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.

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.

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.

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:

• 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.
• 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.
• 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.
• 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.
• Cloud-based IoT applications are usually incorporated into some objects like mobile devices, tablets, as well as connected vehicles and offices.
• Blockchain. It secures data flow and makes all the processes transparent.
• Geospatial Technology. Another technology that enhances the capabilities of smart cities. Geolocation allows us to better track and locates needed devices.

All this helps to receive, analyze, and manage data in real-time to help people understand better various processes within their city.

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:

#1 Automated Video Object Detection Algorithms

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.

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.

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.

#2 Smart parking applications

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.

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.

#3 Autonomous Flying Objects

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.

#4 Face Detection Cameras and Movement for Public Safety

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.

#5 IoT solutions to manage waste smartly

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.

#6 Predicting the infection outbreaks & post-COVID life management

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:

• 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.
• 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.
• 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.

#7 Augmenting Workforce Knowledge and Skills

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.

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.

#8 Reducing Air Pollution

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.

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.

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.

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:

New York

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.

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.

Amsterdam

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.

Copenhagen

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.

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.

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.

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.

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.

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Original post: https://towardsdatascience.com/smart-cities-applications-of-artificial-intelligence-in-urban-management-c445c414c8eb