/*----------------------------*/ MIBIS - ISCTE, Master in Integrated Business Intelligence Systems

Roaming Service for Electric Vehicle Charging Using Blockchain-Based Digital Identity

 

Abstract

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. View Full-Text
 

 


 

Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL

 

Smart Cities: Data-Driven Solutions to Understand Disruptive Problems in Transportation—The Lisbon Case Study

 

Abstract

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. View Full-Text

 


 

Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL

 

Planning process for an operational management platform for a public transport

 Abstract

This work addresses the planning process of a public passenger transport operator, including the generation of schedules and services for vehicles and drivers, in the framework of a previously agreed service. This problem will be studied in the context of all stages of the planning process: parameterization, preparation, production of performance indicators and the generation of results for different operational scenarios. View Full-Text

 


 

Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL

 

Context aware advisor for public transportation

 Abstract

This paper presents an Android-based mobile app designed to provide real time context aware public transportation information and advice to its users through the combination of the user’s preferences and geographic context with data retrieved from a public transportation information system called XTraN Passenger. Thus, this mobile app contributes to fulfill the necessities of the passengers, and also provides an incentive for people to use the public transportation infrastructure more frequently. The proposed mobile app allows the users to benefit from the access to real time public transportation data in a simple and intuitive way. The validation of the features and operation of the developed app was assessed with results from use cases and real-world experimental tests using public transportation data from a Brazilian bus fleet operator. View Full-Text

Index TermsGeographic Information System, Global Positioning System, Intelligent Transportation System, Mobile App, Personalization,Real Time Information.

 


 

Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL

 

Extracting Clinical Knowledge from Electronic Medical Records

 Abstract

As the adoption of Electronic Medical Records (EMRs) rises in the healthcare institutions, these resourcesimportance increases because of the clinical information they contain about patients. However, the unstructured information in the form of clinical narratives present in those records, makes it hard to extract and structure useful clinical knowledge. This unstructured information limits the potential of the EMRs, because the clinical information these records contain can be used to perform important tasks inside healthcare institutions such as searching, summarization, decision support and statistical analysis, as well as be used to support management decisions or serve for research. These tasks can only be done if the unstructured clinical information from the narratives is properly extracted, structured and transformed in clinical knowledge. Usually, this extraction is made manually by healthcare practitioners, which is not efficient and is error-prone. This research uses Natural Language Processing (NLP) and Information Extraction (IE) techniques, in order to develop a pipeline system that can extract clinical knowledge from unstructured clinical information present in Portuguese EMRs, in an automated way, in order to help EMRs to fulfil their potential.  View Full-Text

 Keywords Information Extraction, Knowledge Extraction, Natural Language Processing, Text Mining


 


Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL

 

An Energy Management Platform for Public Buildings

 

Abstract

This paper describes the development and implementation of an electronic platform for energy management in public buildings. The developed platform prototype is based on the installation of a network of wireless sensors using the emerging Long Range (LoRa) low power long-range wireless network technology. This network is used to collect sensor data, which is stored online and manipulated to extract knowledge and generate actions toward energy saving solutions. In this process, gamification approaches were used to motivate changes in the users’ behavior towards more sustainable actions in public buildings. These actions and the associated processes can be implemented as public services, and they can be replicated to different public buildings, contributing to a more energy-sustainable world. The developed platform allows the monitoring and management of the heating/cooling, electric power consumption, and lighting levels. In order to validate the proposed electronic platform, sensor information was collected in the context of a university campus, which was used as an application scenario in public buildings. View Full-Text
 
 

Disaster Management in Smart Cities

 

Abstract

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. View Full-Text
 
 
 

Calcium Identification and Scoring Based on Echocardiography. An Exploratory Study on Aortic Valve Stenosis

 

Abstract

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. View Full-Text
 

Summer School 2021 – IoT for Heatlhy Smart Cities

 

ISTAR, an R&D Unit of ISCTE along with its Internet of Everything Lab, will provide a 2-week intensive Summer School on 

IoT technologies and applications with focus on Health applications for Smart Cities. 

See: https://istar.iscte-iul.pt/summerschool2021/ 

  

Participantes will be acquainted with emergent computing paradigms, technologies, 

services and business models associated with Internet of Things (IoT). 

  

The  objective  of  this  school  is  provide interested participants with theoretical-practical  and 

 experimental  knowledge  about  key IoT technologies and user-centered co-creation design methodologies, for development of intelligent systems towards healthy smart cities. 

