气候变化和新冠疫情时代的智慧城市需要数字双胞胎

IF 2.1 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS IET Smart Cities Pub Date : 2020-09-15 DOI:10.1049/iet-smc.2020.0071
Joseph Dignan
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Proptech, Plantech, Digital twins, VR &amp; AR, Ledger technologies, 5G, AI and Deep Learning, Data Exchanges and Edge Computing that will shape citizen engagement, economic growth and physical infrastructure, but we also need the basic infrastructure of power, water and connectivity in the developing world. Currently, the new enabling technologies are still siloed into point solutions with companies developing single technology value propositions around AI, proptech, Ledger <i>et al.</i> Whatever our working definition of what comprises ‘smart’, the market is maturing into IoT platforms where hardware captures data and software analyses it. To enable us to turn data into information allowing insight to inform impact we also need to share information in an appropriate way and surface it in the most accessible manner possible. We are capturing ever-increasing amounts of data, but our ability to share it with the correct checks and balances is problematic. This will have to change and there is an increasing need for Data Trust models that allow us to synthesise data, and Digital Twinning; where we create a virtual replica of the physical and can feed real time information into the model allowing scenario planning and the meshing of soft and hard data that creates a narrative around arenas such as Health, Wellbeing and Mobility. This leverages the new disruptive technologies mentioned above, allowing city authorities agile and informed decision making while facilitating the sharing of information between the public and private sectors. As such, it creates a market for enabling technologies while informing growth in the city.</p><p>One of the things I noticed when working in the planning department of a local authority in the distant past was that if I used words to explain something I wanted to do, I would be met with blank faces and disinterest. However, if I produced a schematic, plan or map the whole atmosphere changed. Tables were cleared, eyes lit up, erstwhile disinterest turned into enthusiasm. You get the same affect with architects, engineers and developers. These are people who think visually. Nowadays, the same can be seen with the new sorcerers of IoT; data scientists and AI specialists and is the reasons why Digital Twins are both attractive and effective.</p><p>We create so much data, most of which is binary, we need a way to make it talk to us. Maps, charts <i>et al.</i> gave us a two-dimensional view and models gave us a static 3D representation. Related information- reports, impact assessments, development strategies and the rest were created by the kilo then sealed in PDFs and only read by, well, nobody. My planning department experience was 30 years ago, and the stunning thing is the industry hasn't changed. This is still the way we do master planning. We have moved on through CAD and BIM, but the overall process is the same, still frustrated by the inaccessibility of information entombed in PDFs. The above is all the more disappointing given we are well into the 4th Industrial revolution, characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. This is where Digital Twins come into their own.</p><p>A simple definition of a digital twin is that is a digital model of a physical asset, which continuously collects information (via sensors, drones or other IoT and IIoT data collection tools) and applies advanced analytics, machine-learning and artificial intelligence (AI) to gain valuable real-time insights about the physical asset's performance, operation or profitability. In essence, you create a 3D model of a physical entity and populate it with data allowing you manage the physical entity but also to run scenario planning for predicative insight. You now have an accessible oracle for planners, developers, officials, politicians and citizens to share information and contribute to the future of smart communities. The importance of this new way of tracking how people move through cities and buildings is a tool we can use to ameliorate the challenges of Covid-19. A recent Forbes article predicted that a post-coronavirus future will include more contactless interfaces and interactions, strengthened digital infrastructure, better monitoring and use of IoT and Big Data, AI-enabled development, and an increased reliance on robots. Put simply, the trend will be towards virtualization and digitalization in all industries, and Digital Twin-making will pave the road to virtualization and digitalization in the building industry. More online meetings, less travel; more shared, flexible workspaces, fewer assigned physical spaces; more operational data collection via IOT sensors, less manual reporting; more AI-enabled analysis, less guesswork; more maintenance tasks performed by robots, less manual intervention. Building sensors will monitor the temperature of people both within and without the building and can tell if groups are forming without the concomitant social distancing, allowing messages to be sent asking that groups disperse. Apps can be used to identify and book desk and room slots before arrival in buildings and can track people and infection blooms allowing Authorities the ability to see the spread of contagion and respond accordingly.