人工智能城市和智慧城市
Smart cities aren’t just sci-fi or cyberpunk dreams, but an actual solution based on Artificial Intelligence and the Internet of Things. But the question is, what is the mechanism that put it all in action? How far away humanity is from a futuristic picture of smart cities we saw in movies? To answer this question, I decided to shed some light on the current state of things for anyone interested both in existing possibilities and solutions we can track in the foreseeable future.
智慧城市不仅是科幻或计算机朋克的梦想，而且是基于人工智能和物联网的实际解决方案。 但是问题是，什么将其付诸实践？ 人类与电影中看到的智慧城市的未来主义景象相距多远？ 为了回答这个问题，我决定向任何对我们在可预见的将来可以追踪的现有可能性和解决方案感兴趣的人提供一些当前状况。
什么是智慧城市？ 我们为什么需要它？ (What Is A Smart City? Why Do We Need It?)
For better or for worse, smart cities nowadays are less about flying cars, robots selling coffee, or other flashy visions from science fiction. And although we have to go through a long way to achieve stuff like this, now we have no less impressive solutions that became possible thanks to data analysis and sensors to gather all the data.
不管是好是坏，如今的智慧城市都不再像飞行汽车，出售咖啡的机器人或科幻小说中其他浮华的愿景。 尽管我们必须走很长一段路才能实现这样的目标，但是由于数据分析和传感器可以收集所有数据，因此我们现在拥有了同样令人印象深刻的解决方案。
Why is the end value of smart cities? Smart cities aim to solve the negative effects caused by urbanization and make urban lives better. Since there are lots of issues connected with urbanization that is growing exponentially, smart cities can solve a variety of problems like energy distribution, trash collection, consumption of food, energy, water, traffic jam, crime and other consequences of social deprivation.
为什么智慧城市的终极价值？ 智慧城市旨在解决城市化带来的负面影响，并改善城市生活。 由于与城市化相关的许多问题正在成倍增长，因此智慧城市可以解决各种问题，例如能源分配，垃圾收集，食品消耗，能源，水，交通拥堵，犯罪和其他社会剥夺后果。
技术方面：什么是用于城市管理的AI？ (Technical side: What is AI for Urban Management?)
It is not a secret, behind smart cities the central role is played by Artificial Intelligence, wireless networks, and other communication mediums. If you are interested to know in more detail what does it mean, here are key takeaways of the technology behind smart cities:
这并不是秘密，在智慧城市背后，人工智能，无线网络和其他通信媒介扮演着核心角色。 如果您想更详细地了解这意味着什么，那么以下是智慧城市背后的主要技术摘要：
Information and Communication Technology (ICT). Roughly speaking, it is a more general network that connects many devices and serves as a leading bridge between the inhabitants and consumers of certain services and the city administration.
信息和通信技术(ICT)。 粗略地说，它是连接许多设备的更通用的网络，并充当某些服务的居民和消费者与城市管理部门之间的桥梁。
Internet of Things. IoT represents the world of connectivity. IoT is responsible for combining different devices and sensors under one umbrella to transmits the desired signals through sensors and contemplate needed scenarios.
物联网。 物联网代表了连通性的世界。 物联网负责将不同的设备和传感器组合在一起，以通过传感器传输所需的信号并考虑所需的场景。
Sensors. Data transmitters that serve as small elements in a large and innovative smart city system. The sensors record the information in various forms and send this data to the appropriate servers.
传感器。 数据发送器，在大型创新型智能城市系统中仅用作小型元素。 传感器以各种形式记录信息并将该数据发送到适当的服务器。
Artificial Intelligence. AI, at its core, is powered by algorithms. For smart cities, various sensors collect data and pump it through AI and ML algorithms to find patterns. All insights amassed from data can be employed for tasks that allow machines to mimic what humans might consider being intelligent. Put it more simply, AI helps to make sense of the massive amount of data generated by devices.