  

The school provides an overview of future trends and ongoing research in this fast-growing area: 

·         Study the principles, research problems and applications of device, software and IoT 

·         Acquire experience with IoT technologies and operating systems 

·         Understand, in practical experience, how to run user-centered projects based in Design Thinking 

·         Help students to develop self-study skills to keep up with the rapidly changing technologies, tools and techniques in this knowledge area. 

  

  

The school runs  from September 6th to 17th 2021, and consists of 10 hours of expert lectures, anchored by 19 1/2 hours of hands-on training on key topics that include: 

·         Introduction to  IoT 

·         Design Thinking 

·         Security 

·         Tiny Machine Learning and Applications 

·         Applications and challenges on Health and Crowdsourcing 

·         There is an industrial session with presentations by three companies in Portugal that develop and apply IoT techniques. 

  

Participants will work on supervised, hands-on projects, developed at the ISTAR Internet of Everything Lab, 

as well as provided basic training on:  

·         IoT frameworks (e.g. Arduino, LORA communications, and sensors) 

·         Data science tools (Python, Data Analytics introduction) 

·         Design Thinking methodologies

  

Duration: 10 days | 6 ECTS 

  

More information:  https://istar.iscte-iul.pt/summerschool2021/ 

 

Pre-Registration is already open!  Express your interest at 

https://forms.office.com/pages/responsepage.aspx?id=YOgwYsW_lUCmvBBHIa3W5qX3JiiyZRBCsWIM63R8PKpUQ1dFUDgxSzJENDNKS0laNjVDQjRaUlg5Ny4u 

 

 Questions?  pre-award.istar@iscte-iul.pt 




Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL

 

 

DisBot: A Portuguese Disaster Support Dynamic Knowledge Chatbot

Abstract


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 management
. View Full-Text

Publication regarding the second artifact (work held in Chapter 4 and the artifact’s validation of Chapter 5) of the MSc thesis in MIBIS, from Boné J.

 

Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL




DisKnow: A Social-Driven Disaster Support Knowledge Extraction System

Abstract


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.
View Full-Text

Publication regarding the first artifact (work held in Chapter 3) of the MSc thesis in MIBIS, from Boné J.

 

Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL



Data-Driven Approach for Incident Management in a Smart City

Abstract

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. View Full-Text


Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL




Open session SUSTAINABLE CITIES: Viewpoints of the Pioneer Alliance

 

FREE ACCESS
I would like to inform that today, October 21, between 2:00 p.m. and 4:00 p.m., the open session SUSTAINABLE CITIES: Viewpoints of the Pioneer Alliance will take place at ISCTE, Auditorium Silva Leal and online, in the context of the school IoT for Smart Cities.
The program of the Session is on the website, with the intervention of representatives of several European Universities: http://istar.iscte-iul.pt/summerschool2020/.

You can watch it online, via Zoom, at the link: https://videoconf-colibri.zoom.us/j/94732758415?pwd=bWZFL09VS2NSTDJmbm1DK2dqOFZZdz09







Beacons and BIM Models for Indoor Guidance and Location

This research work uses a simplified approach to combine location information from a beacon’s propagation signal interaction with a mobile device sensor (accelerometer and gyroscope) with local building information to give real-time location and guidance to a user inside a building. This is an interactive process with visualisation information that can help user’s orientation inside unknown buildings and the data stored from different users can provide useful information about users’ movements inside a public building. Beacons installed on the building at specific pre-defined positions emit signals that give a geographic position with an associated imprecision, related with Bluetooth’s range. This uncertainty is handled by building layout and users’ movement in a developed system that maps users’ position, gives guidance, and stores user movements. This system is based on an App (Find Me!) for Android OS (Operating System) which captures the Bluetooth Low Energy (BLE) signal coming from the beacon(s) and shows, through a map, the location of the user’s smartphone and guide him to the desired destination. Also, the beacons can deliver relevant context information. The application was tested by a panel of new and habitual campus users against traditional wayfinding alternatives yielding navigation times about 30% smaller, respectively. View Full-Text

Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL






Assessment of perceived quality: comparison of sports apparel retail chains

Sports apparel retail is a very competitive industry in Portugal and is dominated by two main players that continuously seek to capture more customers. The quality of the service provided is a key issue for a company to succeed in the market. Although service quality has been explored in literature, its link to the value proposition of the retail stores is still missing. This research aims at analyzing the adequacy of the service provided by each of these main players to customers’ desires in a comparative way. Customers’ perceived quality is assessed as well as suitability of companies’ desired benefits for the customers. Data was collected using interviews and a customer questionnaire. A sample of 423 responses is used. Conclusions showed that Decathlon has a better fit to customers’ desires as well as better perceived quality than Sports Zone. Specific managerial recommendations for the improvement of the service quality are provided for both companies. View Full Text


Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL





Merging Data Diversity of Clinical Medical Records to Improve Effectiveness

Medicine is a knowledge area continuously experiencing changes. Every day, discoveries and procedures are tested with the goal of providing improved service and quality of life to patients. With the evolution of computer science, multiple areas experienced an increase in productivity with the implementation of new technical solutions. Medicine is no exception. Providing healthcare services in the future will involve the storage and manipulation of large volumes of data (big data) from medical records, requiring the integration of different data sources, for a multitude of purposes, such as prediction, prevention, personalization, participation, and becoming digital. Data integration and data sharing will be essential to achieve these goals. Our work focuses on the development of a framework process for the integration of data from different sources to increase its usability potential. We integrated data from an internal hospital database, external data, and also structured data resulting from natural language processing (NPL) applied to electronic medical records. An extract-transform and load (ETL) process was used to merge different data sources into a single one, allowing more effective use of these data and, eventually, contributing to more efficient use of the available resources. View Full-Text








MORE INTELLIGENT CITIES WITH TECHNOLOGY AND SOCIAL SCIENCES

"Projects on Smart Cities and Internet of Things involve the various ISCTE-IUL schools and are being developed in the scope of Master's and Doctorate degrees, besides partnerships with companies and other entities.

João FerreiraISTAR Researcher

When I make intelligent and efficient use of the lighting or air conditioning system in my home, I have a clear reward by reducing the bill I pay at the end of the month. When a city council does the same in the lighting network of a city, the municipal budget benefits from this policy. But what happens in spaces, such as hospitals, public offices or universities, where users are not individually rewarded for efficient behavior? What mechanisms can lead these very diverse users to behave with greater environmental responsibility and also with greater energy efficiency and, therefore, economic efficiency?

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INTERNET OF THINGS, IoT

Digitization, the Internet of Things (IoT) and 5G communications can be powerful tools to achieve this behavior change. They allow collecting and processing huge amounts of data, in real time, and from them establishing patterns and trends. But what to do with this data, if we are dealing with a set of diverse users, to whom it is not possible to propose systematic and structured solutions?

To answer this question, specialists in Information Science and Technology need the support of other scientific knowledge, such as sociology or psychology, capable of studying and standardizing collective and individual behaviors, but above all, of advancing with the necessary tools to propose behavioral change models oriented to specific users. And this is precisely what is being done at the Iscte's Center for Research in Information Sciences, Technologies and Architecture (ISTAR).

"ISTAR bets on multidisciplinarity to find innovative solutions to the current challenges in the areas of intelligent cities, digital transformation and societal challenges, always focusing on sustainable development, both ecological and social and economic," says Sara Eloy, director of the Center.

The project, coordinated by João Ferreira, from ISTAR, and financed by the Calouste Gulbenkian Foundation, is using Iscte's facilities as a research field, by monitoring the use, from the energy point of view, of areas such as classrooms, auditoriums and administrative spaces. Through sensors and the transmission of data in real time it is possible to have context data of the reality that surrounds us, be it temperature, humidity, luminosity, energy consumption, noise, air quality or the simple presence of people. This data, in addition to providing a snapshot of reality, allows, through further analysis, to identify inefficiencies and waste and thus reduce costs.

The project uses an application for mobile devices, with data representation in 3D models, introduced by the multidisciplinary team in which the AEC (Architecture, Engineering and Construction) played a very important role with the Building Information Modeling (BIM) models. This visually appealing environment allows modeling individual behaviors, through the suggestion of personalized actions based on previous behaviors, aiming at a more sustainable collective behavior, through the reduction of energy consumption in shared spaces. In order to know the effectiveness of this application, in addition to the consumption measurements, two user surveys are carried out, at the beginning and at the end of the research, which will allow observing the behavioral evolution.