</p><p>Arguably, there is a recognised three-step plan to build successful advanced urban infrastructure in the 21st Century city. Firstly, through consultation, agree a set of open outcomes and time frame. Secondly, work out what people will have to do differently (enabled by what technology) to achieve those outcomes. Thirdly, define what success looks like and have the ability to measure the difference. To make the above work you must have data that you can turn into information, giving you insight so you can make decisions with real impact. For that to happen successfully you need to be able to synthesise information and share data through the right governance and protocols.</p><p>It can be argued that IT companies have failed to lead the smart cities market because they are wedded to outdated business models where the return on investment (ROI) is too short and still focus on proprietary point solutions. Instead, the market is increasingly led by the Architecture, Engineering and Construction companies (AEC) who have a longer ROI, the ability to take a lead contractor role and bring in Telco, Utilities and IT as, and when, required but the force majeure is that we need visibility of decision making options facilitated by advanced urban digital infrastructure.</p><p>In conclusion, Digital twins are not a universal panacea but an integral part of the maturation of Advanced Urban Digital Urbanisation colloquially described as the ‘smart city’ market. We are creating the base data through the development of IoT platforms, we have yet to create Data exchanges that will allow for data synthesis that will bring the most out of Digital Twins and concomitant fit for purpose ROI models that would allow us to build the business case for initial and subsequent investment.</p><p>So where will the leadership come from? International Financial Institutions such as the European Commission, World Bank, Asian Development Bank <i>et al.</i>, Sovereign Wealth Funds and National Governments have the funding and mandate but no unifying plan. 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Tables were cleared, eyes lit up, erstwhile disinterest turned into enthusiasm. You get the same affect with architects, engineers and developers. These are people who think visually. Nowadays, the same can be seen with the new sorcerers of IoT; data scientists and AI specialists and is the reasons why Digital Twins are both attractive and effective.</p><p>We create so much data, most of which is binary, we need a way to make it talk to us. Maps, charts <i>et al.</i> gave us a two-dimensional view and models gave us a static 3D representation. Related information- reports, impact assessments, development strategies and the rest were created by the kilo then sealed in PDFs and only read by, well, nobody. My planning department experience was 30 years ago, and the stunning thing is the industry hasn't changed. This is still the way we do master planning. We have moved on through CAD and BIM, but the overall process is the same, still frustrated by the inaccessibility of information entombed in PDFs. The above is all the more disappointing given we are well into the 4th Industrial revolution, characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. This is where Digital Twins come into their own.</p><p>A simple definition of a digital twin is that is a digital model of a physical asset, which continuously collects information (via sensors, drones or other IoT and IIoT data collection tools) and applies advanced analytics, machine-learning and artificial intelligence (AI) to gain valuable real-time insights about the physical asset's performance, operation or profitability. In essence, you create a 3D model of a physical entity and populate it with data allowing you manage the physical entity but also to run scenario planning for predicative insight. 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More online meetings, less travel; more shared, flexible workspaces, fewer assigned physical spaces; more operational data collection via IOT sensors, less manual reporting; more AI-enabled analysis, less guesswork; more maintenance tasks performed by robots, less manual intervention. Building sensors will monitor the temperature of people both within and without the building and can tell if groups are forming without the concomitant social distancing, allowing messages to be sent asking that groups disperse. Apps can be used to identify and book desk and room slots before arrival in buildings and can track people and infection blooms allowing Authorities the ability to see the spread of contagion and respond accordingly.</p><p>Arguably, there is a recognised three-step plan to build successful advanced urban infrastructure in the 21st Century city. Firstly, through consultation, agree a set of open outcomes and time frame. 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International Financial Institutions such as the European Commission, World Bank, Asian Development Bank <i>et al.</i>, Sovereign Wealth Funds and National Governments have the funding and mandate but no unifying plan. 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引用次数: 7