人工智能。 AI的核心是算法。 对于智慧城市，各种传感器会收集数据并通过AI和ML算法将其泵送以查找模式。 从数据中收集的所有见解都可以用于允许机器模仿人类认为是聪明的东西的任务。 简而言之，人工智能有助于理解设备生成的大量数据。
Cloud-based IoT applications are usually incorporated into some objects like mobile devices, tablets, as well as connected vehicles and offices.
通常将基于云的物联网应用程序集成到某些对象中，例如移动设备，平板电脑以及连接的车辆和办公室。
Blockchain. It secures data flow and makes all the processes transparent.
区块链 它可确保数据流的安全并使所有过程透明。
Geospatial Technology. Another technology that enhances the capabilities of smart cities. Geolocation allows us to better track and locates needed devices.
地理空间技术。 增强智慧城市功能的另一项技术。 地理位置使我们能够更好地跟踪和定位所需的设备。
All this helps to receive, analyze, and manage data in real-time to help people understand better various processes within their city.
所有这些都有助于实时接收，分析和管理数据，以帮助人们更好地了解城市中的各种流程。
5 AI在智慧城市中的变革性应用 (5 Transformative Applications of AI in Smart Cities)
What are the real cases and examples of AI-powered technologies behind urban management? Here are some of the most vivid and developed applications up to this moment:
城市管理背后的人工智能技术的真实案例和实例是什么？ 这是到目前为止最生动，最先进的应用程序：
#1 Automated Video Object Detection Algorithms
＃1自动视频对象检测算法
Video-object detection is the first reason why the concept of smart cities attracts attention and admiration. What does it mean and how it works? Video cameras with special sensors can track various patterns, combinations of movements, and in general what is happening and thus signal any deviations from the norm. For example, during festivals, such cameras can immediately report terrorist acts, signs of violence.
视频对象检测是智慧城市概念引起关注和钦佩的首要原因。 它是什么意思，如何运作？ 带有特殊传感器的摄像机可以跟踪各种模式，动作组合以及通常发生的情况，从而发出任何偏离规范的信号。 例如，在节日期间，此类摄像机可以立即报告恐怖行为，暴力迹象。
Besides, such technologies can be used differently. For example, by gathering data from various areas of the municipality, it may later be more comfortable for the police to analyze which areas need more attention. That is, roughly speaking, this theft will make it clear the number of criminal cases.
此外，可以不同地使用这种技术。 例如，通过从市政当局的各个区域收集数据，以后警方可能更愿意分析哪些区域需要更多注意。 也就是说，从粗略讲，这种盗窃行为将使刑事案件的数量更加明确。
An example of such an application is the closed-circuit TV (CCTV) system. Ono more vivid case is Canon cloud-based video analytics service in SG. All-in-all, such video-object detection systems are based on AI object detection and face recognition mechanisms to perform tasks including learning patterns in an area; detecting faces, gender, heights, and moods; reading license plates; and identifying anomalies or potential threats, such as unattended packages.
这种应用的一个例子是在闭路电视 (CCTV)系统。 更为生动的案例是SG中基于佳能云的视频分析服务 。 总体而言，此类视频对象检测系统基于AI对象检测和面部识别机制来执行任务，其中包括区域中的学习模式。 检测面部，性别，身高和情绪； 阅读车牌； 并识别异常或潜在威胁，例如无人看管的包裹。
#2 Smart parking applications
＃2智能停车应用
The problem with a huge number of cars on the roads is crucial for every city. But vehicle parking and traffic management is another space where AI can help. Connected vehicles can interact with parking measures and electric vehicle (EV) charging docks and so direct drivers to the most proximal spot. The mechanism here is simple: with the help of sensors built into parking spots, a real-time map of car traffic is formed.
