/*----------------------------*/ MIBIS - ISCTE, Master in Integrated Business Intelligence Systems: August 2020

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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IoT and Blockchain Paradigms for EV Charging System

In this research work, we apply the Internet of Things (IoT) paradigm with a decentralized blockchain approach to handle the electric vehicle (EV) charging process in shared spaces, such as condominiums. A mobile app handles the user authentication mechanism to initiate the EV charging process, where a set of sensors are used for measuring energy consumption, and based on a microcontroller, establish data communication with the mobile app. A blockchain handles financial transitions, and this approach can be replicated to other EV charging scenarios, such as public charging systems in a city, where the mobile device provides an authentication mechanism. A user interface was developed to visualize transactions, gather users’ preferences, and handle power charging limitations due to the usage of a shared infrastructure. The developed approach was tested in a shared space with three EVs using a charging infrastructure for a period of 3.5 months. View Full-Text




Electric Vehicle Charging Process and Parking Guidance App

This research work presents an information system to handle the problem of real-time guidance towards free charging slot in a city using past date and prediction and collaborative algorithms since there is no real-time system available to provide information if a charging spot is free or occupied. We explore the prediction approach using past data correlated with weather conditions. This approach will help the driver in the daily use of his electric vehicle, minimizing the problem of range anxiety, provide guidance towards charging spots with a probability value of being available for charging in a context for the app and smart cities. This work handles the uncertainty of the drivers to get a suitable and vacant place at a charging station because missing real-time information from the system and also during the driving process towards the free charging spot can be taken. We introduce a framework to allow collaboration and prediction process using past related data. View Full-Text





Edge Computing Approach for Vessel Monitoring System

A vessel monitoring system (VMS) is responsible for real-time vessel movement tracking. At sea, most of the tracking systems use satellite communications, which have high associated costs. This leads to a less frequent transmission of data, which reduces the reliability of the vessel location. Our research work involves the creation of an edge computing approach on a local VMS, creating an intelligent process that decides whether the collected data needs to be transmitted or not. Only relevant data that can indicate abnormal behavior is transmitted. The remaining data is stored and transmitted only at ports when communication systems are available at lower prices. In this research, we apply this approach to a fishing control process increasing the data collection process from once every 10 min to once every 30 s, simultaneously decreasing the satellite communication costs, as only relevant data is transmitted in real-time to the competent central authorities. Findings show substantial communication savings from 70% to 90% as only abnormal vessel behavior is transmitted. Even with a data collection process of once every 30 s, findings also show that the use of more stable fishing techniques and fishing areas result in higher savings. The proposed approach is assessed as well in terms of the environmental impact of fishing and potential fraud detection and reduction. View Full-Text












Higher Education, ISCTE-IUL, Lisbon, Portugal - Information on the functioning of the school year 2020/2021

Because I am receiving questions, in social media, from both Portuguese and foreign students, I share here the email I received from the rectory on 31-07-2020.

Citation:

Preparation of the 2020/2021 school year 

The Iscte is also awaiting guidance from the Ministry of Science, Technology and Higher Education (MSTHE) and the Directorate General of Health (DGH) regarding the operating conditions for the next school year.
However, for the start of the 2020/2021 school year, the Iscte has already defined the following principles:
1. in line with the practice of previous years, it is planned to start classes, for most courses, in September 2020.
2. In the case of the 1st year of undergraduate and integrated master's degrees, given the schedule of the National Access Competition, classes will begin only on October 6 and end in December, according to the school calendar.
3. It is anticipated that classes will be taught in face-to-face from the Iscte rooms.
4. Classes are expected to be held in a mixed regime (face-to-face and online simultaneously).
5. For foreign or international students, who are unable to travel to Lisbon due to the pandemic, the classes can be transmitted online, in English. 

The ways of implementing these principles, as well as their exceptions, will be defined after the approval and dissemination of the MSTHE and DGH guidelines.

Academic Greetings,

Maria de Lurdes Rodrigues
Dean


Avenida das Forças Armadas, Edifício Sedas Nunes, Reitoria
1649-026 LISBON Portugal
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For any additional information about the functioning of the Master in Integrated Business Intelligence Systems (MIBIS), you may contact me by email:




Management




IoT Power Monitoring System for Smart Environments

In this research work, we describe the development and subsequent validation of EnerMon a flexible, efficient, edge-computing based Internet of Things (IoT) LoRa (LongRange) System to monitor power consumption. This system provides real-time information and a descriptive analytics process to provide a ‘big picture’ about energy consumption over time and identify energetic waste. The solution is based on Arduinos, current transformer sensors, Raspberry Pi as an application server and LoRa communication alongside a description and information on what is to be expected of it, describing the development process from the design phase to the validation phase with all steps in between. Due to LoRa low debit communication, an edge computing approach was implemented to create a real-time monitoring process based on this technology. This solution, with the help of descriptive analysis, allows the creation of an energetic local footprint, using a low-cost developed solution for less than 80€ per three-phases monitoring device. This solution also allows for easy installation without communication range and obstacles limitations making it easy use in different situations from big complex building to smaller consumers, such as electric boilers, or simply to measure the energetic footprint of tourists in a small local tourist apartment. View Full-Text








