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Dr. Joao C Ferreira
Iscte - Instituto Universitário de Lisboa

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0 Data Science
0 Health Systems
0 Social Network Analysis
0 Blockchain
0 IoT

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IoT
Blockchain

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Journal article
Published: 24 June 2021 in Journal of Personalized Medicine
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Currently, an echocardiography expert is needed to identify calcium in the aortic valve, and a cardiac CT-Scan image is needed for calcium quantification. When performing a CT-scan, the patient is subject to radiation, and therefore the number of CT-scans that can be performed should be limited, restricting the patient’s monitoring. Computer Vision (CV) has opened new opportunities for improved efficiency when extracting knowledge from an image. Applying CV techniques on echocardiography imaging may reduce the medical workload for identifying the calcium and quantifying it, helping doctors to maintain a better tracking of their patients. In our approach, a simple technique to identify and extract the calcium pixel count from echocardiography imaging, was developed by using CV. Based on anonymized real patient echocardiographic images, this approach enables semi-automatic calcium identification. As the brightness of echocardiography images (with the highest intensity corresponding to calcium) vary depending on the acquisition settings, echocardiographic adaptive image binarization has been performed. Given that blood maintains the same intensity on echocardiographic images—being always the darker region—blood areas in the image were used to create an adaptive threshold for binarization. After binarization, the region of interest (ROI) with calcium, was interactively selected by an echocardiography expert and extracted, allowing us to compute a calcium pixel count, corresponding to the spatial amount of calcium. The results obtained from these experiments are encouraging. With this technique, from echocardiographic images collected for the same patient with different acquisition settings and different brightness, obtaining a calcium pixel count, where pixel values show an absolute pixel value margin of error of 3 (on a scale from 0 to 255), achieving a Pearson Correlation of 0.92 indicating a strong correlation with the human expert assessment of calcium area for the same images.

ACS Style

Luis Elvas; Ana Almeida; Luís Rosario; Miguel Dias; João Ferreira. Calcium Identification and Scoring Based on Echocardiography. An Exploratory Study on Aortic Valve Stenosis. Journal of Personalized Medicine 2021, 11, 598 .

AMA Style

Luis Elvas, Ana Almeida, Luís Rosario, Miguel Dias, João Ferreira. Calcium Identification and Scoring Based on Echocardiography. An Exploratory Study on Aortic Valve Stenosis. Journal of Personalized Medicine. 2021; 11 (7):598.

Chicago/Turabian Style

Luis Elvas; Ana Almeida; Luís Rosario; Miguel Dias; João Ferreira. 2021. "Calcium Identification and Scoring Based on Echocardiography. An Exploratory Study on Aortic Valve Stenosis." Journal of Personalized Medicine 11, no. 7: 598.

Journal article
Published: 24 May 2021 in Energies
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Transportation data in a smart city environment is increasingly becoming available. This data availability allows building smart solutions that are viewed as meaningful by both city residents and city management authorities. Our research work was based on Lisbon mobility data available through the local municipality, where we integrated and cleaned different data sources and applied a CRISP-DM approach using Python. We focused on mobility problems and interdependence and cascading-effect solutions for the city of Lisbon. We developed data-driven approaches using artificial intelligence and visualization methods to understand traffic and accident problems, providing a big picture to competent authorities and supporting the city in being more prepared, adaptable, and responsive, and better able to recover from such events.

ACS Style

Vitória Albuquerque; Ana Oliveira; Jorge Barbosa; Rui Rodrigues; Francisco Andrade; Miguel Dias; João Ferreira. Smart Cities: Data-Driven Solutions to Understand Disruptive Problems in Transportation—The Lisbon Case Study. Energies 2021, 14, 3044 .

AMA Style

Vitória Albuquerque, Ana Oliveira, Jorge Barbosa, Rui Rodrigues, Francisco Andrade, Miguel Dias, João Ferreira. Smart Cities: Data-Driven Solutions to Understand Disruptive Problems in Transportation—The Lisbon Case Study. Energies. 2021; 14 (11):3044.

Chicago/Turabian Style

Vitória Albuquerque; Ana Oliveira; Jorge Barbosa; Rui Rodrigues; Francisco Andrade; Miguel Dias; João Ferreira. 2021. "Smart Cities: Data-Driven Solutions to Understand Disruptive Problems in Transportation—The Lisbon Case Study." Energies 14, no. 11: 3044.

