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Tese de Doutoramento em Informática Industrial, Universidade do Minho, 2008

Mestrado em Electrónica Industrial

There are many uses for machine learning in everyday life and there is a steady increase in the field of medicine; the use of such technologies facilitates the tiresome work of health professionals by either automating repetitive tasks or making them simpler. Bed-related disorders are a great example where tedious tasks could be facilitated by machine learning algorithms, as suggested by many authors, by providing information on the posture of a particular bedded patient to health professionals. To assess the already existing studies in this field, this study provides a systematic review where the literature is analyzed to find correlations between the various factors involved in the making of such a system and how they perform. The overall findings suggest that there is only a significant relationship between the postures considered for classification and the resulting accuracy, despite some other factors such as the amount of data available providing some differences according to the type of algorithm used, with neural networks needing larger datasets. This study aims to increase awareness in this field and give future researchers information based on previous works’ strengths and limitations while giving some suggestions based on the literature review.

A agricultura tem recorrido, tradicionalmente, a métodos empíricos que não rentabilizavam a produção e estava fortemente dependente das condições meteorológicas. Para melhorar a produção agrícola, surgiram as estufas agrícolas que permitem culturas de elevado valor acrescentado. Estas permitem também a elaboração de estudos de conceitos de causa-efeito, que possibilitam a construção de modelos e sistemas para melhorar a produção e a qualidade de determinada colheita. Com base nesta realidade, este artigo apresenta e descreve um trabalho que se encontra em fase de desenvolvimento por investigadores de duas escolas do Instituto Politécnico de Castelo Branco (IPCB) e que visa o desenvolvimento de um sistema para monitorização de uma estufa agrícola situada na Escola Superior Agrária (ESA) daquele Instituto.

Tourism is an important economic sector, which reaches significant relevance in low-density rural areas, where it can be a driver of other sectors of activity that guarantee jobs and small and medium-sized local companies. However, in these regions, most points of tourist interest are scattered, do not have a support structure to receive visitors and, consequently, are difficult to explore for tourism in a profitable way. This article describes a platform that uses technology to expand and enhance opportunities for exploring tourist points and interest in low-density rural territories. This platform provides features for tour operators to publicize and make their points of interest available to tourists, allowing tourists to access certain points of interest automatically using IoT devices, after validation. This possibility is particularly important in low-density territories. This article describes the platform and the results of a preliminary evaluation, at the level of acceptance tests, which allowed to obtain feedback on the interest and usefulness that the application may have.

The use of wireless communications systems on the factory shop floor is becoming an appealing solution with many advantages compared to cable-based solutions, including low cost, easy deployment, and flexibility. This, combined with the continuous growth of low-cost mobile devices, creates opportunities to develop innovative and powerful applications that, in many cases, rely on computing and memory-intensive algorithms and low-latency requirements. However, as the density of connected wireless devices increases, the spectral noise density rises, and, consequently, the radio interference between radio devices increase. In this paper, we discuss how the density of AR/VR mobile applications with high throughput and low latency affect industrial environments where other wireless devices use the same frequency channel. We also discuss how the growing number of these applications may have an impact on the radio interference of wireless networks. We present an agnostic methodology to assess the radio interferences between wireless communication systems on the factory floor by using appropriate radio and system models. Several interference scenarios are simulated between commonly used radio systems: Bluetooth, Wi-Fi, and WirelessHART, using SEAMCAT. For a 1% probability of interference and considering a criterion of C/I = 14 dB, the simulations on an 80 m × 80 m factory shop floor show that low-bandwidth systems, such as Bluetooth and WirelessHART, can coexist with high-bandwidth and low-latency AR/VR applications running on Wi-Fi mobile terminals if the number of 11 Wi-Fi access points and 80 mobile AR/VR devices transmitting simultaneously is not exceeded.

