Browsing by Author "Martins, Pedro"
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- An IoT-Based Framework for Monitoring Photovoltaic BatteriesPublication . Sarmento, Gonçalo; Cardoso, Filipe; Mota, Mickael; Henriques, João; Abbasi, Maryam; Martins, Pedro; Wanzeller, Cristina; Caldeira, FilipeThe need for a more sustainable world is increasing the number of installations of photovoltaic systems including batteries as a way to postpone energy consumption when it is most needed. However, the chemical nature of batteries makes them unreliable and prompt to dangerous situations and can lead to a potential disaster, such as fires and explosions, in case the underline issues keep undetected for a long time. To overcome this scenario is a proposed framework for monitoring the temperature and voltage of batteries enabled by acquired data from Internet of Things (IoT) sensors. In case of these values become abnormal, a notification is triggered. The experimental results demonstrate the feasibility of the proposed framework to detect and notify hazard situations caused by battery faults.
- An overview on software testing and auditingPublication . Lopes, Catia; Cardoso, Filipe; Abbasi, Maryam; Martins, Pedro; Sá, FilipeMore and more people are dependent on technology. They increasingly use electronic services for day-to-day routines, and user loyalty to the software is essential, being defined by the excellence of the SW. The fewer flaws it has, the greater the likelihood of being able to retain the user’s loyalty. For this situation to be possible, tests are crucial in the development stage since they have the main purpose of identifying errors. To be possible to have a good quality of software, it is important to realize the importance of carrying out tests, as well as to understand what types of tests exist and realize which ones fit in each situation. In addition, the article addresses the life cycle and levels as sociated with software testing. In terms of test automation, there are some tools for developing this type of test, referencing the Katalon stu- diom robot framework, Protractoe and Watir; each is framed in different practical situations.
- Comparing machine learning vs. humans for dietary assessmentPublication . Abbasi, Maryam; Cardoso, Filipe; Wanzeller, Cristina; Martins, PedroDue to the availability of large-scale datasets (e.g., ImageNet, UECFood) and the advancement of deep Convolutional Neural Networks (CNN), computer vision image recognition has evolved dramatically. Currently, there are three major methods for using CNN: starting from scratch, using a pre-trained network off the shelf, and performing unsupervised pre-training with supervised changes. When it comes to those with dietary restrictions, automatic food detection and assessment are critical.In this research, we show how to address detection difficulties by combining three CNNs. The different CNN architectures are then assessed. The amount of parameters in the examined CNN models ranges from 5,000 to 160 million, depending on the number of layers. Second, the various CNNs under consideration are assessed based on dataset sizes and physical image context. The results are assessed in terms of performance vs. training time vs. accuracy. Finally, the accuracy of CNNs is investigated and examined using human knowledge and classification from the human visual system (HVS). Finally, additional categorization techniques, such as bag-of-words, are considered to solve this problem.Based on the findings, it can be concluded that the HVS is more accurate when a data set comprises a wide range of variables. When the dataset is restricted to niche photos, the CNN outperforms the HVS.
- Comparison of Image Processing and Classification Methods for a Better Diet Decision-MakingPublication . Abbasi, Maryam; Cardoso, Filipe; Martins, PedroThis paper aims to explore the use of different deep learning techniques, specifically convolutional neural networks (CNNs), for dietary assessment through image food recognition and compare their performance to the human visual system (HVS). Currently, there are three main techniques for using CNNs in this task: training a network from scratch; using an off-the-shelf pre-trained network; and performing unsupervised pre-training with supervised adjustments. In this study, the authors evaluate the performance of three CNN models with varying numbers of parameters (5,000 to 160 million) based on dataset size and spatial image context. The authors also consider human knowledge and classification to compare the performance of the CNNs to the HVS. They find that while the CNNs make errors across different food classes, the HVS tends to make semantic errors with specific food classes. As a result, the HVS shows more consistency in its answers. Overall, the findings suggest that the HVS is more accurate when the dataset is diverse, while the CNN performs better when the dataset is focused on a particular niche. In conclusion, this study provides empirical evidence that machine learning can be more efficient than the HVS in certain tasks but also highlights the strengths and limitations of both approaches. The authors suggest that combining CNNs with other classification techniques, such as bagof-words, may be a promising approach for improving the accuracy of dietary assessment through image food recognition.
- Comparison of Semi-structured Data on MSSQL and PostgreSQLPublication . Alves, Leandro; Cardoso, Filipe; Oliveira, Pedro; Rocha, Júlio; Wanzeller, Cristina; Martins, Pedro; Abbasi, MaryamThe present study intends to compare the performance of two Data Base Management Systems, specifically Microsoft SQL Server and PostgreSQL, focusing on data insertion, queries execution, and indexation. To simulate how Microsoft SQL Server performs with key-value oriented datasets we use a converted TPC-H lineitem table. The data set is explored in two different ways, firsts using the key-value-like format and second in JSON format. The same dataset is applied to PostgreSQL DBMS to analyse performance and compare both database engines. After testing the load process on both databases, performance metrics (execution times) are obtained and compared. Experimental results show that, in general, inserts are approximately twice times faster in Microsoft SQL Server because they are injected as plain text without any type of verification, while in PostgreSQL, loaded data includes a validating process, which delays the loading process. Moreover, we did additional indexation tests, from which we concluded that in general, data loading performance degrades. Regarding query performance in PostgreSQL, we conclude that with indexation, queries become three or four percent faster, and six times faster in Microsoft SQL Server.