Journal article
Published: 19 May 2021 in Smart Cities
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The smart city concept, in which data from different systems are available, contains a multitude of critical infrastructures. This data availability opens new research opportunities in the study of the interdependency between those critical infrastructures and cascading effects solutions and focuses on the smart city as a network of critical infrastructures. This paper proposes an integrated resilience system linking interconnected critical infrastructures in a smart city to improve disaster resilience. A data-driven approach is considered, using artificial intelligence and methods to minimize cascading effects and the destruction of failing critical infrastructures and their components (at a city level). The proposed approach allows rapid recovery of infrastructures’ service performance levels after disasters while keeping the coverage of the assessment of risks, prevention, detection, response, and mitigation of consequences. The proposed approach has the originality and the practical implication of providing a decision support system that handles the infrastructures that will support the city disaster management system—make the city prepare, adapt, absorb, respond, and recover from disasters by taking advantage of the interconnections between its various critical infrastructures to increase the overall resilience capacity. The city of Lisbon (Portugal) is used as a case to show the practical application of the approach.

ACS Style

Luís Elvas; Bruno Mataloto; Ana Martins; João Ferreira. Disaster Management in Smart Cities. Smart Cities 2021, 4, 819 -839.

AMA Style

Luís Elvas, Bruno Mataloto, Ana Martins, João Ferreira. Disaster Management in Smart Cities. Smart Cities. 2021; 4 (2):819-839.

Chicago/Turabian Style

Luís Elvas; Bruno Mataloto; Ana Martins; João Ferreira. 2021. "Disaster Management in Smart Cities." Smart Cities 4, no. 2: 819-839.

Journal article
Published: 18 March 2021 in Energies
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We present a suitable approach to address the electric vehicle charging roaming problem (e-roaming). Blockchain technologies are applied to support the identity management process of users charging their vehicles and to record energy transactions securely. At the same time, off-chain cloud-based storage is used to record the transaction details. A user wallet settled on a mobile application stores user verified credentials; a backend application in the vehicle charging station validates the user credentials to authorize the energy transaction. The current model can be applied to similar contexts where the user may be required to keep several credentials from different providers to authenticate digital transactions.

ACS Style

Joao Ferreira; Catarina Ferreira da Silva; Jose Martins. Roaming Service for Electric Vehicle Charging Using Blockchain-Based Digital Identity. Energies 2021, 14, 1686 .

AMA Style

Joao Ferreira, Catarina Ferreira da Silva, Jose Martins. Roaming Service for Electric Vehicle Charging Using Blockchain-Based Digital Identity. Energies. 2021; 14 (6):1686.

Chicago/Turabian Style

Joao Ferreira; Catarina Ferreira da Silva; Jose Martins. 2021. "Roaming Service for Electric Vehicle Charging Using Blockchain-Based Digital Identity." Energies 14, no. 6: 1686.

Conference paper
Published: 11 March 2021 in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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The development of the Internet of Things and mobile technology is connecting people and cities and generating large volumes of geolocated and space-time data. This paper identifies patterns in the Lisbon GIRA bike-sharing system (BSS), by analyzing the spatiotemporal distribution of travel distance, speed and duration, and correlating with environmental factors, such as weather conditions. Through cluster analysis the paper finds novel insights in origin-destination BSS stations, regarding spatial patterns and usage frequency. Such findings can inform decision makers and BSS operators towards service optimization, aiming at improving the Lisbon GIRA network planning in the framework of multimodal urban mobility.

ACS Style

Vitória Albuquerque; Francisco Andrade; João Carlos Ferreira; Miguel Sales Dias. Understanding Spatiotemporal Station and Trip Activity Patterns in the Lisbon Bike-Sharing System. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2021, 16 -34.

AMA Style

Vitória Albuquerque, Francisco Andrade, João Carlos Ferreira, Miguel Sales Dias. Understanding Spatiotemporal Station and Trip Activity Patterns in the Lisbon Bike-Sharing System. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2021; ():16-34.

Chicago/Turabian Style

Vitória Albuquerque; Francisco Andrade; João Carlos Ferreira; Miguel Sales Dias. 2021. "Understanding Spatiotemporal Station and Trip Activity Patterns in the Lisbon Bike-Sharing System." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , no. : 16-34.