摘要

在2019冠状病毒病之前,人们开始将气候变化作为先进城市数字化转型的总体目标。气候变化是一个邪恶的问题,没有灵丹妙药,但有一个领域对气候变化的负面影响比其他任何领域都大;城市。世界上只有29%的土地,城市目前占地球表面的3%,占地球表面的0.9%。建筑占据了每个城市70%到80%的面积,我们一生中87%的时间都在其中度过。建筑,这个地球上很小的一部分,消耗了世界上75%的电力,40%的全球能源,40%的温室气体排放,25%的全球水供应和40%的固体废物。随着越来越多的人出于经济、社会或冲突原因搬到城市,这个问题只会变得更糟。世界77亿人口中大约有50%生活在城市,预计到2050年将上升到70%;这将创造另外5000个城市。城市化速度最快的将是发展中国家,而发展中国家在处理污染、能源、空气质量、水资源短缺、废物、交通、健康和公民复原力等问题方面的能力最差。疫情对世界经济以及我们在城市生活和工作方式的影响已经取代了对气候问题的关注,但解决这两个问题的答案是,我们需要城市更智能地工作,为此我们需要更好地了解城市。在发达国家,现在有大量的技术进入市场。Proptech, Plantech, Digital twins, VR &;增强现实、分类账技术、5G、人工智能和深度学习、数据交换和边缘计算将影响公民参与、经济增长和物理基础设施,但我们也需要发展中国家的电力、水和连接等基础设施。目前,新的使能技术仍然被孤立在点解决方案中,公司围绕AI、proptech、Ledger等开发单一技术价值主张。无论我们对“智能”的定义是什么,市场正在向物联网平台成熟,硬件捕获数据,软件分析数据。为了使我们能够将数据转化为信息,从而使洞察产生影响,我们还需要以适当的方式共享信息,并以最容易获取的方式将其呈现出来。我们正在获取越来越多的数据,但我们与正确的制衡机构共享数据的能力存在问题。这种情况必须改变,对数据信任模型的需求越来越大,这些模型允许我们合成数据,以及数字孪生;在这里,我们创建了一个物理的虚拟复制品,并可以将实时信息输入到模型中,允许场景规划和软硬数据的网格化,从而创建围绕健康、福祉和流动性等领域的叙事。这利用了上述新的颠覆性技术,使城市当局能够灵活和明智地做出决策,同时促进公共和私营部门之间的信息共享。因此,它为实现技术创造了一个市场,同时为城市的增长提供了信息。很久以前,我在地方政府的规划部门工作时注意到的一件事是,如果我用语言来解释我想做的事情,我就会遇到面无表情和不感兴趣的人。然而,如果我制作了一个示意图,计划或地图,整个氛围就会改变。桌子被清理干净了,眼睛亮了起来,从前的冷漠变成了热情。建筑师、工程师和开发人员也会受到同样的影响。这些人是通过视觉来思考的。如今,同样的情况也出现在物联网的新魔法师身上;数据科学家和人工智能专家,这就是数字双胞胎既吸引人又有效的原因。我们创造了如此多的数据,其中大部分是二进制的,我们需要一种方法让它与我们对话。地图、图表等为我们提供了二维视图,而模型则为我们提供了静态的3D表示。相关信息——报告、影响评估、发展战略等等——都是由一群人创建的,然后封存在pdf文件中,只有——嗯,没有人读过。我在策划部门的经历是30年前的事了,令人惊讶的是这个行业并没有改变。这仍然是我们做总体规划的方式。我们已经通过了CAD和BIM,但整个过程是一样的,仍然因为pdf中隐藏的信息无法访问而感到沮丧。考虑到我们已经进入了第四次工业革命,以技术融合为特征,模糊了物理、数字和生物领域之间的界限,上述情况就更令人失望了。这就是数字双胞胎发挥作用的地方。 数字孪生的一个简单定义是,物理资产的数字模型,它不断收集信息(通过传感器、无人机或其他物联网和工业物联网数据收集工具),并应用高级分析、机器学习和人工智能(AI),以获得有关物理资产性能、运营或盈利能力的有价值的实时见解。本质上,您可以创建物理实体的3D模型,并用数据填充它,从而管理物理实体,还可以运行场景规划以获得预测性洞察力。现在,规划者、开发商、官员、政治家和公民都有了一个可访问的甲骨文,可以共享信息,为智能社区的未来做出贡献。这种跟踪人们如何在城市和建筑物中移动的新方法的重要性,是我们可以用来缓解Covid-19挑战的工具。福布斯最近的一篇文章预测,后冠状病毒时代的未来将包括更多的非接触式界面和互动,加强数字基础设施,更好地监控和使用物联网和大数据,支持人工智能的开发,以及更多地依赖机器人。简而言之,所有行业都将朝着虚拟化和数字化的方向发展,而数字孪生将为建筑行业的虚拟化和数字化铺平道路。更多的在线会议,更少的旅行;更多的共享、灵活的工作空间,更少的指定物理空间;通过物联网传感器收集更多的操作数据,减少人工报告;更多人工智能分析,更少猜测;更多的维护任务由机器人完成,更少的人工干预。建筑物传感器将监测建筑物内外人员的温度,并可以在没有伴随的社交距离的情况下判断群体是否正在形成,从而允许发送信息,要求群体分散。应用程序可用于在到达建筑物之前识别和预订办公桌和房间位置,并可以跟踪人员和感染爆发,使当局能够看到传染病的传播并做出相应的反应。可以说,在21世纪的城市中,有一个公认的三步走计划来建设成功的先进城市基础设施。第一,通过协商,商定一套公开成果和时间表。其次,弄清楚为了实现这些结果,人们需要做哪些不同的事情(通过哪些技术实现)。第三,定义什么是成功,并有能力衡量其中的差异。为了实现上述目标,你必须拥有可以转化为信息的数据,这些数据可以为你提供洞察力,从而使你能够做出具有实际影响的决策。为了成功实现这一点,您需要能够通过正确的治理和协议来合成信息和共享数据。有人认为,It企业未能引领智慧城市市场,是因为他们固守投资回报率(ROI)过短的过时商业模式,仍然专注于专有的点解决方案。相反,市场越来越多地由建筑、工程和施工公司(AEC)领导,这些公司拥有更长的投资回报率,有能力扮演主要承包商的角色,并在必要时引入电信、公用事业和IT,但不可抗力是我们需要先进的城市数字基础设施促进决策选择的可见性。总之,数字孪生不是万能的灵丹妙药,而是先进城市数字城市化成熟的一个组成部分,通常被称为“智慧城市”市场。我们正在通过物联网平台的开发创建基础数据,我们还没有创建数据交换,这将允许数据合成,这将最大限度地利用数字双胞胎和伴随的适合目的的投资回报率模型,这将使我们能够为初始和后续投资建立商业案例。那么,领导层将从何而来?欧盟委员会、世界银行、亚洲开发银行等国际金融机构、主权财富基金和各国政府有资金和授权,但没有统一的计划。也许Covid-19、气候变化和城市之间的关系是他们需要创建一个平台的燃烧平台。
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Smart cities in the time of climate change and Covid-19 need digital twins

