A look ahead: Data-Driven Cities

This is a repost from the official Pictures of the Future Siemens post. You can find the original article located here. 

We live in an age of urbanization. For the past ten years or so, more than half of the world’s population has lived in cities. Moreover, there’s no end in sight for this migration of people to urban areas. On the contrary, the latest UN forecast predicts that 70 percent of the world’s population will be living in cities by 2050. At that point, the world’s total urban population will be almost equal to the earth’s entire population today. Within a mere century, the number of people living in big cities will have grown from one billion to almost six billion. This trend will also lead to the rise of more and more megacities — cities that have more than ten million inhabitants. Whereas there were 28 megacities in 2014, there are expected to be 41 by 2030. Demands on infrastructures are expected to grow accordingly. Smaller cities are also expected to grow considerably. In 2016 there were about 500 cities with more than one million inhabitants; by 2030 there could well be more than 650.

Many cities are already suffering from housing shortages, overstretched infrastructures, and uncertain water and energy supplies. Added to this is the increasing risk of natural disasters resulting from climate change. Emissions from big cities, in particular from the transportation sector, are contributing considerably to this development. According to recent studies, the most effective low-carbon strategy would be to electrify this sector. Some areas are already trending in this direction. However, if the rise in global temperatures is to be kept to less than two degrees Celsius, 90% of all road vehicles would have to be electric by 2060.

The possibility that urban environments may deteriorate as a result of weather changes is a major threat. The aim in many cities is therefore to set the stage for clean air instead of smog; incentivize electric mobility instead of congested roads, and promote clean drinking water and affordable electricity from renewable sources that is available when it is needed, instead of expensive or “dirty” energy produced from fossil fuels.

As more and more cities move toward these goals, they will rely increasingly on digital resources that will, for example, monitor emissions figures and traffic density and coordinate local public transportation and traffic light switching times with monitoring results. Ultimately, they will also use digital technologies to inform individuals about the best ways to reach their destinations, regardless of whether they are driving their own vehicles, sharing cars, using a public transport system, or combining transport modes.

The effects are surprising. A recent study from Siemens – which will be published on July 4 in cooperation with Arup and supported by Londons Deputy Mayor for Business, looking at the capital of the UK as a business case for smart cities – states that on-street smart parking management for the Arc of Opportunity area in the eastern part of the city could save Drivers who are looking for parking spaces 33,000 hours in the car. Applying these savings to an economic valuation of time savings leads to total indirect benefits of € 870,000.

The first step toward making a city smart is to increase knowledge regarding the operations of its infrastructures ranging from water and energy management to traffic, air quality and lighting. In every big city, innumerable sensors and meters collect data from these and other sources. The challenge that cities face is thus to turn this avalanche of data into actionable information.

Answers as to how this can be done are provided by smart software. For example, the City Performance Tool (CyPT) from Siemens. It gives guidance to a city on how to achieve their environmental targets while providing an indication on how each infrastructure-related decision will influence job creation and the infrastructure sector growth.

However, many other software programs consist of more complex systems known as neural networks. Neural networks are computer models that operate in a way that is similar to the human brain. They can be trained to recognize interrelationships and use this knowledge to make forecasts.

One example of the fascinating results that are possible with neural networks is software that was developed by Ralph Grothmann from Siemens Corporate Technology (CT). The software can precisely predict the level of air pollution in major cities several days in advance.

Precise forecasts that are based on recorded data are at the heart of almost all smart city solutions. Such forecasts will enable smart grids to offset fluctuations in the electricity supply that are caused by changing weather conditions. A step in this direction is already taking shape as fleets of electric cars are integrated into building management systems so that the vehicles can serve as energy storage devices.

The future of smart cities will be shaped by the Internet of Things as a networking technology and by smart data as a forecasting technology. For example, it will be possible to coordinate power generation and power demand more precisely than ever before. This development will make increasing decentralization manageable, merge the markets for heating and electricity, and integrate industrial facilities, buildings, and vehicles as energy suppliers.

One step in this direction is offered by MindSphere, an open, cloud-based IoT operating system from Siemens that offers both connectivity and a range of industrial applications so that any enterprise, regardless of industry or size, can begin analyzing data to optimize their operations. Similarly cities and infrastructure operators can develop IoT applications to relieve traffic congestion, conserve water and energy and improve infrastructure services.

This will open up completely new markets for technologies and services. A McKinsey report from 2016 estimates that a total of $49 trillion will have to be invested in infrastructure projects worldwide between 2016 and 2030 in order to simply buttress expected economic growth rates. This averages out to $3.3 trillion per year, or about 3.8% of worldwide GDP (based on an average GDP increase of 3.3% per year). Approximately 60 percent of these investments would have to be made in emerging markets. This trend is causing the global market for smart city solutions to grow. According to Navigant Research, this market will grow by 10 percent annually, from $40 billion in 2017 to $98 billion in 2026.

Cities and their residents can be linked together in networks that have the potential for optimizing not only energy use, but transportation, logistics, medical information, entertainment, and much more. Ultimately, however, all of these services are based on data — and that raises concerns about a “big brother” state. Will tomorrow’s cities be the world of George Orwell’s 1984? Not at all, says Gerhard Engelbrecht,expert in intelligent information and communications technology (ICT) at Siemens Corporate Technology.  He heads the Smart ICT topic in the Aspern urban lakeside development project in Vienna, where more than 100 households are taking part in the research and making their data on power consumption, air quality and room temperature available. “We are aware of this sensible topic and have designed the system accordingly, that only anonymized and aggregated information can be used for research” says Engelbrecht reassuringly.

What will it take to make cities smarter and increasingly livable? On the one hand, says Carlo Ratti, an architect, engineer, and professor at MIT’s Department of Urban Studies and Planning, cities won’t look much different in the future than they do today — in the same way that Roman cities didn’t differ that much from modern ones. “What will change, however, is the way we experience cities,” says Ratti. He believes that this change will be due to the comprehensive use of digital technologies. These technologies have already been introduced into all areas of cities over the past ten years, and they now form the backbone of a large intelligent infrastructure. According to Ratti, our cities are increasingly turning into “open-air computers.”