Conference paper
Published: 11 March 2021 in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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The world nowadays and business processes, in particular, are changing towards digitalization and reduction of time-consuming processes. Provenance and safety of products are becoming key factors for customers’ trust, so traceability solutions are arising. One of the most up-and-coming disruptive technologies today is a Blockchain (BC). The aim of this article is to provide tentative framework of how to assess the level of success of BC technology in supply chain (SC) and the methods that should be used in such assessment. The fish SC will be used to illustrate the discussion and the traceability and trust issues will be enhanced. The pilot shows that BC can promote strategic alignment, provides convenience and could be used as market leverage issue by promoting traceability and consequently trust in the product available. Methods to be used or such endeavor are suggested. A future understanding of the importance for BC technology use, as a traceability provider from the perspective of a final customer, is detected as a path for further research .

ACS Style

Ulpan Tokkozhina; Ana Lucia Martins; Joao C. Ferreira. Adopting Blockchain in Supply Chain – An Approach for a Pilot. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2021, 125 -141.

AMA Style

Ulpan Tokkozhina, Ana Lucia Martins, Joao C. Ferreira. Adopting Blockchain in Supply Chain – An Approach for a Pilot. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2021; ():125-141.

Chicago/Turabian Style

Ulpan Tokkozhina; Ana Lucia Martins; Joao C. Ferreira. 2021. "Adopting Blockchain in Supply Chain – An Approach for a Pilot." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , no. : 125-141.

Review
Published: 27 February 2021
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BACKGROUND The digital age, with ICT, IoT, and big data, has opened new opportunities for improving the delivery of healthcare services, with remote monitor systems playing a crucial role, reaching out to patients. The versatility and necessity of these systems has been demonstrated during the current COVID-19 pandemic. Health Remote Monitoring Systems (HRMS) have various advantages such as the reduction of patient load at hospitals and health centers, which is accomplished through the remote monitorization of patients. Patients that would benefit from remote monitoring are those with chronic diseases, the elderly and patients that experience less severe symptoms recovering from SARS-CoV-2 viral infection. OBJECTIVE This paper aims to perform a systematic review of the literature regarding HRMS in primary health care (PHC) settings, to identify the current status of the digitalization of the health process, the remote data acquisition and the remote interaction process between medical personnel and patients. METHODS A systematic literature review was conducted, using the PRISMA guidelines, to identify articles that explore interventions with HRMS in patients with chronic diseases in the PHC setting. The search was conducted in Scopus and Web of Science Core Collection. The studies considered to this study included (1) continuous electronic recording of patient indicators (sensors or wearables) linked to a computer system integrated into PHC centers, (2) patient input devices linked to a computer system allowing real-time data visualization for analysis by PHC professionals or (3) collection of electronic personal health/clinical data transmitted for analysis by a remote PHC professional. RESULTS The literature review yielded 123 publications, 18 of those met the predefined inclusion criteria. The selected articles highlighted that sensors and wearables are already being used in multiple scenarios related to chronic disease management at the PHC level. The studies focused mostly on patients with diabetes (34.6%) and cardiovascular diseases (26.9%). During the evaluation of the implementation of these interventions, the major difficulty that stood out was the integrating of the information in the already existing systems into the PHC infrastructures and in changing working processes of the PHC’s Professionals (83.4%). CONCLUSIONS The PHC context is specific and can integrate multidisciplinary teams and patients with often complex chronic pathologies. Despite all the theoretical framework, objective identification of problems and the involvement of stakeholders in the design and implementation processes, these interventions mostly fail to be extrapolated into a large scale. This study aimed at demonstrating the importance of matching technological development to the working methods of human resources in interventions regarding the use of sensors and wearables for remote monitoring as a source of information for chronic disease management in PHC, so that information with clinical value is not lost or even gained along the way.

ACS Style

Mariana Peyroteo; Inês Augusto Ferreira; Luís Brito Elvas; João Carlos Ferreira; Luís Velez Lapão. Healthcare Remote Monitoring Systems in patients with Chronic Diseases in Primary Health Care: A Systematic Review (Preprint). 2021, 1 .

AMA Style

Mariana Peyroteo, Inês Augusto Ferreira, Luís Brito Elvas, João Carlos Ferreira, Luís Velez Lapão. Healthcare Remote Monitoring Systems in patients with Chronic Diseases in Primary Health Care: A Systematic Review (Preprint). . 2021; ():1.

