ESTGV - DI - Artigo em ata de evento científico internacional
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- An Advertising Real-Time Intelligent and Scalable Framework for Profiling Customers EmotionsPublication . Alves, Leandro; Oliveira, Pedro; Henriques, João; Bernardo, Marco V.; Wanzeller, Cristina; Caldeira, FilipeThe advertising industry is continuously looking up for effective ways to communicate to customers to impact their purchasing. Usually, profiling them is a time-consuming offline activity. Therefore, it becomes necessary to reduce costs and time to address consumers’ needs. This work proposes a scalable framework enabled by a Machine Learning (ML) model to profile customers to identify their emotions to help to drive campaigns. A multi-platform mobile application continuously profiles consumers crossing the front stores. Profiling customers according to their age and hair color, the color of their eyes, and emotions (e.g. happiness, sadness, disgust, fear) will help companies to make the most suitable advertisement (e.g. to predict whether the advertising tones on the front store are the adequate ones). All that data are made available in web portal dashboards, wherein subscribers can take their analysis. Such results from the analysis data help them to identify tendencies regarding the culture and age, and drive companies to fit front stores accordingly (e.g. to discover the right tones for the season). This framework can help to develop new innovative cost-effective business models at scale by driving in real-time the advertisements to a huge number of consumers to maximize their impact and centralizing the data collected from a large number of stores to design future campaigns.
- An Evaluation of How Big-Data and Data Warehouses Improve Business Intelligence Decision MakingPublication . Martins, Anthony; Martins, Pedro; Caldeira, Filipe; Sá, Filipe; Rocha, {\'AAnalyze and understand how to combine data warehouse with business intelligence tools, and other useful information or tools to visualize KPIs are critical factors in achieving the goal of raising competencies and business results of an organization. This article reviews data warehouse concepts and their appropriate use in business intelligence projects with a focus on large amounts of information. Nowadays, data volume is more significant and critical, and proper data analysis is essential for a successful project. From importing data to displaying results, there are crucial tasks such as extracting information, transforming it analyzing, and storing data for later querying. This work contributes with the proposition of a Big Data Business Intelligence architecture for an efficiently BI platform and the explanation of each step in creating a Data Warehouse and how data transformation is designed to provide useful and valuable information. To make valuable information useful, Business Intelligence tools are presented and evaluates, contributing to the continuous improvement of business results.
- An evolved security architecture for distributed industrial automation and control systemsPublication . Rosa, L.; Proença, J.; Henriques, João; Graveto, V.; Cruz, T.; Simões, P.; Caldeira, Filipe; Monteiro, E.Over the recent years, control and sensor systems used for IACS (Industrial Automation and Control Systems) have become more complex, due to the increasing number of interconnected distributed devices, sensors and actuators. Such components are often widely dispersed in the field – this is the case for microgeneration (wire-to-water generation, solar or wind), smart metering, oil and gas distribution or smart water management, among others. This IoT (Internet of Things)-centric IACS paradigm expands the infrastructure boundaries well beyond the single or aggregated-plant, mono-operator vision (mostly associated with geographically constrained systems topologies), being dispersed over a large geographic area, with increasingly small areas of coverage as we progress towards its periphery. This situation calls for a different approach to cyber threat detection, which is one of the most relevant contributions of the ATENA (Advanced Tools to assEss and mitigate the criticality of ICT components and their dependencies over critical infrAstructures) H2020 project (ATENA 2016). This paper presents and describes the ATENA cyber-security architecture, designed for the emerging generation of distributed IoT IACS, leveraging technologies such as Software Defined Networking/Network Function Virtualization and Big data event processing) within the scope of a cyber-detection architecture designed to deal with the inherent challenges of dispersed IACS, involved different operator domains.
- An Intelligent and Scalable IoT Monitoring Framework for Safety in Civil Construction WorkspacesPublication . Ferreira, Carolina; Correia, Luciano; Lopes, Manuel; Henriques, João; Martins, Pedro; Wanzeller, Cristina; Caldeira, FilipeKeeping civil construction workers safe is an important challenge due to working conditions and low technological support due to the inherent costs. This work surveys the literature and proposes a scalable framework for monitoring workers to minimize the response time with real-time warnings in hazardous situations or safety incidents. From the literature, it was possible to devise a gap in business addressing this problem. To address this problem, this work proposes an IoT scalable framework able to scale to a large number of civil construction companies with a large number of workers in order. The results from this work demonstrate the feasibility of the proposed framework and the low cost of the IoT solution and the scalability of the framework offers the opportunity to leverage new innovative business models capable to leverage their revenues.