Pre-Covid there was the beginnings of a coalescence around Climate Change as the overarching aim of advanced urban digital transformation. Climate change is a wicked problem with no silver bullet but there is one arena that adversely affects climate change more than any other; cities.

Only 29% of the world is land, cities currently occupy 3% of that representing 0.9% of the earth surface. Buildings occupy between 70 and 80% of every city and we spend 87% of our life in them. Buildings, a tiny percentage of the planet, consume 75% of world electricity, 40% of global energy, are responsible for 40% of the total GHG emissions, consume 25% of the global water supply and generate 40% of total solid waste.

The problem is only going to get worse as more people move to cities for economic, social, or conflict reasons. Roughly 50% of the world population of 7.7 billion people lives in cities and it is predicted to rise to 70% by 2050; this could create another 5000 cities. The greatest rise in urbanisation will take place in the developing world, which is the least well equipped to deal with issues of pollution, energy, air quality, water shortages, waste, transport, health and civil resilience. The focus on Climate has now been usurped by the effect Covid has had on the world economy and how we live and work in Cities, but an answer to both is we need cities to work smarter and to do that we need to understand them better.

In the developed world there is a plethora of technologies now reaching the market. Proptech, Plantech, Digital twins, VR & AR, Ledger technologies, 5G, AI and Deep Learning, Data Exchanges and Edge Computing that will shape citizen engagement, economic growth and physical infrastructure, but we also need the basic infrastructure of power, water and connectivity in the developing world. Currently, the new enabling technologies are still siloed into point solutions with companies developing single technology value propositions around AI, proptech, Ledger et al. Whatever our working definition of what comprises ‘smart’, the market is maturing into IoT platforms where hardware captures data and software analyses it. To enable us to turn data into information allowing insight to inform impact we also need to share information in an appropriate way and surface it in the most accessible manner possible. We are capturing ever-increasing amounts of data, but our ability to share it with the correct checks and balances is problematic. This will have to change and there is an increasing need for Data Trust models that allow us to synthesise data, and Digital Twinning; where we create a virtual replica of the physical and can feed real time information into the model allowing scenario planning and the meshing of soft and hard data that creates a narrative around arenas such as Health, Wellbeing and Mobility. This leverages the new disruptive technologies mentioned above, allowing city authorities agile and informed decision making while facilitating the sharing of information between the public and private sectors. As such, it creates a market for enabling technologies while informing growth in the city.

One of the things I noticed when working in the planning department of a local authority in the distant past was that if I used words to explain something I wanted to do, I would be met with blank faces and disinterest. However, if I produced a schematic, plan or map the whole atmosphere changed. Tables were cleared, eyes lit up, erstwhile disinterest turned into enthusiasm. You get the same affect with architects, engineers and developers. These are people who think visually. Nowadays, the same can be seen with the new sorcerers of IoT; data scientists and AI specialists and is the reasons why Digital Twins are both attractive and effective.

