Optical fiber sensors and sensing networks: overview of the main principles and applications

Optical fiber sensors present several advantages in relation to other types of sensors. These advantages are essentially related to the optical fiber properties, i.e., small, lightweight, resistant to high temperatures and pressure, electromagnetically passive, among others. Sensing is achieved by exploring the properties of light to obtain measurements of parameters, such as temperature, strain, or angular velocity. In addition, optical fiber sensors can be used to form an Optical Fiber Sensing Network (OFSN) allowing manufacturers to create versatile monitoring solutions with several applications, e.g., periodic monitoring along extensive distances (kilometers), in extreme or hazardous environments, inside structures and engines, in clothes, and for health monitoring and assistance. Most of the literature available on this subject focuses on a specific field of optical sensing applications and details their principles of operation. This paper presents a more broad overview, providing the reader with a literature review that describes the main principles of optical sensing and highlights the versatility, advantages, and different real-world applications of optical sensing. Moreover, it includes an overview and discussion of a less common architecture, where optical sensing and Wireless Sensor Networks (WSNs) are integrated to harness the benefits of both worlds.This work was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Collection of a continuous long-term dataset for the evaluation of Wi-Fi-fingerprinting-based indoor positioning systems

The dataset introduced in this paper is available in two versions: lite version https://doi.org/10.5281/zenodo.6646008 (accessed on 28 July 2022) which considers Wi-Fi samples from each MD every 20 min, has a total of 382,852 Wi-Fi samples, thus making it easier to parse and analyse; full version https://doi.org/10.5281/zenodo.6928554 (accessed on 29 July 2022) which has all collected samples, with a total of 7,446,538 Wi-Fi samples.Indoor positioning and navigation have been attracting interest from the research community for quite some time. Nowadays, new fields, such as the Internet of Things, Industry 4.0, and augmented reality, are increasing the demand for indoor positioning solutions capable of delivering specific positioning performances not only in simulation but also in the real world; hence, validation in real-world environments is essential. However, collecting real-world data is a time-consuming and costly endeavor, and many research teams lack the resources to perform experiments across different environments, which are required for high-quality validation. Publicly available datasets are a solution that provides the necessary resources to perform this type of validation and to promote research work reproducibility. Unfortunately, for different reasons, and despite some initiatives promoting data sharing, the number and diversity of datasets available are still very limited. In this paper, we introduce and describe a new public dataset which has the unique characteristic of being collected over a long period (2+ years), and it can be used for different Wi-Fi-based positioning studies. In addition, we also describe the solution (Wireless Sensor Network (WSN) + mobile unit) developed to collect this dataset, allowing researchers to replicate the method and collect similar datasets in other spaces.This work has been supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020, and the PhD fellowship PD/BD/137401/2018

Real-world deployment of low-cost indoor positioning systems for industrial applications

The deployment of an Indoor Position System (IPS) in the real-world raised many challenges, such as installation of infrastructure, the calibration process or modelling of the building's floor plan. For Wi-Fi-based IPSs, deployments often require a laborious and time-consuming site survey to build a Radio Map (RM), which tends to become outdated over time due to several factors. In this paper, we evaluate different deployment methods of a Wi-Fi-based IPS in an industrial environment. The proposed solution works in scenarios with different space restrictions and automatically builds a RM using industrial vehicles in operation. Localization and tracking of industrial vehicles, equipped with low-cost sensors, is achieved with a particle filter, which combines Wi-Fi measurements with heading and displacement data. This allows to automatically annotate and add new samples to a RM, named vehicle Radio Map (vRM), without human intervention. In industrial environments, vRMs can be used with Wi-Fi fingerprinting to locate human operators, industrial vehicles, or other assets, allowing to improve logistics, monitoring of operations, and safety of operators. Experiments in an industrial building show that the proposed solution is capable of automatically building a high-quality vRM in different scenarios, i.e., considering a complete floor plan, a partial floor plan or without a floor plan. Obtained results revealed that vRMs can be used in Wi-Fi fingerprinting with better accuracy than a traditional RM. Sub-meter accuracies were obtained for an industrial vehicle prototype after deployment in a real building.This work was supported in part by the Fundacao para a Ciencia e Tecnologia-FCT through the Research and Development Units Project Scope under Grant UIDB/00319/2020 and in part by the Ph.D. Fellowship under Grant PD/BD/137401/2018. The associate editor coordinating the review of this article and approving it for publication was Prof. Masanori Sugimoto

