Enabling the Future Internet for Smart Cities

Enabling the Future Internet for Smart Cities

Research Themes

Combining Data for Better Health Care

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.

Team

Prof. Renata Wassermann (renata@ime.usp.br)
Arlindo Flavio da Conceição
Kelly Rosa Braghetto

Students:
Débora Lina Nascimento Ciriaco Pereira
Evelin Angélica de Farias

External collaborators:
– Diogo F. C. Patrao – A.C. Camargo
– Fernanda Almeida – UFABC
– Lais Salvador – DCC/UFBA

Management of Optical Architectures on the Support of the 5G Internet and Future Radio Access Networks

Team

Prof. Daniel Batista (batista@ime.usp.br)
Prof. Edmundo Roberto Mauro Madeira
Prof. Carlos Kamienski
Prof. Gustavo Bittencourt Figueiredo
Prof. Massimo Tornatore
Prof. Biswanath Mukherjee

Modeling and prediction of the evolution of bus line travel times for smart mobility

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.

Team

Prof. Raphael Camargo (raphael.camargo@ufabc.edu.br)
Prof. Renato Ishii
Prof. Daniel Cordeiro
Dr. Roberto Speicys

Sensing urban areas for monitoring and warning of natural disasters

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.

Team

Prof. Arlindo da Conceição (arlindo.conceicao@unifesp.br)
Prof. Álvaro Luiz Fazenda
Prof. Denise Stringhin

Prof. Alfredo Goldman
Dr. Antonio D. de Carvalho J.

Processamento de eventos complexos com modelagem semântica e tratamento de incerteza para aplicações de cidades inteligentes

Team

Prof. Rafael Lopes
Prof. Francisco J. Silva e Silva (fssilva@lsdi.ufma.br)
Prof. Markus Endler

Safety Management for Pedestrians in Urban Environments

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.

Team

Prof. Flavio S. C. Silva (fcs@ime.usp.br)
Prof. Julio Singer
Prof. Antonio Carlos
Prof. Paulo Miranda
Prof. Arlindo da Conceição
Prof. Stefania Bandini
Andrea Gorrini
Luca Crociani

InterSCity: A Scable Microservice-based Open Source Platform for Smart Cities

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.

Team

Prof. Claudio Luiz Marte
Prof. Alfredo Goldman
Prof. Fabio Kon (kon@ime.usp.br)
Prof. Markus Endler
Prof. Fabio Costa

PMSP

UNI: Infraestrutura de Rede Unificada

Team

Prof. Edmundo Madeira
Prof. Luiz Bittencourt
Prof. Alfredo Goldman
Prof. Fabio Kon
Prof. Otto Duarte (otto@gta.ufrj.br)

SOS: Sistema de Operação em Segurança

Team

Prof. Daniel Batista
Prof. Alfredo Goldman
Prof. Fabio Kon
Prof. Otto Duarte (otto@gta.ufrj.br)
Prof. Carlos Kamienski

Improving fog computing techniques to allow a better quality of experience in vehicular networks

Team

Prof. Edmundo Madeira (edmundo@ic.unicamp.br)
Prof. Luiz Bittencourt
Prof. Alfredo Goldman

OpenAir Museum: development, convergences and integration between Arquigrafia and Smart Audio City Guide

Team

Prof. Marco Aurélio Gerosa
Prof. Flavio Soares Correia
Prof. Artur Simões Rozestraten (artur.rozestraten@usp.br)

ContextNet SME: A Multisided Platform for IoT Service Matchmaking, Composition and Commoditization

Team

Prof. Markus Endler (endler@inf.puc-rio.br)
Prof. Alfredo Goldman
Prof. Francisco Silva e Silva
Prof. Marcelo Klötztle

Sensing in Smart Cities with Open-design Hardware

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.

Team

Janaina Silva
Antonio Deusany de Carvalho Junior
Prof. Alfredo Goldman
Prof. Fabio Kon
Prof. Marcos Buckeridge

Big Data visualization for a Smart City Platform

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.

A Data Processing Service for Smart Cities

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,

InterSCSimulator: A Scalable, Open Source Smart City Simulator

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.

Team

Eduardo F.Z. Santana
Fabio Kon | site

Integrating scalable simulator and platform for smart cities

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.

A Scalable Microservice-based Open Source Platform for Smart Cities

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,