We create so much data, most of which is binary, we need a way to make it talk to us. Maps, charts et al. gave us a two-dimensional view and models gave us a static 3D representation. Related information- reports, impact assessments, development strategies and the rest were created by the kilo then sealed in PDFs and only read by, well, nobody. My planning department experience was 30 years ago, and the stunning thing is the industry hasn't changed. This is still the way we do master planning. We have moved on through CAD and BIM, but the overall process is the same, still frustrated by the inaccessibility of information entombed in PDFs. The above is all the more disappointing given we are well into the 4th Industrial revolution, characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. This is where Digital Twins come into their own.

A simple definition of a digital twin is that is a digital model of a physical asset, which continuously collects information (via sensors, drones or other IoT and IIoT data collection tools) and applies advanced analytics, machine-learning and artificial intelligence (AI) to gain valuable real-time insights about the physical asset's performance, operation or profitability. In essence, you create a 3D model of a physical entity and populate it with data allowing you manage the physical entity but also to run scenario planning for predicative insight. You now have an accessible oracle for planners, developers, officials, politicians and citizens to share information and contribute to the future of smart communities. The importance of this new way of tracking how people move through cities and buildings is a tool we can use to ameliorate the challenges of Covid-19. A recent Forbes article predicted that a post-coronavirus future will include more contactless interfaces and interactions, strengthened digital infrastructure, better monitoring and use of IoT and Big Data, AI-enabled development, and an increased reliance on robots. Put simply, the trend will be towards virtualization and digitalization in all industries, and Digital Twin-making will pave the road to virtualization and digitalization in the building industry. More online meetings, less travel; more shared, flexible workspaces, fewer assigned physical spaces; more operational data collection via IOT sensors, less manual reporting; more AI-enabled analysis, less guesswork; more maintenance tasks performed by robots, less manual intervention. Building sensors will monitor the temperature of people both within and without the building and can tell if groups are forming without the concomitant social distancing, allowing messages to be sent asking that groups disperse. Apps can be used to identify and book desk and room slots before arrival in buildings and can track people and infection blooms allowing Authorities the ability to see the spread of contagion and respond accordingly.

Arguably, there is a recognised three-step plan to build successful advanced urban infrastructure in the 21st Century city. Firstly, through consultation, agree a set of open outcomes and time frame. Secondly, work out what people will have to do differently (enabled by what technology) to achieve those outcomes. Thirdly, define what success looks like and have the ability to measure the difference. To make the above work you must have data that you can turn into information, giving you insight so you can make decisions with real impact. For that to happen successfully you need to be able to synthesise information and share data through the right governance and protocols.

It can be argued that IT companies have failed to lead the smart cities market because they are wedded to outdated business models where the return on investment (ROI) is too short and still focus on proprietary point solutions. Instead, the market is increasingly led by the Architecture, Engineering and Construction companies (AEC) who have a longer ROI, the ability to take a lead contractor role and bring in Telco, Utilities and IT as, and when, required but the force majeure is that we need visibility of decision making options facilitated by advanced urban digital infrastructure.

In conclusion, Digital twins are not a universal panacea but an integral part of the maturation of Advanced Urban Digital Urbanisation colloquially described as the ‘smart city’ market. We are creating the base data through the development of IoT platforms, we have yet to create Data exchanges that will allow for data synthesis that will bring the most out of Digital Twins and concomitant fit for purpose ROI models that would allow us to build the business case for initial and subsequent investment.

So where will the leadership come from? International Financial Institutions such as the European Commission, World Bank, Asian Development Bank et al., Sovereign Wealth Funds and National Governments have the funding and mandate but no unifying plan. Perhaps the relationship between Covid-19, climate change and cities is the burning platform they need to create one.

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来源期刊
IET Smart Cities
IET Smart Cities Social Sciences-Urban Studies
CiteScore
7.70
自引率
3.20%
发文量
25
审稿时长
21 weeks
期刊最新文献
Guest Editorial: Smart cities 2.0: How Artificial Intelligence and Internet of Things are transforming urban living Smart city fire surveillance: A deep state-space model with intelligent agents Securing smart cities through machine learning: A honeypot-driven approach to attack detection in Internet of Things ecosystems Smart resilience through IoT-enabled natural disaster management: A COVID-19 response in São Paulo state Optimising air quality prediction in smart cities with hybrid particle swarm optimization-long-short term memory-recurrent neural network model
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