对于每个城市而言，道路上大量汽车的问题至关重要。 但是，停车场和交通管理是AI可以提供帮助的另一个空间。 联网车辆可以与停车措施和电动汽车(EV)充电站相互作用，因此可以将驾驶员引导到最靠近的位置。 此处的机制很简单：借助内置在停车位中的传感器，可以形成汽车行驶的实时地图。
The function here is only one — to record the movement of the vehicles and show the driver free spaces for further progress, which helps tremendously to understand right from the start where it is possible to park a car. The most interesting thing is that these sensors can be used in different ways and for complex situations. For instance, during rush hour, such a system can immediately show a free seat and help the driver to reserve this place for himself.
这里的功能仅仅是一个功能-记录车辆的行驶并向驾驶员显示自由空间以供进一步行驶，这从一开始就极大地帮助您了解可以停车的地方。 最有趣的是，这些传感器可以以不同的方式用于复杂的情况。 例如，在高峰时段，这样的系统可以立即显示一个自由座位，并帮助驾驶员为自己预留这个位置。
#3 Autonomous Flying Objects
＃3自主飞行物
Smart Cities initiatives envision drones as autonomous vehicles transporting goods from one hub to another, as well as from hubs to consumers. There are already good examples of drones developed by Uber, Hyundai, and more. Flying drones can help when there is a need to observe a certain part of the city. It is also possible to involve object detection or facial recognition approaches to identify needed patterns and transmit signals to the appropriate people.
智慧城市计划设想将无人机作为自动驾驶汽车将货物从一个枢纽运输到另一个枢纽，以及从枢纽运输到消费者。 由Uber，现代等公司开发的无人机已经有很好的例子。 当需要观察城市的某个部分时，飞行无人机可以提供帮助。 还可能涉及物体检测或面部识别方法，以识别所需的模式并将信号传输给适当的人。
#4 Face Detection Cameras and Movement for Public Safety
＃4面部检测摄像头和移动装置，以确保公共安全
This application in smart cities follows from the previous one. So in fact, by identifying faces, movements, objects, you can collect a lot of insights from the data. Whether it is a photo or a video, we can develop Video Content Analytics solutions to identify and track persons. For example, if the police are unable to locate a missing offender, face recognition and systems that use this technology can alert the missing person quickly.
智慧城市中的这一应用是前一个应用的继任者。 因此，实际上，通过识别面Kong，动作和物体，您可以从数据中收集很多见解。 无论是照片还是视频，我们都可以开发视频内容分析解决方案来识别和跟踪人员。 例如，如果警察无法找到失踪者，则面部识别和使用该技术的系统可以Swift提醒失踪者。
#5 IoT solutions to manage waste smartly
＃5物联网解决方案可智能管理废物
One more application that solves important problems. Smart waste solutions like Sensoneo can detect trash thrown on various paces and even recognize the types of garbage for categorization. By the way, this system managed to save over 30% of waste collection costs. Another example of smart solutions for waste management is Urbo that it not only works with real-time data from sensors but also from geospatial solutions and machine learning, in which, for example, the system interprets data through learning.
解决重要问题的另一个应用程序。 诸如Sensoneo之类的智能废物解决方案可以检测各种速度的垃圾，甚至可以识别分类的垃圾类型。 顺便说一下，该系统设法节省了30％以上的废物收集成本。 废物管理智能解决方案的另一个例子是Urbo ，它不仅可以处理来自传感器的实时数据，还可以处理地理空间解决方案和机器学习的数据，例如，系统通过学习来解释数据。
#6 Predicting the infection outbreaks & post-COVID life management
＃6预测感染爆发和COVID后的生活管理
Another important use case is becoming a reality thanks to smart cities and AI, which has a chance to help humanity. From the very beginning of rising pandemic caused by COVID-19, lots of solutions to detect viruses raised. Here are some of them that are widely used in smart cities:
得益于智慧城市和人工智能，另一个重要的用例正在成为现实，这有机会帮助人类。 从COVID-19引起的大流行开始，就已经提出了许多检测病毒的解决方案。 以下是在智慧城市中广泛使用的一些工具：
Remote temperature monitoring systems. There are many variations of technologies that can measure body temperature remotely. For example, in China, there are smart helmets that immediately signal a rise in temperature in a crowd. In addition, there are other options for measuring temperature that does not even have contact with the body.
