Smart cities have led us to collect a huge amount of data every day. Interpret and extract some meaning about these data is a major issue to solve. Big data visualization techniques can be used to present the data in a graphical/visual way allowing one to grasp its characteristics or identify new patterns. Tallys’ research intends to develop a Big Data Visualization service integrated within InterSCity platform that will provide reusable visualization mechanisms to support the development of Smart Cities applications.
Smart city platforms needs to integrate a large volume of data from different sources that must be properly managed to produce valuable outcomes for cities. To provide reusable data processing services for several client applications, such platforms needs to use Big Data tools and techniques in both historical and real-time data processing. In this sense, smart city platforms must provide generic services and interfaces that allow different applications to meet data processing requirements in a scalable,
This research aims to develop an open-source, extensible, large-scale Traffic Simulator for Smart Cities developed in Erlang, called InterSCSimulator. The objective of InterSCSimulator is simulate complex Smart City scenarios with millions of agents using a real map of a large city and, in future versions, address other domains beyond traffic.
Eduardo F.Z. Santana
Fabio Kon | site
The concept of Smart Cities has been growing as well as several platforms to support such demand. However, testing these platforms in real environments is often infeasible. Lack of infrastructure, cost and political questions are some of the issues that are not simple to solve. A Smart City Simulator that is scalable and able to simulate the entire infrastructure and peculiarities of a city can facilitate this kind of test.
This research aims at integrating the InterSCity platform and the InterSCSimulator simulator as they have already been presented as highly scalable open source projects.
Despite the various advances in middleware technologies to support future smart cities, there are no universally accepted platforms yet. Most of the existing solutions do not provide the required flexibility to be shared across cities. Moreover, the extensive use and development of non-open-source software leads to interoperability issues and limits the collaboration among R&D groups. Arthur’s research explores the use of a microservices architecture to address key practical challenges in smart city platforms. More specifically,