Chicago/Turabian Style

Mariana Peyroteo; Inês Augusto Ferreira; Luís Brito Elvas; João Carlos Ferreira; Luís Velez Lapão. 2021. "Healthcare Remote Monitoring Systems in patients with Chronic Diseases in Primary Health Care: A Systematic Review (Preprint)." , no. : 1.

Research article
Published: 02 February 2021 in International Transactions on Electrical Energy Systems
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This article presents a power management system (PMS) designed for smart homes aiming to deal with the new challenges imposed by the proliferation of plug‐in electric vehicles (EVs) and their coexistence with other residential electrical appliances. The PMS is based on a hybrid wireless network architecture composed by a local hub/gateway and several Bluetooth Low Energy (BLE) and Wi‐Fi sensor/actuator devices. These wireless devices are used to transfer information inside the smart home using the Message Queuing Telemetry Transport (MQTT) protocol. Based on the proposed solution, the current consumption of the EV battery charger and other residential electrical appliances are dynamically monitored and controlled by using a configurable algorithm, ensuring that the total current consumption does not cause the tripping of the home circuit breaker. An Android client application allows the user to monitor and configure the system operation in real‐time, a developed Wi‐Fi smart plug permits to measure the RMS values of current of the connected electrical appliance and change its state of operation remotely, and an EV battery charger may be controlled in terms of operating power according to set‐points received from the Android client application. Experimental tests are used to evaluate the quality of service provided by the developed smart home platform in terms of communication delay and reliability. An experimental validation for different conditions of operation of the proposed smart home PMS concerning the power operation of the EV battery charger with the proposed control algorithm is also presented.

ACS Style

Ruben E. Figueiredo; Vitor Monteiro; Joao C. Ferreira; Joao L. Afonso; Jose A. Afonso. Smart home power management system for electric vehicle battery charger and electrical appliance control. International Transactions on Electrical Energy Systems 2021, 31, e12812 .

AMA Style

Ruben E. Figueiredo, Vitor Monteiro, Joao C. Ferreira, Joao L. Afonso, Jose A. Afonso. Smart home power management system for electric vehicle battery charger and electrical appliance control. International Transactions on Electrical Energy Systems. 2021; 31 (4):e12812.

Chicago/Turabian Style

Ruben E. Figueiredo; Vitor Monteiro; Joao C. Ferreira; Joao L. Afonso; Jose A. Afonso. 2021. "Smart home power management system for electric vehicle battery charger and electrical appliance control." International Transactions on Electrical Energy Systems 31, no. 4: e12812.

Journal article
Published: 01 February 2021 in Sustainability
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Energy consumption in buildings depends on the local climate, building characteristics, and user behavior. Focusing on user interaction, this research work developed a novel approach to monitoring and interaction with local users by providing in situ context information through graphic descriptions of energy consumption and indoor/outdoor environment parameters: temperature, luminosity, and humidity, which are routinely measured in real-time and stored to identify consumption patterns and other savings actions. To involve local users, collected data are represented in 3D color representation using building 3d models. A simplified color scale depicts environmental comfort (low/comfortable/high temperature/relative humidity) and energy consumption (above/below usual patterns). We found that these indices induced user commitment and increased their engagement and participation in saving actions like turning off lights and better management of air conditioning systems.

ACS Style

Bruno Mataloto; Daniel Calé; Kaiser Carimo; Joao Ferreira; Ricardo Resende. 3D IoT System for Environmental and Energy Consumption Monitoring System. Sustainability 2021, 13, 1495 .

AMA Style

Bruno Mataloto, Daniel Calé, Kaiser Carimo, Joao Ferreira, Ricardo Resende. 3D IoT System for Environmental and Energy Consumption Monitoring System. Sustainability. 2021; 13 (3):1495.

Chicago/Turabian Style

Bruno Mataloto; Daniel Calé; Kaiser Carimo; Joao Ferreira; Ricardo Resende. 2021. "3D IoT System for Environmental and Energy Consumption Monitoring System." Sustainability 13, no. 3: 1495.

