.220 --> 00:07:37.620 And i'll just end at smart city or smart cities in the euro 138 00:07:38.000 --> 00:07:40.510 And you see how it's developed 139 00:07:40.510 --> 00:07:41.820 Can you see actually 140 00:07:42.460 --> 00:07:43.610 yeah 141 00:07:43.910 --> 00:07:45.940 so actually 142 00:07:45.940 --> 00:07:51.390 IT's a rather linear a IT's a steady increase in numbers 143 00:07:51.760 --> 00:07:53.380 And then in the last four years 144 00:07:53.380 --> 00:07:57.160 IT's really nearly x financial growth 145 00:07:57.610 --> 00:07:58.890 In the last few years 146 00:07:59.220 --> 00:08:01.670 IT's been really a great improvement 147 00:08:01.670 --> 00:08:01.910 Oh 148 00:08:01.910 --> 00:08:04.600 I mean I I great increase in the numbers 149 00:08:06.150 --> 00:08:07.850 So what is it 150 00:08:07.850 --> 00:08:12.730 I don't want to spend much time on defining it for one reason 151 00:08:12.730 --> 00:08:13.030 uh 152 00:08:13.030 --> 00:08:15.790 because you've already heard a lot about it 153 00:08:16.260 --> 00:08:28.750 But the second reason is that I think really that's but I think really IT's necessary that in every cITy you define individually what makes our cities smart 154 00:08:28.750 --> 00:08:32.200 What is that we want to develop into 155 00:08:32.430 --> 00:08:33.350 I was sixteen 156 00:08:34.530 --> 00:08:41.440 So I I I think you could debate a lot about what are the real definition of the smart city is 157 00:08:41.440 --> 00:08:43.400 But that's an academic debate 158 00:08:43.640 --> 00:08:45.340 And it's very important 159 00:08:45.340 --> 00:08:50.070 If something is used as a guideline on urban development 160 00:08:50.070 --> 00:08:52.710 it needs to be specific of the place 161 00:08:53.260 --> 00:08:59.020 And it needs to be specific of the kind of the people speaking about this place 162 00:09:01.130 --> 00:09:01.950 Nevertheless 163 00:09:01.950 --> 00:09:03.140 I would suggest 164 00:09:03.290 --> 00:09:03.600 uh 165 00:09:03.600 --> 00:09:04.630 one definition 166 00:09:04.630 --> 00:09:07.280 just as a working definition for today 167 00:09:09.150 --> 00:09:09.680 Um 168 00:09:09.680 --> 00:09:35.070 and the shortest definition that I could find of the smart city is the one by betty at all as a smart city is a city in which ict with isa tv information and communication technology is merged with traditional infrastructure as coordinated and integrated using new digital digital technologies 169 00:09:36.220 --> 00:09:37.970 So that is in very short 170 00:09:38.260 --> 00:09:39.240 I I think 171 00:09:39.240 --> 00:09:46.650 a useful appreciation approach to smart cities and secondly 172 00:09:46.650 --> 00:09:49.930 it reflects the core of many practitioners 173 00:09:49.930 --> 00:09:51.720 definitions of the smart city 174 00:09:52.820 --> 00:09:58.260 So I would like to keep this in mind for the lecture as a definition 175 00:10:00.820 --> 00:10:05.340 And now come to some findings because what we did in germany 176 00:10:05.340 --> 00:10:07.270 I mean in all countries 177 00:10:07.360 --> 00:10:09.420 we scan all our cities 178 00:10:09.420 --> 00:10:09.700 Well 179 00:10:09.700 --> 00:10:12.550 there is a small city and eco city development 180 00:10:12.860 --> 00:10:21.830 So we check for particularly ambitious environmental policies and for ambitions to become a smart city 181 00:10:22.820 --> 00:10:25.320 It does not need to be called smart city 182 00:10:25.850 --> 00:10:26.470 In france 183 00:10:26.470 --> 00:10:27.110 for example 184 00:10:27.110 --> 00:10:29.260 IT's called build antigens 185 00:10:29.490 --> 00:10:35.600 So we looked for that as well or a digital city or innovation city 186 00:10:35.600 --> 00:10:37.900 So we scan the web 187 00:10:38.150 --> 00:10:41.720 the internet for the ambitions of the city 188 00:10:42.180 --> 00:10:43.040 And in germany 189 00:10:43.040 --> 00:10:49.420 we are we are very lucky because every city has got one particular website of the city 190 00:10:49.470 --> 00:10:50.610 which is easy to find 191 00:10:50.610 --> 00:10:55.120 which is the city name dot d e so it's a good entry point 192 00:10:55.120 --> 00:10:59.260 And then you can study how the city is presented 193 00:11:00.670 --> 00:11:03.150 So we did this for all us shame 194 00:11:03.150 --> 00:11:04.330 It says seventy nine 195 00:11:04.330 --> 00:11:09.730 So we've got eighty one cities above one hundred thousand inhabitants 196 00:11:10.880 --> 00:11:13.480 So that's really the biggest we've got 197 00:11:13.480 --> 00:11:13.700 I mean 198 00:11:13.700 --> 00:11:17.420 we've got only a few cities with the million or more 199 00:11:17.670 --> 