远程温度监控系统。 可以远程测量体温的技术有很多种。 例如，在中国，有智能头盔会立即发出信号，提示人群温度升高。 另外，还有其他选项甚至可以测量温度，而这些温度甚至不会与人体接触。
Predicting outbreaks. These are a variety of systems that read data on public health and make predictions about whether there will be an outbreak of an epidemic or not. For example, a system called BlueDot made this prediction a weak prior to the coronavirus spread from Wuhan around the world.
预测爆发。 这些系统可以读取公共卫生数据，并预测是否会爆发流行病。 例如，在冠状病毒从武汉扩散到世界各地之前，一个名为BlueDot的系统使该预测很弱。
Social distancing control. Another possibility of artificial intelligence is to measure the social distance between the population and to notify in case of non-compliance with safety rules during a coronavirus pandemic. For example, in Singapore, there is such a system called SafeDistancer.
社会疏远控制。 人工智能的另一种可能性是测量人群之间的社会距离，并在冠状病毒大流行期间不遵守安全规定的情况下进行通知。 例如，在新加坡，有一个名为SafeDistancer的系统。
#7 Augmenting Workforce Knowledge and Skills
＃7增强员工的知识和技能
The US Energy Department stated: 25% of workers are expected to retire within five years, and for newcomers who have no prior experience in certain realms will be impossible to do the same work at the same pace. It will take years to absorb all the previous knowledge. But AI promises to accelerate this process. Thanks to Natural Language Processing (NLP) and pattern recognition, we can build systems that will extract valuable information from past internal communications, training documents, and more.
美国能源部表示：预计25％的工人将在五年内退休，而对于那些在某些领域没有经验的新移民来说，将不可能以相同的速度完成相同的工作。 吸收所有以前的知识将需要数年时间。 但是，人工智能有望加快这一进程。 借助自然语言处理 (NLP)和模式识别 ，我们可以构建可以从过去的内部通信，培训文档等中提取有价值信息的系统。
For example, IBM has already provided a ready-made system called Maximo Equipment Maintenance Assistant, which explores knowledge from previous employees and allows newcomers to keep abreast of the most subtle nuances. The undoubted advantage of this system is that it provides recommendations on how best to solve problems of various complexity.
例如，IBM已经提供了一个名为Maximo Equipment Maintenance Assistant的现成系统，该系统可以探索以前员工的知识，并允许新来者及时了解最细微的差别。 该系统的优点无疑在于，它提供了有关如何最好地解决各种复杂问题的建议。
#8 Reducing Air Pollution
＃8减少空气污染
Just like famous Greta Thunberg stated: if we do not take steps to control greenhouse gas (GHG) emissions now, we will face a global catastrophe in the future. But fortunately, now, thanks to smart cities and the use of AI to reduce energy waste, pollution of the earth, water, and air, we can easily prevent this problem. By the way, this is quite possible, according to statistics, already developed technologies can reduce greenhouse gas emissions by at least 4% in 2030. But progress does not stand still, and maybe this number will be even higher.
就像著名的Greta Thunberg所说：如果我们现在不采取措施控制温室气体(GHG)的排放，将来我们将面临全球灾难。 但是幸运的是，现在，由于有了智慧城市和AI的使用，减少了能源浪费，对地球，水和空气的污染，我们可以轻松地预防此问题。 顺便说一下，据统计，这是完全有可能的，到2030年，已经开发的技术可以减少至少4％的温室气体排放。但是进展不会停滞不前，也许这个数字还会更高。
Among the existing implementations of this task, there are vivid examples in Singapore, a rather advanced city in terms of technology. There, AI and IoT are used to continually collect information about air, pollution, temperature, etc. Then, data analysis lets the city administration know which territories require the fastest intervention and prevention from pollution.