Journal article
Published: 18 December 2020 in Applied Sciences
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This paper presents DisBot, the first Portuguese speaking chatbot that uses social media retrieved knowledge to support citizens and first-responders in disaster scenarios, in order to improve community resilience and decision-making. It was developed and tested using Design Science Research Methodology (DSRM), being progressively matured with field specialists through several design and development iterations. DisBot uses a state-of-the-art Dual Intent Entity Transformer (DIET) architecture to classify user intents, and makes use of several dialogue policies for managing user conversations, as well as storing relevant information to be used in further dialogue turns. To generate responses, it uses real-world safety knowledge, and infers a dynamic knowledge graph that is dynamically updated in real-time by a disaster-related knowledge extraction tool, presented in previous works. Through its development iterations, DisBot has been validated by field specialists, who have considered it to be a valuable asset in disaster[d=JB] -management.

ACS Style

João Boné; João C. Ferreira; Ricardo Ribeiro; Gonçalo Cadete. DisBot: A Portuguese Disaster Support Dynamic Knowledge Chatbot. Applied Sciences 2020, 10, 9082 .

AMA Style

João Boné, João C. Ferreira, Ricardo Ribeiro, Gonçalo Cadete. DisBot: A Portuguese Disaster Support Dynamic Knowledge Chatbot. Applied Sciences. 2020; 10 (24):9082.

Chicago/Turabian Style

João Boné; João C. Ferreira; Ricardo Ribeiro; Gonçalo Cadete. 2020. "DisBot: A Portuguese Disaster Support Dynamic Knowledge Chatbot." Applied Sciences 10, no. 24: 9082.

Journal article
Published: 22 November 2020 in Applied Sciences
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Buildings in Lisbon are often the victim of several types of events (such as accidents, fires, collapses, etc.). This study aims to apply a data-driven approach towards knowledge extraction from past incident data, nowadays available in the context of a Smart City. We apply a Cross Industry Standard Process for Data Mining (CRISP-DM) approach to perform incident management of the city of Lisbon. From this data-driven process, a descriptive and predictive analysis of an events dataset provided by the Lisbon Municipality was possible, together with other data obtained from the public domain, such as the temperature and humidity on the day of the events. The dataset provided contains events from 2011 to 2018 for the municipality of Lisbon. This data mining approach over past data identified patterns that provide useful knowledge for city incident managers. Additionally, the forecasts can be used for better city planning, and data correlations of variables can provide information about the most important variables towards those incidents. This approach is fundamental in the context of smart cities, where sensors and data can be used to improve citizens’ quality of life. Smart Cities allow the collecting of data from different systems, and for the case of disruptive events, these data allow us to understand them and their cascading effects better.

ACS Style

Luís B. Elvas; Carolina F. Marreiros; João M. Dinis; Maria C. Pereira; Ana L. Martins; João C. Ferreira. Data-Driven Approach for Incident Management in a Smart City. Applied Sciences 2020, 10, 8281 .

AMA Style

Luís B. Elvas, Carolina F. Marreiros, João M. Dinis, Maria C. Pereira, Ana L. Martins, João C. Ferreira. Data-Driven Approach for Incident Management in a Smart City. Applied Sciences. 2020; 10 (22):8281.

Chicago/Turabian Style

Luís B. Elvas; Carolina F. Marreiros; João M. Dinis; Maria C. Pereira; Ana L. Martins; João C. Ferreira. 2020. "Data-Driven Approach for Incident Management in a Smart City." Applied Sciences 10, no. 22: 8281.

Journal article
Published: 02 September 2020 in Applied Sciences
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This research is aimed at creating and presenting DisKnow, a data extraction system with the capability of filtering and abstracting tweets, to improve community resilience and decision-making in disaster scenarios. Nowadays most people act as human sensors, exposing detailed information regarding occurring disasters, in social media. Through a pipeline of natural language processing (NLP) tools for text processing, convolutional neural networks (CNNs) for classifying and extracting disasters, and knowledge graphs (KG) for presenting connected insights, it is possible to generate real-time visual information about such disasters and affected stakeholders, to better the crisis management process, by disseminating such information to both relevant authorities and population alike. DisKnow has proved to be on par with the state-of-the-art Disaster Extraction systems, and it contributes with a way to easily manage and present such happenings.

ACS Style

João Boné; Mariana Dias; João C. Ferreira; Ricardo Ribeiro. DisKnow: A Social-Driven Disaster Support Knowledge Extraction System. Applied Sciences 2020, 10, 6083 .