Bedded or lying-people pressure-map datasets can be used to identify patients’ in-bed postures and can be very useful in numerous healthcare applications. However, the construction of these datasets is not always easy, and many researchers often resort to existing datasets to carry out their experiments and validate their solutions. This systematic review aimed to identify and characterise pressure-map datasets on lying-people- or bedded-people positions. We used a systematic approach to select nine studies that were thoroughly reviewed and summarised them considering methods of data collection, fields considered in the datasets, and results or their uses after collection. As a result of the review, six research questions were answered that allowed a characterisation of existing datasets regarding of the types of data included, number and types of poses considered, participant characteristics and size of the dataset, and information on how the datasets were built. This study might represent an important basis for academics and researchers to understand the information collected in each pressure-map dataset, the possible uses of such datasets, or methods to build new datasets.

Reducing the gap between Software Engineering education and the needs in the software industry is a goal for Academia. Advancement in terms of cutting-edge technical skills and good soft skills preparation is the desired goal to shorten the onboarding in the labour market. Generally, in computer science or computer engineering courses, separate subjects exist to teach requirements engineering, analysis and design, coding, or validation. However, integrating all these phases normally requires experience in developing a complete project. The approach presented in this paper has involved the staff of a software company in collaboration with the staff of an academic Institution and resulted in a student's involvement in a full-stack software development project. The student was involved in an agile team composed of teachers and Information Technology (IT) professionals. Scrum framework was followed, and the product was developed using a low-code development platform. Results show that this agile and full stack approach allows students to develop cutting-edge technical and non- technical skills. The paper presents the approach, the achieved results, some lessons learned and some guidelines for the future.

Tourism is an important economic sector with particular importance for several countries and regions. For low-density rural territories, this sector can be an important driver of other sectors that guarantee jobs and local small and medium enterprises. However, in these regions mostly points of interest are dispersed and do not have a support structure to receive visitors and consequently most computer applications to support tourism are not suitable for these situations. This work describes a platform that uses technology to enhance the potential of opportunities to explore tourist attractions in low-density rural territories. This approach considers the particularities of these territories and the characteristics of existing points of interest. It provides mechanisms for tourism operators to make their points of interest available to be visited by tourists, without the need to spend a lot of resources and without the need of constant support from the tourism operators responsible for these points of interest. This approach may contribute to enhancing existing heritage in low-density rural territories, bringing new opportunities and unique experiences without requiring much human labor and enhancing the tourism benefit in low-density rural territories.

Plant diseases and pests significantly influence food production and the productivity and economic profitability of agricultural crops. This has led to great interest in developing technological solutions to enable timely and accurate detection. This systematic review aimed to find studies on the automation of processes to detect, identify and classify diseases and pests in agricultural crops. The goal is to characterize the class of algorithms, models and their characteristics and understand the efficiency of the various approaches and their applicability. The literature search was conducted in two citation databases. The initial search returned 278 studies and, after removing duplicates and applying the inclusion and exclusion criteria, 48 articles were included in the review. As a result, seven research questions were answered that allowed a characterization of the most studied crops, diseases and pests, the datasets used, the algorithms, their inputs and the levels of accuracy that have been achieved in automatic identification and classification of diseases and pests. Some trends that have been most noticed are also highlighted.

No ensino do Controlo recorre-se frequentemente a simulações computacionais, através de software disponível para o efeito, permitindo a visualização do comportamento dos sistemas em estudo. O trabalho apresentado neste artigo, visa disponibilizar uma ferramenta multimédia, com várias componentes, para suporte ao ensino de disciplinas da área do Controlo (FEMECO). Esta servirá de apoio ao professor, para ensinar a matéria, e será utilizada pelos alunos, facilitando a aprendizagem segundo o ritmo próprio de cada indivíduo. Para o efeito, está a ser desenvolvido um CD-ROM, contendo os fundamentos teóricos e práticos, com uma forte componente pedagógica baseada em simulações dos problemas em estudo, e um site WEB de apoio logístico.

This paper describes a project that is being developed at Escola Superior de Tecnologia - Instituto Politécnico de Castelo Branco – Portugal. It consists of a prototype for a real time data pick up system, using the Controller Area Network (CAN) bus. The goal is the gathering of data contained in bar code labels that are coupled to cloths pieces in an apparel factory during the production process.

