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.
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.
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.