在此任务的现有实现中，新加坡是一个生动的例子，新加坡在技术上是一个相当先进的城市。 在那里，人工智能和物联网用于不断收集有关空气，污染，温度等方面的信息。然后，数据分析使市政府知道哪些区域需要最快的干预和预防污染。
Besides, there is another example from the well-known company IBM. The company is currently testing a new system that can reduce the severity of air pollution in Beijing by analyzing data from coal plants, industrial complexes, weather conditions, and traffic jams. This system is worth attention because, in addition to analysis, it is also designed to give recommendations on what measures can be taken to improve the situation.
此外，还有著名公司IBM的另一个例子。 该公司目前正在测试一种新系统，该系统可以通过分析来自燃煤电厂，工业园区，天气状况和交通拥堵的数据来降低北京的空气污染严重性。 该系统值得关注，因为除了分析之外，它还旨在就可以采取哪些措施改善这种情况提供建议。
智慧城市的一些最聪明的例子 (Some of the brightest examples of smart cities)
There a lot of smart cities that are growing rapidly, and every year their number becomes even bigger. Here are the cities that I found to be the most interesting one up to this moment:
有许多智慧城市正在Swift发展，并且每年的数量都在增加。 以下是到目前为止我发现最有趣的城市：
New York
纽约
New York isn’t just the most well-known smart city, but one of the most developed ones. One of the brightest examples of applications used there is LinkNYC — project to create a network covering several cities with free Wi-Fi service for access to city services, maps, and directions. One more AI-based application is Cyber NYC, a solution to grow the cybersecurity matters.
纽约不仅是最著名的智能城市，而且是最发达的城市之一。 LinkNYC是使用的最出色的应用程序示例之一，该项目旨在创建一个覆盖多个城市的网络，并提供免费的Wi-Fi服务以访问城市服务，地图和路线。 Cyber NYC是另一个基于AI的应用程序，它是解决网络安全问题的解决方案。
Quite expectedly, there are a variety of systems helping to tackle problems with water quality and conservation, public safety, and waste management. For instance, heating programs that are switching users from oil to natural gas have reduced the city’s sulfur dioxide emissions by more than 70% since 2008.
可以预见，有各种各样的系统可以帮助解决水质和节约，公共安全和废物管理方面的问题。 例如，自2008年以来，通过供暖计划将用户从石油转换为天然气，该市的二氧化硫排放量减少了70％以上。
Amsterdam
阿姆斯特丹
Started booming in 2009, Amsterdam’s smart city has grown very quickly, and up to date, there is over 200 active projects. The most astonishing application of AI is a system for boat delivery called ‘roboats’ that help to manage boats in timely manner. Besides, there are systems that tackle problems connected with environmental issues like overconsumption, overpopulation, global warming, and more. For this, Amsterdam developed its own City Data and made it open source. You can search, download, collect, and manage needed data just as you want to, let’s say, for boosting your own project.
阿姆斯特丹的智慧城市从2009年开始蓬勃发展，发展Swift，迄今为止，已有200多个活跃项目。 AI的最令人惊讶的应用是一种称为“ roboats ”的船只交付系统，该系统有助于及时管理船只。 此外，还有一些系统可以解决与环境问题相关的问题，例如过度消费，人口过剩，全球变暖等等。 为此，阿姆斯特丹开发了自己的城市数据并将其开源 。 可以说，您可以搜索，下载，收集和管理所需的数据，以增强自己的项目。
Copenhagen
哥本哈根
Another smart city that is worth attention is Copenhagen. One of the city’s most high-profile developments is a bicycle parking system, which Copenhagen has made a reality in collaboration with the Massachusetts Institute of Technology (MIT). In addition, the city has many other data collection systems: traffic is monitored and regulated in real-time reducing CO2 emissions. Sensors monitor water, air, noise, weather, waste, and condition of the sewer system.
