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Smart Cities Research Center

Ongoing projects

EcoModZHC (CENTRO-01-0145-FEDER-179932)

logo Title: Circular Economy of Water and Materials through Modular Constructed Wetlands
Partners: CIMT, NERSANT, Ambidustri, Palser, Pegop, petMaxi, SLD
Researchers: Henrique Pinho, Manuel Barros, Carlos Ferreira, Pedro Granchinho, Dina Mateus, Isabel Silva, Pedro Neves, Simão Lopes
Date: 2022-07-01 - 2023-07-30
Status: ongoing
url: website
Description: The EcoModZHC project consists of a Proof of Concept, in which it is intended to implement a prototype of a Constructed Wetland to demonstrate the effectiveness of urban and industrial wastewater recovery through modular systems, promoting the circular economy of water and solid waste and by-products, and to promote this greener and more sustainable technology for wastewater treatment. The prototype to be built, installed and operated, will include two innovative features in this type of wastewater treatment installation: (i) Remote, constant and real-time monitoring of the operation of the installation and the performance and quality parameters of the potable water; (ii) The energy autonomy of the installation, through renewable energy systems.

OMRisk (UIDB/05567/2020/04)

logo Title: OMRisk – Optical sensor for microbiological risk evaluation
Partners: NA
Researchers: Rui Gonçalves, Henrique Pinho, José Casimiro Pereira, Manuel Barros, Paulo Coelho, Pedro Correia, Sandra Jardim, Luís Oliveira, Dina Mateus, Luís Almeida
Date: 2022-06-01 - 2023-12-31
Status: ongoing
url:
Description: The main objective of this project is the development and application of an image acquisition system for identification of pathogenic microorganisms in real-time mode (or almost real-time). The system comprises an optical system and digital sensor aimed to images acquisition in the visible, ultraviolet and near infrared bands with the expected quality that will be able to feed an automatic image classification framework. The project includes the development of image processing and analyses tools for image enhancement and fine tuning of the acquisition kit, the definition of the image database and related metadata and also the development of a framework for image labelling and dataset creation for enabling supervised learning algorithms.

Solar (UIDB/05567/2020/05)

logo Title: Prediction and detection of sunlight entering through transparent building surfaces
Partners: NA
Researchers: Diogo Chambel Lopes, Isabel Nogueira
Date: 2022-05-29 - 2023-12-31
Status: ongoing
url:
Description: Solar is a project that aims to develop a software to receive the necessary data and produce the desired results in terms of sunlight availability inside buildings. The presence of sunlight over time can be predicted using variables such as latitude and longitude, the configuration of windows, balconies and other surfaces of sunlight entry, and a survey of the surrounding obstacles. Its goal is to develop an image processing algorithm that can determine the blocked and unblocked areas for each combination of azimuth and elevation coordinates and generate the desired solar exposure data for new construction or solar exposure analysis of existing buildings. It is hoped that procedures for assessing the thermal quality of buildings will be added at a later stage, with the goal of more efficient energy use.

MoSBurn (UIDB/05567/2020/03)

logo Title: Modeling the multifactorial burnout syndrome in college students
Partners: Center for Research and Innovation in Business Sciences and Information Systems, Instituto Politécnico do Porto, Center for Collaborative Studies in Mathematical Biology (Illinois State University)
Researchers: Luís M. Grilo, Maria Cristina Costa, Aldina Correia, Anuj Mubayi
Date: 2022-05-01 - 2023-12-31
Status: ongoing
url:
Description: The MoSBurn project aims to model the Burnout (considering the three dimensions: exhaustion, cynicism and effectiveness) of college students based on a quantitative study that includes questionnaires with internationally validated scales. Burnout is a state of emotional, mental and physical exhaustion caused by excessive and prolonged stress (distress), which has a detrimental effect on students’ academic performance and can ultimately lead to dropout. Recently, this problem seems to have increased due to the pandemic of COVID-19, which is a major concern for universities. By applying the Structural Equation Modeling, it is expected to estimate a model that allows identifying which (in)direct effects are statistically significant regarding burnout of college students, considering optimism and distress as potential predictors. Understanding the results may help suggest some intervention to improve student performance and help universities in their mission to provide well-being and quality education to their students.