AMA Style

João Boné, Mariana Dias, João C. Ferreira, Ricardo Ribeiro. DisKnow: A Social-Driven Disaster Support Knowledge Extraction System. Applied Sciences. 2020; 10 (17):6083.

Chicago/Turabian Style

João Boné; Mariana Dias; João C. Ferreira; Ricardo Ribeiro. 2020. "DisKnow: A Social-Driven Disaster Support Knowledge Extraction System." Applied Sciences 10, no. 17: 6083.

Journal article
Published: 18 August 2020 in Applied Sciences
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People in shared building space have an important role in energy consumption because they can turn on/off equipment and heat/cooling systems. This behaviour can be influenced by giving then locally tailored context information (energy consumption, temperature, luminosity) and information about the cost of their actions. This paper presents an approach to create personalized local energy consumption predictions in a building using past sensor data, correlated with external conditions to create local context predictions. This prediction is sent in real-time to people’s mobile devices in order to influence their behaviour when increasing or decreasing temperature using heating or cooling systems. This information is essential for sustainability actions in shared spaces, where this information can have an important role. Also, the data (temperature) representation in the building information model (BIM) module can help the user understand environment conditions and, together with the user sharing their thermal feelings, can be used to change behaviour. This approach using BIM’s representation models allows Things2People interaction to improve energy savings in these shared spaces.

ACS Style

Bruno Mataloto; Hugo Miguel Nogueira Mendes; Joao C. Ferreira. Things2People Interaction toward Energy Savings in Shared Spaces Using BIM. Applied Sciences 2020, 10, 5709 .

AMA Style

Bruno Mataloto, Hugo Miguel Nogueira Mendes, Joao C. Ferreira. Things2People Interaction toward Energy Savings in Shared Spaces Using BIM. Applied Sciences. 2020; 10 (16):5709.

Chicago/Turabian Style

Bruno Mataloto; Hugo Miguel Nogueira Mendes; Joao C. Ferreira. 2020. "Things2People Interaction toward Energy Savings in Shared Spaces Using BIM." Applied Sciences 10, no. 16: 5709.

Journal article
Published: 11 June 2020 in Applied Sciences
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Performance Evaluation is a process that occurs multiple times per year on a company. During this process, the manager and the salesperson evaluate how the salesperson performed on numerous Key Performance Indicators (KPIs). To prepare the evaluation meeting, managers have to gather data from Customer Relationship Management System, Financial Systems, Excel files, among others, leading to a very time-consuming process. The result of the Performance Evaluation is a classification followed by actions to improve the performance where it is needed. Nowadays, through predictive analytics technologies, it is possible to make classifications based on data. In this work, the authors applied a Naive Bayes model over a dataset that is composed by sales from 594 salespeople along 3 years from a global freight forwarding company, to classify salespeople into pre-defined categories provided by the business. The classification is done in 3 classes, being: Not Performing, Good, and Outstanding. The classification was achieved based on KPI’s like growth volume and percentage, sales variability along the year, opportunities created, customer base line, target achievement among others. The authors assessed the performance of the model with a confusion matrix and other techniques like True Positives, True Negatives, and F1 score. The results showed an accuracy of 92.50% for the whole model.

ACS Style

Nelito Calixto; João Ferreira. Salespeople Performance Evaluation with Predictive Analytics in B2B. Applied Sciences 2020, 10, 4036 .

AMA Style

Nelito Calixto, João Ferreira. Salespeople Performance Evaluation with Predictive Analytics in B2B. Applied Sciences. 2020; 10 (11):4036.

Chicago/Turabian Style

Nelito Calixto; João Ferreira. 2020. "Salespeople Performance Evaluation with Predictive Analytics in B2B." Applied Sciences 10, no. 11: 4036.

Journal article
Published: 24 May 2020 in Sensors
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In this research work, we present an IoT solution to environment variables using a LoRa transmission technology to give real-time information to users in a Things2People process and achieve savings by promoting behavior changes in a People2People process. These data are stored and later processed to identify patterns and integrate with visualization tools, which allow us to develop an environmental perception while using the system. In this project, we implemented a different approach based on the development of a 3D visualization tool that presents the system collected data, warnings, and other users’ perception in an interactive 3D model of the building. This data representation introduces a new People2People interaction approach to achieve savings in shared spaces like public buildings by combining sensor data with the users’ individual and collective perception. This approach was validated at the ISCTE-IUL University Campus, where this 3D IoT data representation was presented in mobile devices, and from this, influenced user behavior toward meeting campus sustainability goals.

