Smart Cities - Hungary

As the world population continues to grow, cities are especially becoming more crowded and in need of more efficient infrastructure and service offerings. Internet of Things (IoT) technologies are improving efficiency, sustainability and livability.

Environmental concerns have been gaining traction in recent years and the citizens are demanding sustainable solutions. Smart energy systems and waste management solutions are adopting IoT technologies and benefiting from the data collected via the connected devices. Smart grids are especially important in increasing reliability and security in the times of outages, security threats and other unexpected occurrences. IoT sensors are used in smart waste management to monitor the garbage cans and optimize waste collection schedules and reduce litter.

The Smart Cities market is expected to continue seeing a fast growth, as governments are seeing the potential they can bring for both sustainable and economic growth. China has made “Smart Cities Development Plan” part of their Made in China 2025, while Germany invested over EUR 1 billion for development and investment of urban technologies.

Data coverage

The data encompasses B2B, B2C and B2G revenues. The revenue only refers to the spending share of the Internet of Things components.

Modeling approach/ Market size:

The market size is determined through a combination of top-down and bottom-up approaches. We use annual financial reports of the market-leading companies and industry associations, as well as third-party studies and reports to analyze the markets. To estimate the segment size for each country individually, we use relevant key market indicators and data from country-specific industry associations, such as consumer spending, internet penetration, 4G coverage, and current and historical developments. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques but primarily exponential smoothing. The selection of forecasting techniques is based on the behavior of the relevant market. The main drivers are the GDP and the level of digitization.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change.