- An Overview on Cloud Services for Human TrackingPublication . Martins, Manuel; Mota, David; Martins, Pedro; Abbasi, Maryam; Caldeira, FilipeThis paper reflects the intention to test the use of public cloud services to assess the presence of humans in a given space, more precisely, multiple stores, with the least effort and in the fastest way. It is also intended to demonstrate that the use of the public cloud can be an instrument of added value in business areas and research areas. In the specific case, the cloud was used to train and use artificial intelligence models.
- An overview on how to develop a low-code application using OutSystemsPublication . Martins, Ricardo; Caldeira, Filipe; Sá, Filipe; Abbasi, Maryam; Martins, PedroThe motivation for developing a self-service platform for employees arises precisely from the idea that in all organizations there are tasks that could be automated in order to redirect work resources to more important tasks. The proposed application consists of the development of a self-service platform, for personal information and scheduling tasks, aimed at the employees instead of all the solutions that are in the market that aim their platform to the Human Resources. We focus on the employers giving them more responsibility to make their own personal management like, change their personal info, book their vacations and other, giving to the Human Resources the tasks of managing all these actions made by the employers. At the end of the work, it is expected that the final solution to be considered as an example of success with regards to the theme of business automation and innovation, using the low-code application Outsystems to perform the full proposed application development.
- Analysis and real-time data of meteorologic impact on home solar energy harvestingPublication . Ferreira, João; Lourenço, Ismael; Henriques, João; Pires, Ivan Miguel; Caldeira, Filipe; Wanzeller, CristinaSolar energy production increased in the world from 0 TWh in 1965 to 724.09 TWh in 2019. Solar energy is adopted as a source for residential renewable energy sources because, besides Biomass sources, it’s the only one that can be installed and maintained at home. Operating efficiency is an important consideration when evaluating the application of photovoltaic panels (PV) technology. A real-time system monitoring is required to analyse the current production and understand the impact of the weather conditions on PV production. This paper extends the literature on the residence solar energy harvesting subject, by providing a scalable architecture that can be used as starting point on data analysis on PV panels efficiency and how weather conditions impact energy production. A dataset was collected related to PV panel energy production, the residence energy consumption and that’s reading weather conditions. Wind intensity and direction, temperature, precipitation, humidity, atmospheric pressure and radiation were weather conditions analysed. Moreover, this data was analysed and interpreted in order to evaluate the pros and cons of the architecture as well as how the weather impacted the energy production.
- Are you lost? Using Facial Recognition to Detect Customer Emotions in Retail StoresPublication . Borges, Valter; P. Duarte, Rui; Cunha, Carlos; Mota, David; ThinkmindThe understanding of consumer behavior is a dynamic field, especially relevant to the success of companies and for consumer satisfaction. It is especially important in the situation of intense competition, currently characteristic for the retail store industry, where companies fight for every individual customer. Moreover, companies do not want customers to enter their system and leave without buying products they intended to buy. This has an impact on user satisfaction and retail stores income. In this paper we present a method that targets customer satisfaction in the aforementioned context using a facial recognition system acting at the emotional level of the customer. Our method is based on cumulative negative emotions that are associated to a sadness level, which triggers events for retail store assistants to help customers. Results show that this method is adequate to measure these emotions and is a useful reference for retail store assistant intervention.
- Automatic User Testing and Emotion Detection in Interactive Urban DevicesPublication . P. Duarte, Rui; Cunha, Carlos; Pereira Cardoso, José CarlosAutomated testing and evaluation of interfaces is a well-established reality supported by many tools that shorten the time to deploy new software versions to the user. However, exploring users’ emotions while interacting with interfaces as a tool to further increase the quality of traditional usability evaluation methods is still far from being a reality. This work uses the automatic analysis of users’ emotions while interacting with touchable interactive urban devices to detect usability issues. To this end, a coupled approach is implemented: the data is acquired from the interaction, and user emotions are extracted and processed to determine the emotional status during the interaction. This data is integrated into a web application so that designers can further improve the quality of the interface in the presence of negative emotions. Results show that the experimental tests showed that different users manifest similar negative emotions in the same contexts, which is a clear sign of usability issues that are to be corrected by the design team.
- Behavioral Anomaly Detection of Older People Living IndependentlyPublication . Cunha, Carlos; P. Duarte, Rui; Mota, DavidOlder people living independently represent one significant part of the population nowadays. Most of them have family or friends interested in being informed about changes in their routine. Considering these changes signal some physical or mental problem, they can trigger a contact or action from the interested persons to provide support. This paper presents an approach for non-intrusive monitoring of older people to send alerts after detecting anomalous behaviors. An analysis of seven months of data gathered using PIR sensors in a couple’s living house has shown regularities in their presence in compartments along the day. We validated the adequacy of an outlier detection algorithm to build a model of the persons’ behavior, exhibiting just 3.6% of outliers interpreted as false positives.