ACS Style

Bruno Mataloto; João Ferreira; Ricardo Resende; Rita Moura; Sílvia Luís. BIM in People2People and Things2People Interactive Process. Sensors 2020, 20, 2982 .

AMA Style

Bruno Mataloto, João Ferreira, Ricardo Resende, Rita Moura, Sílvia Luís. BIM in People2People and Things2People Interactive Process. Sensors. 2020; 20 (10):2982.

Chicago/Turabian Style

Bruno Mataloto; João Ferreira; Ricardo Resende; Rita Moura; Sílvia Luís. 2020. "BIM in People2People and Things2People Interactive Process." Sensors 20, no. 10: 2982.

Conference paper
Published: 04 May 2020 in Transactions on Petri Nets and Other Models of Concurrency XV
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With the development of new technologies and methodologies, multiple sectors start to experience the benefits and drawbacks. Currently, the industry is facing a new revolution known as Industry 4.0. This new path al-lowed all enterprises to further develop their methodologies and understand the disadvantages and advantages of it. With the sole purpose of retaining costs in production while maintaining the same degree of quality, companies desire to diminish their downtime due to malfunction or improper maintenance schedules that may not amount to the desired efficiency. Nevertheless, not all companies manage to enter this exclusive circle, since such technologies also deliver a high cost which some companies simply cannot support. Consequently, this generates a huge drawback to the outsiders of this revolution.

ACS Style

João Silva; João Carlos Ferreira; Frederica Gonçalves. The ‘‘aftermath’’ of Industry 4.0 in Small and Medium Enterprises. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 26 -33.

AMA Style

João Silva, João Carlos Ferreira, Frederica Gonçalves. The ‘‘aftermath’’ of Industry 4.0 in Small and Medium Enterprises. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():26-33.

Chicago/Turabian Style

João Silva; João Carlos Ferreira; Frederica Gonçalves. 2020. "The ‘‘aftermath’’ of Industry 4.0 in Small and Medium Enterprises." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 26-33.

Review
Published: 09 April 2020 in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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The electric mobility dissemination is forcing the adoption of new technologies and operation paradigms, not only focusing on smart grids, but also on smart homes. In fact, the emerging technologies for smart homes are also altering the conventional grids toward smart grids. By combining the key pillars of electric mobility and smart homes, this paper characterizes the paradigms of the electric vehicle (EV) in smart homes, presenting a review about the state-of-the-art and establishing a relation with future perspectives. Since the smart home must be prepared to deal with the necessities of the EV, the analysis of both on-board and off-board battery charging systems are considered in the paper. Moreover, the inclusion of renewable energy sources, energy storage systems, and dc electrical appliances in smart homes towards sustainability is also considered in this paper, but framed in the perspective of an EV off-board battery charging system. As a pertinent contribution, this paper offers future perspectives for the EV in smart homes, including the possibility of ac, dc, and hybrid smart homes. Covering all of these aspects, exemplificative and key results are presented based on numerical simulations and experimental results obtained with a proof-of-concept prototype.

ACS Style

Vitor Monteiro; Jose A. Afonso; Joao Carlos Amaro Ferreira; Tiago J. C. Sousa; Joao L. Afonso. The Electric Vehicle in Smart Homes: A Review and Future Perspectives. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020, 3 -17.

AMA Style

Vitor Monteiro, Jose A. Afonso, Joao Carlos Amaro Ferreira, Tiago J. C. Sousa, Joao L. Afonso. The Electric Vehicle in Smart Homes: A Review and Future Perspectives. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2020; ():3-17.

Chicago/Turabian Style

Vitor Monteiro; Jose A. Afonso; Joao Carlos Amaro Ferreira; Tiago J. C. Sousa; Joao L. Afonso. 2020. "The Electric Vehicle in Smart Homes: A Review and Future Perspectives." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , no. : 3-17.

