By DC Member Dr Daniel Trauth*

The United Nations estimates that over 60 per cent of the world's population will live in cities by 2030, and that by 2050, it will be about two-thirds. The challenges associated with this concentration are enormous and can only be overcome by smart cities. The aim is to provide municipalities with smart systems that improve the service provided to citizens while also reducing costs.

Connecting AI with the real world

The focus here is on connecting artificial intelligence (AI) with the real world, from traffic management to parking space monitoring and intelligent energy networks to waste management. Many municipalities focus too heavily on improvements in computer networking in public administration and neglect the real world.

According to some estimates, the average citizen in Germany comes into contact with a public office three to ten times a year. But they are out and about on the streets every day, the rubbish is collected several times a week, and hopefully the energy supply is uninterrupted. Therefore, the ‘smartification’ of communities must extend far beyond public administration.

Smart cities do not have to be just large cities. Often, medium-sized and small towns are ahead of the metropolises because the decision-making processes are shorter and a top-down approach works better.

The urgency of making our cities smarter is illustrated by the figures. Today, cities already account for around 70 per cent of global energy consumption, although they only cover five per cent of the Earth's land mass. This is associated with a steadily increasing urban demand for water, land, building materials, food, measures to reduce air pollution and waste management. Cities are under constant pressure to provide better services, increase efficiency, reduce costs, increase effectiveness and productivity, and counteract infrastructure overload and environmental pollution. These challenges can only be met with smart city concepts.

Trend towards conurbations

For the first time in human history, more people have been living in conurbations than in rural areas since 2008. In Germany, for example, young people in particular are migrating from rural areas in about half of all 402 districts and urban districts. Young people are now in the minority in rural areas. The exodus is driven less by unemployment or a lack of jobs than by the experience of pubs and cinemas closing and more and more friends leaving. It is likely that growth in urban centres in the first three decades of the 21st century will exceed the cumulative urban expansion in human history.

Intelligent infrastructures as a basis

The United Nations agency International Telecommunication Union (ITU) has compiled over 100 different definitions of a smart city and has come up with the following definition: ‘A smart sustainable city is innovative and uses information and communication technologies and other tools to improve the quality of life, the efficiency of urban operations and services, and competitiveness, thereby meeting the economic, social and environmental needs of present and future generations.’

‘The term smart city thus describes a comprehensive concept for a city in which data plays a key role in the form of smart infrastructures. These include the following areas: buildings, mobility, energy, water, waste disposal, healthcare and digital infrastructures’.

Five digital levels

Five interlocking digital levels are to be assumed: a widely distributed network of sensors, connectivity for ‘collecting’ the data, data analysis with forecasting functionality, an automation layer and an urban network that connects the physical and digital infrastructures. Successful implementation definitely requires a fail-safe broadband network, an efficient ecosystem for the Internet of Things (IoT) and real-time analysis of the collected data in terms of big data and AI. Even today, a city consists of different vertical infrastructures, which, however, have so far functioned more or less separately from each other. The challenge lies in capturing the immense volumes of data from these completely different areas, combining them and evaluating them using AI.

Urban data bus for a digital ecosystem

An electronic urban data bus as the basis for a digital ecosystem is a pioneering first step towards a smart city. In such a digital ecosystem, the public and private sectors could work together according to defined rules to provide the population with a range of coordinated services. In practice, it is usually not about comprehensive concepts, but rather about using sensors and AI to address specific problem areas, such as inner-city parking management.

The global smart cities market is currently estimated to be worth over 700 billion dollars and is forecast to grow to 4 trillion dollars by 2030. The German smart cities market is currently estimated at around 8 billion euros; by 2030, it is expected to expand to up to 47 billion euros. The potential for smart cities is huge.

Dr Daniel Trauth is the managing director of dataMatters GmbH (www.datamatters.io), which specialises in the use of artificial intelligence in the real economy. Areas of application include smart cities, smart factories, industry 4.0, smart buildings, IoT, mechanical and plant engineering, healthcare, agriculture and much more. Data from real-world operations is collected by sensors, collected in data rooms and analysed there using AI software or transferred to the corporate customers' AI systems for further processing. The results can be used to make operations more efficient, sustainable and economical. Examples of applications: parking management, early warning systems for anomalies such as extreme weather, machine wear or burst pipes, heating/lighting automation in buildings, CO2 footprint recording based on real data, and much more. For example, municipalities like to use dataMatters to improve urban quality of life and sustainability. Dr.-Ing. Dipl.-Wirt. Ing. Daniel Trauth has spun off dataMatters from RWTH Aachen University and led it to become an international player at the interface between the real economy and AI. He has been honoured for this with over 20 awards (RWTH Spin-off Award 2019, digitalPioneer 2020, and many more).