- Exploring OpenStack for Scalable and Cost-Effective Virtualization in EducationPublication . Abbasi, Abbasi; Cardoso, Filipe; Silva, José; Martins, Pedrohe technological landscape of cloud computing has transformed significantly with the advent of virtualization, allowing for the provision of computing resources over the internet. The leading cloud computing software providers offer this new concept, and various service providers currently exist, providing options for virtualizing services on-premises as well. OpenStack presents an open-source alternative for building virtual local or cloud setups that support petabytes of data, unlimited scale, and configurable networking. The tool’s features make it an ideal solution for large scale virtualization, reducing maintenance costs and optimizing hardware resource utilization, particularly in education and government sectors. This paper presents an overview of the OpenStack software, with a focus on constructing a scalable hosting architecture tailored to educational settings. We discuss functional and architectural details that are essential to implementing unique cloud computing models for virtualization purposes. We describe an experimental virtualization setup that was implemented within an educational scenario, along with a guideline for configuring OpenStack. Overall, this study offers insights into the potential of OpenStack for virtualizing large-scale educational setups, paving the way for cost-effective and efficient resource utilization.
- In-Depth Analysis of Mobile Apps Statistics: A Study and Development of a Mobile AppPublication . Abbasi, Maryam; Cardoso, Filipe; Lopes, André; Rodrigues, Diogo; Saraiva, João; Martins, Pedro; Sá, FilipeWith the popularity of smartphones and mobile devices, mobile application (a.k.a. “app”) markets have been growing exponentially in terms of the number of users and downloads. To increase user satisfaction, app developers invest a lot of work into gathering and utilizing user input. This paper presents an analysis of the mobile app market through the development of a mobile app. The app provides users with an overview of the most important statistics, including the best apps in each category, the categories with the most apps, and the overall statistics. The data was collected through the analysis of publicly available annual reports, and presented in a user-friendly format through the use of graphics. The focus of the study was to provide a useful tool for developers and individuals seeking specific statistics. Although the approach has proven to be effective, the authors suggest potential, such as incorporating live data from the Google Play Store and analysing the App Store. Additionally, comparing the data from multiple years can provide useful insights into the evolution of the market.
- IoT Smart Collect - Routing Process and Driver GuidancePublication . Abbasi, Maryam; Cardoso, Filipe; Nascimento, Bruno; Santos, Rui; Sá, Filipe; Silva, José; Martins, PedroWaste collection is a traditional process that involves a driver collecting waste from a set of designated deposits based on a pre-determined route. The authors present a new approach that utilizes Artificial Intelligence to define the route based on the occupancy volume of the deposits. The new process involves the use of a mobile application to assist the driver during the journey. The application communicates with the central system to receive information on the next route, calculates the best possible route considering traffic laws and road conditions, and guides the driver throughout the journey. The application also provides real-time updates on the driver’s progress and allows the driver to provide feedback All collected data is stored and can be consulted and explored through lists, graphs, and filtering options. The authors believe that the new approach will improve the efficiency of waste collection and provide a better experience for the driver.
- IoT-Based Monitoring System for Photovoltaic Battery ManagementPublication . Sarmento, Gonçalo; Cardoso, Filipe; Mota, Mickael; Henriques, João; Abbasi, Maryam; Martins, Pedro; Wanzeller, Cristina; Caldeira, FilipeAs number of photovoltaic systems being installed is increasing, also many users are deciding to include batteries, and postpone the consumption of that energy when it is most needed. Moreover,a crucial issue can keep undetected for long time causing dangerous situation which can lead to a potential disaster. However, the chemical nature of batteries makes them unreliable and dangerous. In this risky scenario, it becomes essential to monitor their behaviour in order to avoid accidents. In that purpose, a enabled Internet of Things (IoT) framework is proposed for monitoring the batteries values for temperature and voltage through the use of sensors. If these values becomes abnormal, a notification is triggered to the responsible person. Based on experimental results, the proposed framework to detect and notify hazard situations caused by battery faults.
- Local e-gov mobile application(s) reviewPublication . Abbasi, Maryam; Cardoso, Filipe; Holanda, Maria; Almeida, Dany; Silva, José; Martins, PedroThis study aims to evaluate the adoption of e-government services in Portuguese municipalities, specifically focusing on the usage of mobile applications. Data was collected from 40 of the most populous municipalities in Portugal and analyzed for usage of e-government services such as incidents, traffic conditions, and population alerts through mobile apps. The study found a mixed correlation between population size and e-government app usage, with lower population municipalities showing lower adoption rates. The results suggest that further efforts are needed to improve accessibility and promote e-government services to increase engagement and usage among the local population. The study provides valuable insights for local government representatives and stakeholders to effectively use and access e-government services for the benefit of all residents. The results emphasize the need for effective outreach and promotion strategies, as well as the importance of user testing and feedback in the development process, to ensure that the applications meet the needs and expectations of users. Furthermore, the study highlights the need for investment in marketing and communication initiatives to increase awareness and adoption of e-government apps among the population. In conclusion, this study contributes to the literature on e-government adoption in Portuguese municipalities and provides a foundation for future research in this area. The findings can inform the development of effective policies and strategies to promote the adoption and usage of e-government services, enhance accessibility and efficiency of local government services, and improve the quality of life for residents.