Blog publications

Disruptive technologies for smart cities - Artificial intelligence

Disruptive technologies for smart cities - Artificial intelligence

KISMC & partners

This article is animated by the interim results of an ongoing Erasmus+ project named Smart technologies by design (Smart by Design).

This international project is carrying out by Knowledge, Innovation and Strategies Management Club (KISMC) - a Bulgarian innovation management organization that is focused on developing competences in innovation, creativity and entrepreneurship.

Knowledge, Innovation and Strategies Management Club is a member of our cluster.

Our attention will be focused on the gap between the citizen's (smart cities') needs, the technological solutions which can cover these needs, and the knowledge and skills of citizens, cities and service providers of using these technologies for a better life.

Disruptive technologies make the cities smarter

Disruptive technologies have the potential to transform the way cities currently operate and they are at the core of nearly all upcoming smart city’s solutions. After a decade of experimentation, smart cities are entering a new phase. Although digital solutions are only one of the tools needed to make a city great, they are the most powerful and cost-effective additions seen in many years. According to the McKinsey Global Institute, digital solutions could improve some quality-of-life indicators by as much as 30 per cent. Real-time crime mapping, for instance, utilizes statistical analysis to highlight patterns, while predictive policing goes a step further, anticipating crime to head off incidents before they occur.

Another example of these solutions is the Internet of Things sensors on existing infrastructure systems which can help crews fix problems before they turn into breakdowns and delays. If we examine our history, we realize that we live in constant change. Humans have faced all sorts of changes, economic, political, climatic, technological. In the different industrial revolutions seized, adaptations made by humans can be perceived, along with the 1st industrial revolution, the railway arrived with the steam engines which enabled transportation of goods causing all the farming, demographic and transport revolution. Afterwards, the 2nd industrial revolution arrived, emerging new energy sources like oil and electricity, which with its utilization, first technological innovations took place. These technological innovations produced an improvement in the quality of life of people, first personal computers and internet appeared which located us before a 3rd industrial revolution, not only in a technological one but in a scientific and a cultural one. With this 3rd revolution, fast technologic advances force humans to assimilate more concepts in a shorter time, information, productivity and everything reach scales not previously reached and under this context the 4th industrial revolution appeared, where we really perceived and realized that we live in a constant change, as mentioned at the beginning, achieving small or big progress which is changing the world.

A vision for cities of the future

The city of the future must meet the needs of its residents. Yet in surveying residents of 25 major cities, McKinsey finds that a fifth of those cities falls short of delivering satisfaction. Respondents cited numerous inadequacies: crime, congestion, fire emergency response, waste management, active mobility options, police security, lack of basic utilities, public transit, as well as poor quality of housing and government services. Given the fierce competition for talent across cities, dissatisfied urbanites are likely to vote with their feet and leave for more attractive environments. (Source: Thriving amid turbulence: Imagining the cities of the future; Capital Projects & Infrastructure, Public Sector October 2018, McKinsey & Company). In order to not lag behind due to inactivity, the city leaders must know how to use the newest and most advanced technologies, which is progressing faster than expected. We have realized during the implementation of the project and as a result of the study that the most important and those with enough predictive potential to transform the cities into smart cities are the following technologies (technology areas):

  1. Artificial Intelligence
  2. Data analytics
  3. Cloud Computing
  4. Internet of Things
  5. Cyber-physical systems
  6. Smart sensors
  7. Collaborative robotics
  8. Cybersecurity
  9. Blockchain
  10. Augmented reality
  11. Virtual reality

Artificial Intelligence

We start with the first area Artificial Intelligence (AI) and below you can find the features, functionalities, existing platforms, and standards, which are recognized by us as the most important from the point of view of upcoming evolving and disruptive solutions in the smart cities.

Artificial Intelligence (AI) refers to the technology which aims the creation of intelligent machines that react and work like humans. Some of the skills for the computers with AI are the speech recognition, learning (information acquisition and patterns to use it), reasoning (using rules to reach definitive conclusions), self-correction and problems solving. This technology allows machines to learn from past experiences, adjust to new inputs and perform tasks like humans. Nowadays, the AI refers to a big range of concepts, from robotic process automation to the current more sophisticated robots. It has evolved due to the huge amount of available data or the increase of speed, size and variety of data that companies are collecting. The AI is also able to realize tasks like the identification of patterns in data in a much more efficient way than humans, which allows companies to extract better conclusions from the information.

Artificial Intelligence can be categorized in different ways and types of activities that they perform. But basically, the tasks that a computer-based on AI can carry out, can go from developed from very concrete tasks (faint AI) to other systems provided with human cognitive skills (strong AI), being able to give answers to problems or tasks that previously were not assigned or expected to them. In recent years, the AI has grown capabilities thanks to the advance of some technologies, such as:

  • Improved machine learning (ML) techniques;
  • Availability of massive amounts of training data;
  • Unprecedented computing power;
  • Mobile connectivity.