Vehicle Electrification: New Challenges and Opportunities for Smart Grids

Nowadays, concerns about climate change have contributed significantly to changing the paradigm in the urban transportation sector towards vehicle electrification, where purely electric or hybrid vehicles are increasingly a new reality, supported by all major automotive brands. Nevertheless, new challenges are imposed on the current electrical power grids in terms of a synergistic, progressive, dynamic and stable integration of electric mobility. Besides the traditional unidirectional charging, more and more, the adoption of a bidirectional interconnection is expected to be a reality. In addition, whenever the vehicle is plugged-in, the on-board power electronics can also be used for other purposes, such as in the event of a power failure, regardless if the vehicle is in charging mode or not. Other new opportunities, from the electrical grid point of view, are even more relevant in the context of off-board power electronics systems, which can be enhanced with new features as, for example, compensation of power quality problems or interface with renewable energy sources. In this sense, this paper aims to present, in a comprehensive way, the new challenges and opportunities that smart grids are facing, including the new technologies in the vehicle electrification, towards a sustainable future. A theoretical analysis is also presented and supported by experimental validation based on developed laboratory prototypes. View Full-Text







Child’s Target Height Prediction Evolution


This study is a contribution for the improvement of healthcare in children and in society generally. This study aims to predict children’s height when they become adults, also known as “target height”, to allow for a better growth assessment and more personalized healthcare. The existing literature describes some existing prediction methods, based on longitudinal population studies and statistical techniques, which with few information resources, are able to produce acceptable results. The challenge of this study is in using a new approach based on machine learning to forecast the target height for children and (eventually) improve the existing height prediction accuracy. The goals of the study were achieved. The extreme gradient boosting regression (XGB) and light gradient boosting machine regression (LightGBM) algorithms achieved considerably better results on the height prediction. The developed model can be usefully applied by pediatricians and other clinical professionals in growth assessment. View Full-Text



Attend a Portuguese university?

Hello, everyone!
This page is an individual initiative as part of my doctoral research, at #ISTAR, #ISCTE. The theme is the internationalization of higher education. I intend to promote the debate of desires and opinions between those who seek to study abroad and those who have already had experience of internationalization.
Would you please answer the 2 questions below?
Thank you in advance!






Salespeople Performance Evaluation with Predictive Analytics in B2B



"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." View Full-Text



BIM in People2People and Things2People Interactive Process

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. View Full-Text


Machine learning for quality control system

Attending the Master in Integrated Business Intelligence Systems you can learn to do this, for example:

"In this work, we propose and develop a classification model to be used in a quality control system for clothing manufacturing using machine learning algorithms. The system consists of using pictures taken through mobile devices to detect defects on production objects. In this work, a defect can be a missing component or a wrong component in a production object. Therefore, the function of the system is to classify the components that compose a production object through the use of a classification model. As a manufacturing business progresses, new objects are created, thus, the classification model must be able to learn the new classes without losing previous knowledge. However, most classification algorithms do not support an increase of classes, these need to be trained from scratch with all . Thus. In this work, we make use of an incremental learning algorithm to tackle this problem. This algorithm classifies features extracted from pictures of the production objects using a convolutional neural network (CNN), which have proven to be very successful in image classification problems. We apply the current developed approach to a process in clothing manufacturing. Therefore, the production objects correspond to clothing items." Read full article



Named Entity Recognition for Sensitive Data Discovery in Portuguese

Here is an example of work you can learn to do by attending the Master in Integrated Business Intelligence Systems

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. View Full-Text


LoBEMS—IoT for Building and Energy Management Systems

Here is an example of work you can learn to do by attending the Master in Integrated Business Intelligence Systems

This work presents the efforts on optimizing energy consumption by deploying an energy management system using the current IoT component/system/platform integration trends through a layered architecture. LoBEMS (LoRa Building and Energy Management System), the proposed platform, was built with the mindset of proving a common platform that would integrate multiple vendor locked-in systems together with custom sensor devices, providing critical data in order to improve overall building efficiency. The actions that led to the energy savings were implemented with a ruleset that would control the already installed air conditioning and lighting control systems. This approach was validated in a kindergarten school during a three-year period, resulting in a publicly available dataset that is useful for future and related research. The sensors that feed environmental data to the custom energy management system are composed by a set of battery operated sensors tied to a System on Chip with a LoRa communication interface. These sensors acquire environmental data such as temperature, humidity, luminosity, air quality but also motion. An already existing energy monitoring solution was also integrated. This flexible approach can easily be deployed to any building facility, including buildings with existing solutions, without requiring any remote automation facilities. The platform includes data visualization templates that create an overall dashboard, allowing management to identify actions that lead to savings using a set of pre-defined actions or even a manual mode if desired. The integration of the multiple systems (air-conditioning, lighting and energy monitoring) is a key differentiator of the proposed solution, especially when the top energy consumers for modern buildings are cooling and heating systems. As an outcome, the evaluation of the proposed platform resulted in a 20% energy saving based on these combined energy saving actions. View Full-Text



Smart Health

Remote monitoring of patients becomes increasingly necessary, especially for patients with chronic diseases, the elderly, and others who need special support. Technology and data science are already sufficiently developed to not only enable remote monitoring but to make real-time decisions based on the extraction of knowledge from captured data. There is a great demand for people specialised in IoT, remote sensing, data mining.
Here is a master's course where you can learn and practice on these subjects.



João FerreiraAssistant Professor and Master's Director





Luís Rosário, Cardiologist at Santa Maria Hospital



Studying abroad

Hello, everyone!
This page is an individual initiative as part of my doctoral research, at #ISTAR, #ISCTE. The theme is the internationalization of higher education. I intend to promote the debate of desires and opinions between those who seek to study abroad and those who have already had experience of internationalization.
Would you please answer the 2 questions below?
Thank you in advance!