The Big Data and IoT for Smart Cities

The digitalization of professional and personal worlds also leads to the digitization of our cities. Large American IT corporations such as IBM and Cisco have been in a few years into their respective Smart City strategies. Now, SAP, Microsoft and Google are also offering their solutions for more efficient urban development. The Internet of Things (IoT) and  Big Data technologies have offered new opportunities for many cities to collect more data and provide better services.

Internet of Things and Services

Digitization of private and professional areas by the expansion of the Internet has made many things possible. For example, fast information processing and communication/collaboration via broadband. The parallel spread of smart devices (e.g., smartphones) also led to the emergence of new opportunities for more cooperative public services.

The new Internet protocol IPv6 enables an almost infinitely extended addressing frame (compared to the limited previous protocol IPv4) and thus enable billions of devices or products with sensors, computing power etc., to be connected  via Internet (e.g., Internet of Things/services).

For example, in the City of Santander, Spain, sensors are used to collect measure different parameters, such as the temperature, the noise level and the light conditions, from selected roads in addition to the number of vehicles. These sensors are installed both in the road lighting and in the road surface and can collect data on the current traffic flow. Sensors are also installed in buses in order to transmit congestion data. In the future, trains and smart city bikes will also be used for data collection.

Big Data and Predictive Analytics

The collection of data generated in various information and communication systems, nowadays takes place in many different ways. This allows information to be generated through the use of mobile devices, through pictures of video recordings, or by leaving comments in social networks.  In addition, the embedded sensors and GPS data from vehicles also provide information which can flow into the data analysis.

From these data collection activities, both structured and unstructured data are often collected, processed, and analyzed in real-time. This is done by so-called the Big Data analytics systems. The results from Big Data analytics are able to show not only the historical facts, but also the prediction of possible subsequence (predictive analytics).

Example of Predictive Analytics for City Services

The “Smart Cities Council” network has recently led an emotionally sensitive study that highlights the benefits of forward-looking analysis named “how predictive analytics is saving children’s lives in Los Angeles.”,   Based on the data analysis results, the study is trying to predict the possible abuse of children at an early stage (at best before entering). Necessary measures are taken by merging data from different local institutions and their analysis. The study is intended to show where action arises.

Solutions for Different Areas of a Smart City

In addition to technical solutions to support the actual city services management, the product portfolio of the large providers shows a broader spectrum. For example, they are not only offering solutions for energy supply, water supply and transportation in the core areas of a city, but also technologies for the control of the building infrastructure (Smart Building). In order to ensure public safety, the use of surveillance cameras is also proposed. The range of large IT companies also includes products in the fields of education, care and social services. Some cities have developed their own smart city ideas in partnerships with one of the major IT solution providers.

Conclusions

The digitization of our cities allows us installing more and better tools to collect data. The installation of sensors on buildings allows for example to obtain interesting data on consumption of energy, pollution levels in the air, etc. Throughout the city, the high performance surveillance camera systems also make the city possible to obtain data for security services.

Regarding mobility, a key issue for smart cities, the tools built into cars and public transport can obtain very accurate data on geolocation of vehicles and citizens. The development of drones also provides an additional tool for gathering information about the city. Thanks to their autonomy and mobility, these connected objects are able to provide reliable and instant information on a selected variable of a city.