Existing platforms

Platforms for AI are hardware architectures or software frameworks that allow the software to run. Even if there are many different types of platforms related to this technology, some of the most relevant are: Platform Address Microsoft Azure Machine Learning (; Google Cloud Prediction API (; TensorFlow  (; Infosys Nia (; Wipro Homes (; API.AI (; Premonition (; Rainbird (; Ayasdi (; MindMeld (; Wit (; Vital A. I (; KAI (; Receptiviti (; Rage-A (; Infrrd ( );


Published standards

The European Commission has launched the Communication COM (2018) Artificial Intelligence for Europe which establishes a new initiative for Europe about AI. This recognizes the need of the standardization as an answer to the challenges of this key technology, especially in terms of security, trust and ethical considerations. CEN and CENELEC support the fulfilment of the European legislation with harmonized standards. In relation to international organizations, the ISO has a technical committee which is working on the development of standards in Artificial Intelligence, which is the ISO/IEC JTC 1/SC 42. There are currently two published ISO standards under this working group, and there are some more which are being developed. Published standards:

  • ISO/IEC TR 20547-2:2018: Information technology - Big data reference architecture - Part 2: Use cases and derived requirements;
  • ISO/IEC TR 20547-5:2018: Information technology - Big data reference architecture - Part 5: Standards roadmap;

Application areas

Artificial Intelligence is a term which has existed for many years, but due to the development that current technologies are having, it has been recently spread to different application sectors and environments. Some of them are:

  • Entertainment: videogames, apps, sports betting;
  • Recommendations in music, videos or movies;
  • Self-driving cars like Google driverless car, Tesla’s autopilot: self-parking, collision detection, blind-spot monitoring, voice recognition or navigation;
  • Chat-bots for online customer service;
  • Banking and finance: analysing market data, manage finances, offer suggestions;
  • Manufacturing: assembling plants;
  • eCommerce and digital marketing;
  • Home applications: learning behaviours and patterns;
  • Electronics: thermostats or smart lights
  • Workplace communication;
  • Healthcare: diagnosis and treatments, virtual nurses;
  • Cybersecurity;
  • Logistics and supply chain;
  • Online retail stores;
  • Smartphones: virtual personal assistants (Siri, Cortana or Google Now).

Expected development over time

As one of the main technologies which will help to evolve our ways to work and interact with technology, the trend is that the AI will keep growing and becoming more normalized in our society. So, platforms, standards, and applications will keep incrementing. Platforms Apparently, the future of the AI resides on a deeper personalization, innovation in voice AI and a better view of the customer. Even if there are plenty of platforms for AI, not many of them are deploying voice interfaces. Some applications for mobile devices have already implemented it in daily life and it will offer opportunities for companies. The tendency will be to add voice control to their AI for a better experience with their customers. Some of the most famous firms (Google, Amazon...) are integrating voice assistants as part of their services. The AI will help for a bigger personalization of services. Customers will be able to express preferences to the biggest brands and acquire much more personalized services or products. So, future platforms will shift towards a new type of services.

Upcoming standards

The European Commission foresees that Artificial Intelligence will impact the commitment of some European guidelines. It will have effects in several sectors in which standardization is very relevant: smart manufacturing, robotics, autonomous driving, virtual reality, health sector, visual recognition, data analysis and management, domestic tools or cybersecurity. In all those sectors there are already essential standards which will need to be updated in order to add this new technology.

Currently, there are four standards under development from the working group ISO/IEC JTC 1/SC 42:

  • ISO/IEC AWI TR 20547-1: Information technology -- Big data reference architecture Part 1: Framework and application process;
  • ISO/IEC DIS 20547-3: Information technology -- Big data reference architecture -- Part 3: Reference architecture;
  • ISO/IEC AWI 22989: Artificial Intelligence Concepts and Terminology
  • ISO/IEC AWI 23053: Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML).

Potential applications for the knowledge economy and in particular for the smart cities

Even if Artificial Intelligence is becoming more common in our daily life, there are many more applications foreseen or improved, like:

  • Automated transport: fully self-driving cars, buses or trains;
  • Cyborg technology: enhancing natural abilities, amputated parts;
  • Climate change: identifying trends and use the information to come up with solutions and natural disasters;
  • Dangerous jobs: bomb defusing, toxic substances, intense heat, difficult access places, prevent human harm;
  • Robot as friends: in the future, robots will be able to understand and feel emotions;
  • Eldercare: helping with everyday life providing more independence;
  • Journalism: it is expected that the AI will be able to write articles or reports which don’t require very deep knowledge.

Latest news

© 2024 SOFIA - Knowledge City - cluster.