Several approaches have been proposed to reduce the gap between software engineering education and the needs and practices of the software industry. Many of them aim to promote a more active learning attitude in students and provide them with more realistic experiences, thus recreating industry software development environments and collaborative development and, in some cases, with the involvement of companies mainly acting as potential customers. Since many degree courses typically offer separate subjects to teach requirements engineering, analysis and design, coding, or validation, the integration of all these phases normally necessitates experience in a project context and is usually carried out in a final year project. The approach described in this article benefits from the close involvement of a software house company which goes beyond the common involvement of a potential customer. Students are integrated into distributed teams comprising students, teachers and IT professionals. Teams follow the agile Scrum methodology and use the OutSystems low-code development platform providing students with the experience of an almost real scenario. The results show that this approach complements the knowledge and practice acquired in course subjects, develops the students’ technical and non-technical skills, such as commitment, teamwork, and communication, and initiates them in the methodologies and development strategies used in these companies. The feedback from the teachers involved, software companies and students was very positive.

Pressure ulcers are a critical issue not only for patients, decreasing their quality of life, but also for healthcare professionals, contributing to burnout from continuous monitoring, with a consequent increase in healthcare costs. Due to the relevance of this problem, many hardware and software approaches have been proposed to ameliorate some aspects of pressure ulcer prevention and monitoring. In this article, we focus on reviewing solutions that use sensor-based data, possibly in combination with other intrinsic or extrinsic information, processed by some form of intelligent algorithm, to provide healthcare professionals with knowledge that improves the decision-making process when dealing with a patient at risk of developing pressure ulcers. We used a systematic approach to select 21 studies that were thoroughly reviewed and summarized, considering which sensors and algorithms were used, the most relevant data features, the recommendations provided, and the results obtained after deployment. This review allowed us not only to describe the state of the art regarding the previous items, but also to identify the three main stages where intelligent algorithms can bring meaningful improvement to pressure ulcer prevention and mitigation. Finally, as a result of this review and following discussion, we drew guidelines for a general architecture of an intelligent pressure ulcer prevention system.

In recent years the Internet of Things, in addition to use cases in 'smart cities', has also increasingly been used in precision agriculture. As in the rest of the world, it has been a growing reality in Portugal. In an agricultural environment, where energy resources can be scarce and dispersed, the implementation of a LoRa network with autonomous sensor nodes must consider the limitations imposed by the energy consumed by the sensor node, when powered by a battery and a solar panel. For this, experimental tests must be carried out so that there is enough data for the implementation and optimization of the devices. This article presents a work focused on the study of the autonomy and energy efficiency of the sensor device, using algorithms capable of managing energy consumption as a function of the luminosity of the place. Preliminary results attest to the relevance of this approach, keeping the sensor node in operation without interruptions.

Pressure ulcers are skin injuries that develop mainly over bony areas as the result of prolonged pressure caused by the immo- bility of bedridden patients. They constitute not only a source of additional suffering for these patients but also contribute to the burnout of healthcare professionals who must maintain continuous monitoring of these patients. Data from countries such as the UK or the USA allows the cost of this problem to be estimated to be, respectively, near £2 billion and $80 billion. In this article, we describe the SensoMatt approach to pressure ulcer prevention and management, which is being developed as a research project that includes partners from industry, healthcare, and academia. The SensoMatt solution is centered on a pressure sheet that is placed under the patient’s mattress, complemented by an online management portal and a mobile app. These provide patients and healthcare providers with an unparalleled set of services that include personalized analysis, prevention warnings and recommendations.

Efficient use of resources is a critical factor in almond crops. Technological solutions can significantly contribute to this purpose. The VeraTech project aims to explore the integration of sensors and cloud-based technologies in almond crops for efficient use of resources and reduction of environmental impact. It also makes available a set of relevant and impactful performance indicators in agricultural activity, which promote productivity gains supported by efficient use of resources. The proposed solution includes a sensor network in the almond crops, the transmission of data and its integration in the cloud, making this data available to be consumed, processed, and presented in the monitoring and alerts dashboard. In the current state of the development, several data are collected by sensors, transmitted over LoRaWAN, integrated using AWS IoT Core, and monitored and analysed through a cloud business analytics service. This project is implemented on a farm located in the Beira-Baixa region of Portugal and involves a partnership between Vera Cruz (owner of the farm), Veratech, and the Polytechnic Institute of Castelo Branco.