Research Themes

IoT implementations are vulnerable mainly because developers place more emphasis on functionality rather than security. In fact, smart city initiatives are usually deployed without security testing. For instance, MQTT protocol, the most widely-used IoT protocol, has been implemented for several uses, including medical equipment, airplane coordination, and home automation systems, but it was not designed with security in mind. Security-by-design, preventive, and proactive approaches are needed to mitigate potential threats; identify possible attack scenarios; reduce economic losses;

The high penetration of variable and non-programmable distributed micro-generation of energy, smart buildings, smart homes, and smart meters have brought new challenges for the operation of the Power Systems. This new environment needs a smarter network considering the transformation of the simple customer of the power grid in a “Smart Customer”, and many times, in a “Prosumer” (Producer/Consumer). InterSCity, as a multidisciplinary project to develop a platform for smart cities of the future, uses digital technologies to make all services of a city more efficient and reliable,

This project focuses on improving health care in São Paulo through the use of distributed data, available either publicly or from our partners, such as the City Health Secretariat. Integrating this data smartly will allow us to have a general overview of patient care pathways and of the use of public resources, which will in turn allow for better planning at the city level. While the focus is on health, the methods and frameworks will be developed having in mind their future adaptation to other important domains, such as public transport.

The future 5G Internet has demanding new efforts from telecommunication operators to meet its demands. Cloud radio access networks (CRAN) based architectures have already been deployed by operators to cope with the large user coverage demanded by those networks, maintaining an energy-efficiently operation by centralizing the mobile data processing. However, CRAN demands high transfer rates on the fronthaul interconnecting the radio elements and the cloud.
Moreover, it introduces strict time delay constraints, which has led to the proposal of hybrid architectures that implement centralized and distributed closer-to-the-user processing using Fog Computing.

Bus transportation systems in metropolis, such as São Paulo, are complex systems that constantly interacts with city dynamics. Understanding the behavior of this system under different contexts, such as day of the week, time of the day and holidays is vital for a better planning of bus transportation systems. The objective of this project is to improve bus scheduling and travel time predictions using a novel graph-based model for bus travel time behavior under different contexts, using: (i) regression and clustering techniques over historical GPS data to extract spatio-temporal features, and considering factors such as week day, time of the day and holidays and (ii) a combination of the graph-based model and real-time information from multiple bus routes to predict the performance of bus lines and the behavior of individual buses.

The focus of this project is to take advantage of the Internet of Things solutions in order to design solutions that obtain data from sensors distributed over Smart Cities. Free hardware and Internet of Things technologies will be used to build sustainable sensing stations that will be interconnected in urban areas considering the risk of climate changes, possible damage, and minor environment impact. The research results will be distributed with open source and hardware in order to allow other cities to benefit from the solutions created.

The goal of our project is to build data-centric models that can be used to simulate interactions involving vehicle passengers, drivers and pedestrians, to assess safety related issues. As a concrete deliverable, we aim at the development of a tool to inform citizens about safety issues in different sites within a urban setting.

Future Smart Cities will gather the Internet of Things, Big Data, and Cloud Computing to enable novel solutions to enhance citizens’ experience within the city. In opposition to traditional approaches based on vertical silos and ad hoc solutions, integrated middleware platforms can provide an unified infrastructure to support sophisticated, cross-domain smart city applications.

This project aims open-design hardware prototypes for monitoring the environment using open-design hardware and open source software. The first prototype has a sensor station and a base station. The sensor station is attached to a tree and sends the collected data to the base station which is interconnected to the InterSCity Platform. The project is partnership with the group managed by Prof. Marcos Buckeridge, from Instituto de Biociências – Universidade de São Paulo in the context of the INCT InterSCity.

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.

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,