Cognition (UIDB/05567/2020/01)

logo Title: Driver’s Behavior Cognition Based on Mobile Phone Sensors
Partners: Instituto Politécnico de Leiria, Igor Sikorsky Kyiv Polytechnic Institute
Researchers: João Patrício, Carlos Ferreira, Carlos Rabadão, Eugénio Pina de Almeida, Iryna Husyeva, Oleksandr Koval, Oleksandr Sarafannikov, Paulo Costa, Paulo Loureiro, Sandra Jardim, Sílvio Mendes
Date: 2021-06-01 - 2023-12-31
Status: ongoing
url:
Description: COGNITION aims to develop a software solution for early recognition of abnormal and inattentive driving in order to prevent road accidents and increase traffic safety. More specifically, the aim of this project is to develop an application which gathers data from mobile phone sensors, processes it and warns the driver about potentially dangerous situations. It is intended that the project culminates in the provision of a valuable service in the area of traffic safety. Moreover, if driving behavior such as inattention and drunk driving can be detected and prevented in a timely manner, most road traffic accidents can be prevented. In addition, vehicle dynamics and driving behavior can also be applied to crowd detection to help traffic planners analyze traffic conditions and make correct decisions.

GePISCal (UIDB/05567/2020)

logo Title: General Purpose Image Similarity Calculation for Heterogeneous Applications
Partners: Instituto Politécnico de Leiria, Igor Sikorsky Kyiv Polytechnic Institute
Researchers: Sandra Jardim, Carlos Mora, Eugénio Pina de Almeida, João Patrício, José Casimiro Pereira
Date: 2021-06-01 - 2023-12-31
Status: ongoing
url: YouTube
Description: GePISCal is a digital image processing project, where the main research is done in the image segmentation, image features extraction, object extraction and classification, and image interpretation areas. It aims the development of an effective and reliable automatic solution for graphic research/surveillance, through the direct confrontation of the graphic elements existing in the images to be compared, without any human intervention in pre- or post-research screening of the images obtained. Through the design and implementation of image analysis algorithms, based on machine and deep learning models and techniques, it is intended to model the human perception of images, and overcome some of the limitations of currently existing Content Based Image Retrieval (CBIR) systems. It is intended that the system resulting from this project be usable in a real context, in which the databases have dimensions in the order of millions of images, and continuous growth.

BREUCA (POCI-01-0247-FEDER-048257)

logo Title: Development of a high-precision Virtual Reality simulator designed to be used in professional simulation and gaming environments associated with real events
Partners: Universidade do Minho, Bubblecode, Altice, Formula E, Kartódromo Internacional de Braga
Researchers: Sandra Jardim, António Manso, Carlos Mora, Helena Monteiro, João Patrício, Luís Merca, Manuela Fernandes, Ricardo Campos, Sérgio Rodrigues
Date: 2021-01-01 - 2023-06-30
Status: ongoing
url: website / YouTube
Description: The BREUCA project aims to develop a high-precision Virtual Reality simulator designed to be used in a gaming environment that will allow its users to compete in real-time races against racers on the track, immersing them in an environment as real as possible, that is, effectively happening anywhere in the world, and virtually in any user’s home. It is intended that changes in the real car or events of the race reverberate in an event in a virtual environment, with an error of less than 0.1 seconds. In terms of technical-scientific development, it is a project that covers three vital points of technological development: virtual reality, precision simulation, real-time game with the cars on the track.

CRASH (POCI-01-0247-FEDER-070315)