另一个值得关注的智慧城市是哥本哈根。 该市最引人注目的发展之一是自行车停车系统，哥本哈根与麻省理工学院(MIT)合作实现了这一系统。 此外，该市还有许多其他数据收集系统：实时监控交通状况，减少二氧化碳排放量。 传感器监视水，空气，噪声，天气，废物和下水道系统的状况。
下一步是什么？ (What’s Next?)
How urban management can be changed in the short and long-termed perspective? The development of sensors, wireless networks, web, and mobile applications takes effort and investments to obtain needed results. But, already AI’s potential to transform urban spaces is quite promising.
从短期和长期的角度来看，城市管理如何改变？ 传感器，无线网络，Web和移动应用程序的开发需要付出努力和投资才能获得所需的结果。 但是，人工智能在改变城市空间方面的潜力已经十分可观。
Right now, we have great applications based on video-object detection, traffic management systems, autonomous flying objects, face detection cameras, smart waste systems, and more. The future looks even brighter. According to PRNewswire, the estimation of overall market of smart cities will equal $2.57 trillion by 2025, increasing at a clip of 18.4% per year on average.
目前，我们在视频对象检测，交通管理系统，自主飞行的对象，面部检测摄像头，智能垃圾处理系统等方面拥有出色的应用程序。 未来看起来更加光明。 根据PRNewswire的数据 ，到2025年 ，智慧城市的整体市场规模将达到2.57万亿美元，平均每年以18.4％的速度增长 。
To sum it up I want to say that smart cities can solve problems of various kinds. First of all, we are facing global urbanization, which means we need to improve urban lives as soon as possible. And if leaning on Cisco estimation, smart cities can improve their energy efficiency by 30% within 20 years. That’s why smart cities can be not just innovative but necessary steps for many in the foreseeable future.
综上所述，我想说的是，智慧城市可以解决各种问题。 首先，我们正面临全球城市化，这意味着我们需要尽快改善城市生活。 如果根据思科的估计，智慧城市可以在20年内将其能源效率提高30％ 。 因此，在可预见的将来，智慧城市不仅可以创新，还可以成为许多人的必要步骤。
But at the same time, I think we shouldn’t forget about security. We can reap benefits from smart cities if we can trust all the technologies behind them. In case when various citizens are sharing information, there should be advanced solutions against hacking-attacks and data theft. This means, data collected, stored, and analyzed should be confident. To obtain these security core goals, we should think about the integration of strong authentication and ID control solutions.
但同时，我认为我们不应忘记安全性。 如果我们可以信任智慧城市背后的所有技术，便可以从中受益。 如果各种公民共享信息，则应该有针对黑客攻击和数据盗窃的高级解决方案。 这意味着收集，存储和分析的数据应充满信心。 为了获得这些安全核心目标，我们应该考虑将强大的身份验证和ID控制解决方案集成在一起。
……………………………………….…
…………………………………………
If you want to dive more into the world of AI, ML & Data Science, welcome to my Instagram and Medium blog, where I share useful posts on cutting-edge technologies.
如果您想更深入地研究AI，ML和数据科学领域，欢迎访问我的 Instagram 和 Medium 博客，我在其中分享了有关前沿技术的有用文章。
You can also find me on Linkedin, and in case you are connected with SAP, welcome to my SAP S4 Hana channel on Telegram.
您也可以在 Linkedin 上找到我 ，如果您与SAP连接，请访问 Telegram上的 SAP S4 Hana频道 。
Let’s grow together!
让我们一起成长！
翻译自: https://towardsdatascience.com/smart-cities-applications-of-artificial-intelligence-in-urban-management-c445c414c8eb
人工智能城市和智慧城市