00:11:20.400 So this is called a large city in germany 200 00:11:20.470 --> 00:11:23.960 everything that has got more than one hundred thousand inhabitants 201 00:11:24.460 --> 00:11:26.820 IT's called a smaller a large cITy 202 00:11:27.480 --> 00:11:29.440 So we skipped all of them 203 00:11:29.700 --> 00:11:30.510 Eighty one 204 00:11:30.510 --> 00:11:34.470 that's and we found very few 205 00:11:34.470 --> 00:11:35.340 actually 206 00:11:35.670 --> 00:11:36.630 um 207 00:11:38.850 --> 00:11:43.250 municipalities that are really committed to become a small city 208 00:11:43.990 --> 00:11:49.400 Many want to become an eco city or an environment 209 00:11:49.880 --> 00:11:50.140 uh 210 00:11:50.140 --> 00:11:51.500 pioneer city 211 00:11:51.670 --> 00:11:55.860 but very few actually aim at becoming a smart city 212 00:11:56.920 --> 00:11:59.620 And of those who have the ambition 213 00:11:59.750 --> 00:12:03.440 very few have more than some few individual projects 214 00:12:04.120 --> 00:12:08.090 And if you then look for those who are really coordinated 215 00:12:08.090 --> 00:12:09.380 IT's even fewer 216 00:12:11.410 --> 00:12:18.260 And I I find a particular development that there were a lot of announcements in the years twenty thirteen 217 00:12:18.260 --> 00:12:19.420 twenty fourteen 218 00:12:19.640 --> 00:12:22.720 Many mayors say we want to be the first smart city 219 00:12:22.720 --> 00:12:24.150 the biggest or the best 220 00:12:24.980 --> 00:12:26.820 But then there's not much follow up 221 00:12:26.820 --> 00:12:28.010 What you can see 222 00:12:28.810 --> 00:12:30.820 If you ask people 223 00:12:30.820 --> 00:12:32.170 we are we are working on it 224 00:12:32.170 --> 00:12:32.910 you know 225 00:12:33.960 --> 00:12:34.880 um 226 00:12:35.080 --> 00:12:44.370 but there's a few cities where to which every excellent refers if you ask them what what's the smart city in germany 227 00:12:44.910 --> 00:12:50.610 People say we are go for hamburg munich burden like the big cities and cologne 228 00:12:50.610 --> 00:12:52.650 That's really the four biggest cities 229 00:12:52.650 --> 00:12:55.620 If you are not considering the big metropolitan areas 230 00:12:55.620 --> 00:12:59.170 if you just go for the city's these are the four biggest cities 231 00:13:02.020 --> 00:13:04.030 So counting 232 00:13:04.030 --> 00:13:05.390 discounting them 233 00:13:05.690 --> 00:13:07.340 Eighty one overall 234 00:13:08.180 --> 00:13:10.380 So in in thirty four 235 00:13:10.380 --> 00:13:11.470 in more than half 236 00:13:11.470 --> 00:13:14.390 we didn't find any ambition to become a smart city 237 00:13:16.510 --> 00:13:18.080 In nineteen of them 238 00:13:18.560 --> 00:13:23.530 we found few projects and little coordination between the projects 239 00:13:23.590 --> 00:13:25.070 No guiding document 240 00:13:25.070 --> 00:13:26.090 for example 241 00:13:26.370 --> 00:13:28.900 This is how we want to become this modern city 242 00:13:30.360 --> 00:13:39.210 And um only nineteen we find something like a real development and coordinated development towards smart city 243 00:13:42.570 --> 00:13:58.650 And this actually is very much in line with a a big overview over all european cities that has been done in fifteen has been published in twenty fifteen by the european union by the general director 244 00:13:58.650 --> 00:14:00.060 IT's on um 245 00:14:00.060 --> 00:14:01.680 internal policies 246 00:14:02.200 --> 00:14:05.220 It has been published and they said 247 00:14:05.220 --> 00:14:06.700 overall in europe 248 00:14:07.170 --> 00:14:17.460 you find in scandinavia you find virtually all large cities aim to become smart city aim to become smart city in austria 249 00:14:17.460 --> 00:14:18.300 the netherlands 250 00:14:18.300 --> 00:14:20.900 IT's more than half its a majority 251 00:14:21.760 --> 00:14:25.270 And I I know that and we've got no partners in italy 252 00:14:25.270 --> 00:14:25.590 Um 253 00:14:25.590 --> 00:14:29.880 but I know it from austria that actually all large cities and you become smart 254 00:14:29.980 --> 00:14:30.550 um 255 00:14:30.550 --> 00:14:32.680 cities and in the lab metal 256 00:14:32.680 --> 00:14:35.900 And it's also many in uk 257 00:14:35.900 --> 00:14:36.320 spain 258 00:14:36.320 --> 00:14:36.700 france 259 00:14:36.700 --> 00:14:37.650 IT's about half 260 00:14:37.650 --> 00:14:38.220 I don't know 261 00:14:38.220 --> 00:14:39.510 exactly in france 262 00:14:39.510 --> 00:14:42.040 IT could be and germany 263 00:14:42.180 --> 00:14:42.610 poland 264 00:14:42.610 --> 00:14:44.340 that's really related to the curriculum 265 00:14:44.340 --> 00:14:45.760 That's that's true