logo Title: Development of a high precision reconstruction system designed to be used in a professional simulation environment related with real crash events
Partners: Instituto Politécnico de Leiria, Igor Sikorsky Kyiv Polytechnic Institute
Researchers: Sandra Jardim, António Manso, Carlos Mora, João Patrício, Luís Ferreira, Luís Merca, Sérgio Rodrigues
Date: 2021-01-01 - 2023-06-30
Status: ongoing
url: website / YouTube
Description: The CRASH project aims the research in the area of Data Science, 3D Simulation, Artificial Intelligence and Software Engineering, proposing the development of a fully functional prototype that provides a high-precision virtual reconstruction, description and diagnosis of the causes of road accidents. The project envisages the development of a 3D scanning system for vehicles, with a precise definition of the deformations suffered during an accident, and the development of an accident scene simulation system, with the identification of all forensic evidence of accidents and their measurement definition. The implementation of artificial intelligence models will provide the system with the ability to relate 3D objects and evidence from other sources of information (sensors), allowing the reconstruction of the entire timeline of the accident, combining data and relevant 3D objects, and making it possible to include at any time in the timeline mechanical and dynamic models of relevant vehicles, related to any type of 3D object. Accident reconstruction will be based on the definition of mechanical equations of kinematic and dynamic behavior of physical models resulting from 3D digitization. It is also foreseen the integration of the information registered in the vehicles to feed the dynamic behavior of the vehicle and the behavior of the driver.

Dragonfly (UIDP/05567/2020/02)

logo Title: Implementation of a mobile robotic surface water quality monitoring system
Partners: CIMT
Researchers: Manuel Barros, Carlos Ferreira, Pedro Granchinho, Pedro Neves, Hugo Magalhães, Henrique Pinho
Date: 2020-06-01 - 2023-12-31
Status: ongoing
url: YouTube
Description: The aim of the Dragonfly project is to implement enabling technologies for the deployment, and management of a cost-effective mobile remote sensing framework (or cyber physical system) for monitoring freshwater quality towards water reservoirs protection against pollution. The module is composed of several sub-systems optimized for the collection of relevant water quality data and its transmission in real time to a central monitoring and control unit. The data will make it possible to identify sources of contamination and its evolution, being, therefore, a decision-making tool to trigger environmental protection mechanisms and lead to the rapid identification of the origins of the problem(s) and their respective resolution.

H2-REnWaste (UIDP/05567/2020/01)

logo Title: Production of Hydrogen with Renewable Energy using Wastewater
Partners: CIMT
Researchers: Paulo Coelho, Mário Gomes, Henrique Pinho, José Fernandes, Valentim Nunes, Marco Cartaxo, Carlos Pereira
Date: 2020-06-01 - 2023-12-31
Status: ongoing
url: YouTube
Description: The H2-REnWast project will install an electrolyser at the IPT campus. In order to explore the potential of producing Green Hydrogen, the electrolyser will be integrated with the IPT solar farm (photovoltaic - PV), hydrogen storage and a small fuel cell for re-electrification. For this purpose, in addition to using energy from renewable sources (Green H2), in order to make the process even “Greener”, and so as to maximise relevance, wastewater will be used in the hydrogen production process. Thus, the treatment of wastewater is necessary to achieve high hydrogen purity and efficiency of process. The plant will be operated in multiple emulated configurations (energy storage, microgrid, fuel production). Hydrogen is increasingly seen as a very important energy vector, both at European and national level. IPT is part of a working group created by the CIMT to turn the Médio Tejo into a “Hydrogen Region”.

SmartBASE (UIDB/05567/2020/00)

logo Title: Backbone And Support Environment for Smart Projects
Partners: NA
Researchers: Luís M. L. Oliveira, Renato Panda, Pedro Correia, Paulo Coelho, Henrique Pinho
Date: 2020-06-01 - 2023-12-31
Status: ongoing
url: YouTube
Description: The project goal consists in the implementation of shared hardware and software resources available for all Ci2 projects and thematic areas.

SmarterCW (UIDP/05567/2020/03)

logo Title: Smart monitoring of constructed wetlands and other green wastewater treatment technologies to improve efficiency and water quality
Partners: NA
Researchers: Henrique Pinho, Luís M. L. Oliveira, Manuel Barros, Carlos Ferreira, Dina Mateus
Date: 2020-06-01 - 2023-12-31
Status: ongoing
url: YouTube

Description: The project aims the create a framework to provide the monitoring of biological wastewater treatment processes through the gathering of continuous data from remote water and environmental sensors. The acquired data can be processed and analysed through data analytics tools to provide a better understanding of the complex and coupled phenomena underneath wastewater treatment. The results will allow for improving the efficiency and control of green wastewater treatment technologies.


 

 
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