Conference paper
Published: 09 April 2020 in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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The Internet of Things (IoT) is applied to many cases on the topic of smart cities. In the scope of this paper, we apply a flexible IoT-Developed platform, using LoRa communication, applied to university auditoriums in order to try and find patterns and/or anomalies in energy consumption and in the interior temperature. This platform enables the interested parties to monitor the energy consumption of lighting, of HVAC (Heating, Ventilation, and Air Conditioning) and if electrical plugs alongside the monitoring of temperatures, aiming to create a report about the efficient, the thermal insulation and the HVAC behavior. Based on the acquired information, a management strategy is applied to find that the lack of certain systems leads to an extreme waste of energy and the lack of proper cleaning procedures can lead to decreasing the efficiency of the HVAC.

ACS Style

Diogo Santos; Bruno Mataloto; Joao Carlos Amaro Ferreira; Vítor Monteiro; João L. Afonso. Smart Auditorium: Development and Analysis of a Power and Environment Monitoring Platform. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020, 73 -87.

AMA Style

Diogo Santos, Bruno Mataloto, Joao Carlos Amaro Ferreira, Vítor Monteiro, João L. Afonso. Smart Auditorium: Development and Analysis of a Power and Environment Monitoring Platform. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2020; ():73-87.

Chicago/Turabian Style

Diogo Santos; Bruno Mataloto; Joao Carlos Amaro Ferreira; Vítor Monteiro; João L. Afonso. 2020. "Smart Auditorium: Development and Analysis of a Power and Environment Monitoring Platform." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , no. : 73-87.

Journal article
Published: 27 March 2020 in Applied Sciences
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The process of protecting sensitive data is continually growing and becoming increasingly important, especially as a result of the directives and laws imposed by the European Union. The effort to create automatic systems is continuous, but, in most cases, the processes behind them are still manual or semi-automatic. In this work, we have developed a component that can extract and classify sensitive data, from unstructured text information in European Portuguese. The objective was to create a system that allows organizations to understand their data and comply with legal and security purposes. We studied a hybrid approach to the problem of Named Entity Recognition for the Portuguese language. This approach combines several techniques such as rule-based/lexical-based models, machine learning algorithms, and neural networks. The rule-based and lexical-based approaches were used only for a set of specific classes. For the remaining classes of entities, two statistical models were tested—Conditional Random Fields and Random Forest and, finally, a Bidirectional-LSTM approach as experimented. Regarding the statistical models, we realized that Conditional Random Fields is the one that can obtain the best results, with a f1-score of 65.50%. With the Bi-LSTM approach, we have achieved a result of 83.01%. The corpora used for training and testing were HAREM Golden Collection, SIGARRA News Corpus, and DataSense NER Corpus.

ACS Style

Mariana Dias; João Boné; João C. Ferreira; Ricardo Ribeiro; Rui Maia. Named Entity Recognition for Sensitive Data Discovery in Portuguese. Applied Sciences 2020, 10, 2303 .

AMA Style

Mariana Dias, João Boné, João C. Ferreira, Ricardo Ribeiro, Rui Maia. Named Entity Recognition for Sensitive Data Discovery in Portuguese. Applied Sciences. 2020; 10 (7):2303.

Chicago/Turabian Style

Mariana Dias; João Boné; João C. Ferreira; Ricardo Ribeiro; Rui Maia. 2020. "Named Entity Recognition for Sensitive Data Discovery in Portuguese." Applied Sciences 10, no. 7: 2303.

Conference paper
Published: 10 January 2020 in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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This research work presents a prototype model, focused on an android application, to handle the problem of finding an available parking space during driving process for all type of road vehicles in a city using historical data and prediction methods, where there is not any type of real-time system to provide information about the current state of the parking lot. Different source data integration were performed to improve the process of prediction, namely events in the surrounding areas, traffic information on the vicinity of the park and weather conditions on the city of the parking lot. This type of system aims to help users on a daily basis to find an available parking space, such as recommending the best parking lot taking into account some heuristics used by the decision algorithm, and creating a route to it, this way removing some anxiety felt by drivers looking for available spaces.

ACS Style

Gonçalo Alface; Joao C. Ferreira; Ruben Pereira. App Guidance for Parking Occupation Prediction. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020, 172 -191.

AMA Style

Gonçalo Alface, Joao C. Ferreira, Ruben Pereira. App Guidance for Parking Occupation Prediction. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2020; ():172-191.

Chicago/Turabian Style

Gonçalo Alface; Joao C. Ferreira; Ruben Pereira. 2020. "App Guidance for Parking Occupation Prediction." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , no. : 172-191.