Coordinator: Augusto Sampaio
The main objective of this project is to create a systematic and rigorous methodology to specify, verify, design and implement robotic applications. It is part of the RoboStar initiative (https://www.cs.york.ac.uk/RoboStar/). The focus is on the design of a graphical simulation language, RoboSim, and mapping models in RoboSim to several target platforms: Arduino, B and Simulink/Stateflow, among others. Development of the final implementations from the simulations is also in scope. Finally, we will also consider probabilistic models, modelling of the environment and the development of real-world applications. Currently, the RoboCalc project offers the following facilities:
- A state machine based notation (RoboChart) to model individual robots;
- A translation from RoboChart to the process algebra CSP to use the FDR tool in background for the purpose of functional analyses (both of classical properties as deadlock and livelock, as well as doman specific properties); and
- RoboTool, implemented as an Eclipse plugin, to support the model edition and analysis as described in the previous items. The aim is to extend this scope with facilities for simulation and implementation of robot applications. We also plan to evolve RoboChart with features to specify swarm robots.
The aim is to extend this scope with facilities for simulation and implementation of robot applications. We also plan to evolve RoboChart with features to specify swarm robots. Finally, we will also consider modelling of the environment and develop three case studies.
Building an Urban Mobility Data Infrastructure
Coordinator: Kiev Gama
The popularization of Internet of Things in the context of smart cities has led to an increasing use of sensors to monitor different aspects of the city such as traffic, weather and air pollution. For instance, big Brazilian cities, including Recife, Rio de Janeiro, Curitiba and São Paulo, have equipped their bus fleets with sensors to monitor their buses in order to improve their service. The huge amount of data produced by IoT sensors (e.g. geolocation) has brought the attention of researchers and practitioners interesting in studying, e.g., mobility patterns and traffic behavior. The main goal of this project is to collect, integrate and analyze urban data from IoT sensors and other sources (e.g. social media) to help monitoring and planning urban mobility. Since the data used by this project might be spread in different sources and might not be easy to access, we also plan to develop a solution that publishes this data in a proper and accessible way.
Towards an Evaluation and Support Platform for Conducting Empirical Studies and Creating Testbeds
Coordinator: Sérgio Soares
INES 2.0 will have several projects addressing Smart Cities challenges. This project goal is to provide infrastructure, methodologies, and tools to support evaluating research results/proposals from INES 2.0 projects. This also brings a positive side-effect, while addressing all INES 2.0 projects looking for supporting assessment activities, we will have a wide view of INES 2.0 progress and results. This is also strategic, since we can be a focal point to the project coordination and to ensure projects are following the coordination definition to use other projects results in their proposals, such as middleware, applications,etc.
Prevention, detection, and resolution of code integration conflicts
Coordinator: Paulo Borba
This project aims at investigating and proposing better collaborative development tools supporting prevention, detection and resolution of code integration conflicts. This way, we hope that organizations adopting our proposed tools gain competitive advantage as a result of reducing the number of conflicts and the effort to detect and resolve them during the software development life cycle. The idea is to investigate alternative forms of modularity, mainly directed to the code integration process, with the purpose of improving this process productivity and the resulting products quality. To this end, we intend to propose, formalize, implement and evaluate code integration concepts, techniques and tools.
SWS – Smart Water System
Coordinator: Eduardo Almeida
Water is a vital and scarce resource in our society. More and more, different cities around the world have been facing problems to manage it in an efficient way. The goal of this project is to develop a real time intelligent system to manage water reservoirs around the city. The main aspects considered in the solution should be the level of water in the reservoirs and the water quality.