Sílvia Luís, researcher at the Iscte's Center for Research and Social Intervention (CIS), considers that "the use of engineering and IoT gives psychology specialists the possibility of a more targeted intervention adapted to the characteristics of each person. We know, case by case and with great detail, the reason for each behavior, for example, if it is motivated by lack of knowledge about the way to act, or if it is due to the devaluation of the resulting benefits. And, according to these motivations, it is possible to propose measures and suggestions for improvement".

The research project will culminate in the development of a manual of energy efficiency recommendations and best practices for shared buildings, especially universities. The multidisciplinary nature of this project benefits from the fact that, on the same campus of the Iscte, researchers and lecturers from various fields, from architecture to engineering, from management to social sciences and public policies, develop their activities. 

One of the concerns, in this as in other ongoing investigations where mobile devices are used and a great deal of information is collected, relates to the protection of the personal data of those involved. In addition to all research being carried out with voluntary participants and with informed consent, the data is properly anonymized and subject to confidentiality rules. In addition, these activities are monitored by the Iscte Ethics Committee.


WINTER SCHOOL

Along with this multidisciplinary project for behavior change in public spaces, ISTAR develops a wide range of activities in the area of smart cities, having held, in the summer of 2019, a summer school and an international conference on the subject, which brought together several national and foreign experts. At the center of the debates were the new emerging computing paradigms, new services linked to IoT, as well as the opportunities that, from an architectural and urbanistic point of view, can lead to the achievement of more efficient, sustainable cities with a better quality of life. 

Taking into account the success of the July 2019 summer school, a new version will be held in February 2020 (winter school), in which the blockchain theme will also be addressed, with the participation of foreign researchers, universities from the Lisbon region and also representatives of the business environment.

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Sara Eloy - Director of 
ISTAR 

"ISTAR bets on multidisciplinarity to find innovative solutions to the current challenges in the areas of intelligent cities, digital transformation and societal challenges, always focusing on a sustainable development, both ecological and social and economic".

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 OTHER PROJECTS IN THE AREA OF SMART CITIES


The smart cities and IoT are at the center of several projects, which involve several researchers from ISTAR and also teachers and students from the School of Technology and Architecture of ISCTE-IUL, either in the laboratory or in the context of partnerships with companies.

> Collaboration in the project to install 14 thousand intelligent lighting stations in Tomar, which began in September 2019. It is the installation of led lamps with layers of intelligence, sensors to measure temperature, intensity and brightness according to the environment, with remote control. Iscte, in collaboration with Cisco, developed all the communications part, previously based on GSM, which is now performed through LoRa (Long Range) communications, which allows a very low transmission rate, low energy consumption, and which is being used to remotely perform the firmware updates of the entire system. This project will allow the saving of 700 thousand euros per year in energy. As a result of this collaboration, two LoRa illuminators will be installed at Iscte, which will allow reducing the energy bill. Two master theses have been developed as part of this project.

> Collaboration with the company Evox in a monitoring and waste management system, which will use sensors that will indicate in real time the level of the containers spread throughout the city. ISTAR worked on the optimization of the installed capacity, so that the collection is uniform, with a pre-defined periodicity, allowing to reduce operational costs by 30%. The pilot experience takes place in the city of Castelo Branco.

> Project on the loading of electric cars in condominiums, or other spaces where energy is shared. It is a IoT system with sensors for energy measurement and authentication through a mobile device. This work began with a master's thesis, then a PhD, and is now being tested for eventual commercialization in public charging stations using blockchain, dispensing with charging cards.

> Project on energy saving in a daycare center in the Lisbon region, carried out by a master student. The work consisted of monitoring consumption related to lighting and air conditioning in the establishment and developing standardized visualization and action templates, which allowed for savings of 20% in the energy bill.

> Participation in the Open Data Laboratory of the Lisbon City Hall, through which university and research institutions are invited to solve challenges, namely related to mobility and energy, from the data provided by various entities operating in the city. Several projects are being developed, in the scope of the Master in Integrated Business Intelligence Systems.

> Solution to reduce the tourist congestion in the historical areas of the city of Lisbon. A mobile phone activity detection system allows collecting data on the abnormal concentration of people in certain areas of the city, especially those most frequented by tourists. This information is transmitted to a cell phone application, providing information to tourists and tour operators about the areas to avoid. This system, in a very advanced stage of development, will allow a more efficient and sustainable management of tourism activity in the Portuguese capital.

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Sílvia Luís - CIS Researcher

The use of engineering and IoT gives psychology specialists the possibility of a more targeted intervention adapted to the characteristics of each person. We know the reason for each behavior and its motivations.

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