ADApt – Abordagem para Desenvolvimento e Avaliação de Aplicações no Ambiente de Cidades Inteligentes
Coordinator: Rossana Andrade
In the coming years the number of people living in urban centers will increase. As as result, infrastructure problems will become increasingly complex. Cities need to be smart to ensure the well-being of both the city and its citizens. The intelligence of a city is driven and technologically enabled by the Internet of Things (IoT).In this context, this project propose an approach for the UFC/UFBA/UFRN 4 development and evaluation of IoT applications focused on smart cities. As a result, his work will investigate personalization issues for smart home scenarios where user preferences can be identified to predict actions that smart objects can execute proactively. At the same time, the adaptations performed by smart objects in this scenario demand that quality aspects are assured. Therefore, the best system configuration that maximizes quality attributes should be prioritized. As a result, it is expected novel methods for profile identification of users in the context of smart cities and new quality evaluation measures tailored for smart cities.
KNoT-FI: An Integrated KNoT-FIWARE Environment for Developing Smart Cities Applications
Coordinator: Thais Vasconcelos Batista
In the Internet of Things (IoT) paradigm, middleware platforms have been used as underlying infrastructure to ease application development. FIWARE is a platform that has stood out in such a scenario as an open, extensible solution for developing IoT applications by making use of generic components and a standardized API. However, it allows integrating only devices with native connection to the Internet, thus requiring adaptations to integrate those that do not have this capability. On the other hand, the KNoT platform allows virtualizing physical devices that do not have IP connection, with minimal development effort. In this context, this project aims to provide an integrated environment supported by a middleware infrastructure to ease application development, allowing to use several types of devices to compose smart city applications. The environment will be explored in a case study in public safety, encompassing 2 UFRN/UFPE/CESAR information provided by different sources (as cameras and sensors) and citizen participation.
Improving the Energy Efficiency of Android Mobiles Applications
Coordinator: Fernando José Castor de Lima Filho
Energy consumption is an important problem in software development, especially for mobile devices, a fundamental component of smart city infrastructures. There are many different ways to reduce the energy consumption of an application, from controlling usage of a devices’ sensors to choosing the most appropriate data structure. This information is spread throughout vendor manuals, discussions forums, scientific papers, and other sources. In this proposal, we aim to develop an intelligent virtual assistant (IVA) to centralize the validated knowledge produced by researchers and specialists in software energy efficiency, with a focus on Android apps. Using an IVA should lower the complexity of saving energy in app development, supporting even novice developers in building energy-efficient apps.
A Microservice-Driven Architecture to support Fog Computing with focus on processing and contextual data offloading
Coordinators: Fernando Antonio Mota Trinta and Vinícius Cardoso Garcia
Fog Computing is defined as a scenario where a huge number of heterogeneous (wireless and sometimes autonomous), ubiquitous and decentralized devices communicate and potentially cooperate among themselves and with the network to perform storage and processing tasks without the intervention of third parties. These tasks may support basic network functions or new services and applications that run in a sandboxed environment. Fog Computing presents several challenges. One of them includes the management of complex tasks that are not well-supported by resource-constrained devices. In fact, this problem is not restricted to computing tasks only, but it can also comprises data that should not be stored in some IoT nodes. A promising technique to address this issue is offloading, an approach to increase performance and reduce the energy consumption by migrating processing or data from constrained devices into other infrastructure, with greater computing power and storage. In this project, we address this research topic and propose an architecture to support data and computing offloading in Fog environments based on the microservices architectural style.
SPEAKR – Smart Processing & Environment for Analytics Knowledge Resources
Coordinator: Ricardo José Rocha Amorim
This project comes from the development of an architecture for the analysis of large amounts of multi-source, heterogeneous data generated through intelligent services. This combines Big Data technologies, ontologies, middleware and architectural standards, adopted as a way to obtain a flexible and interoperable architecture for the measurement, collection and analysis of data in diverse applications and their context. Software Engineering and Design techniques will be used in the development of the platform and the design of friendly interfaces that facilitate the use of intelligent services of analytics knowledge in contexts of multi-source, heterogeneous data. It is expected to obtain a generic architecture and independent of the context, being able to be integrated in different business environments.