Study of prebiotic activity of lignocellulosics hydrolyzed products

Orientador: Lucia Regina DurrantTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de AlimentosResumo: Neste trabalho foram avaliadas 6 linhagens de fungos basidiomicetos, sendo que estas foram testadas em 5 tipos de fontes lignocelulósicas provindas de resíduos agroindustriais. Estes foram testados sob fermentação submersa em cultivo estacionário no período de 30 dias de incubação. Na busca dos melhores hidrolisados para os testes prebióticos, foram selecionados os hidrolisados utilizados para fonte de enzimas dos fungos Pleurotus sp BCCB068 e Pleurotus tailândia, no 10° dia de incubação, utilizando farelo de arroz como fonte de carbono com as maiores atividades de xilanase de 0,29 U/ml e 0,24 U/mL respectivamente. Estes valores foram ampliados posteriormente com a otimização do processo de fermentação, elevando as atividades para 0,4 U/mL e 0,69 U/mL, respectivamente. Os hidrolisados escolhidos foram aplicados como fonte de enzimas lignocelulolíticas sobre a matriz de xilana e carboximetilcelulose, avaliando a degradação destas matrizes no período de 0 a 60 minutos de hidrólise. Neste período, os hidrolisados mostraram-se capaz de hidrolisar até 66,4% da xilana e 59,9% de carboximetilcelulose, formando compostos xilooligossacarídeos e celooligossacarídeos, respectivamente, além de vários monômeros de açúcares. As linhagens Pleurotus sp BCCB068 e Pleurotus tailândia também foram utilizadas diretamente para degradar a matriz de xilana em fermentação de 40 dias de cultivo, onde degradaram esta matriz em 73,6% no 20° dia para a primeira e 70,1% já no 5° dia de cultivo para a segunda linhagem, com produção de xilooligossacarídeos e seus monômeros. Os hidrolisados com efeito positivo na degradação das matrizes de xilana e carboximetilcelulose foram testados na sua atividade prebiótica, com significativa estimulação de culturas probióticas do gênero Lactobacillus e Bifidobacterium, e sem estimulação significativa de bactérias enteropatogênicas como a S. enteritidis e E. coli, em experimentos in vitro. Estes resultados indicam o grande potencial destas linhagens fúngicas para a degradação de matrizes hemicelulósicas, para a obtenção de compostos hidrolisados com características prebióticasAbstract: In this present work, six basidiomycete strains were evaluated using five different lignocelulosic agricultural residues as substrates. These fungi were cultivated under non-agitated conditions for 30 days. Searching for the best strains able to produce lignocellulolytic enzymes, hidrolise these growth substrates and generate compounds having prebiotic activity, Pleurotus sp BCCB068 and Pleurotus tailândia were selected at 10 days of growth using rice bran as the sole carbon source, because they exibited the best xylanase activities (0.29 and 0.24 U/mL, respectively). Growth of these fungi was optimized using an experimental design, resulting in the increase of xylanase activities to 0.4 and 0.69 U/mL, respectively. The crude extract obtained following growth of these fungi used as enzyme source for the hidrolises of xylan and carboxymethylcellulose matrices, which were degradaded (66.4 and 59.9%), respectively, during 0-60 minutes of hydrolysis, forming xylo- and celo-oligosaccharides, as well as several sugar monomers. Pleurotus sp BCCB068 and Pleurotus tailândia were also used directly to degrade xylan under fermentation during 40 days, produzing xylooligosaccharides and sugars, and showing degradation of 73.6% at the 20th day, and 70,1% at the 5th day, respectively. The hydrolyzed products with positive effect in the degradation of xylan and carboxymethylcellulose were evaluated regarding their prebiotic activity, showing significant stimulation of Lactobacillus and Bifidobacterium. However, no significant stimulation of enteropatogenic bacteria such as S. enteritidis and E. coli, in an in vitro experimentation. These results indicate a great potential of these fungal strains to degrade hemicellulosic materials and produce hydrolyzed compounds with prebiotic characteristicsDoutoradoDoutor em Ciência de Alimento

O trabalho sob demanda via plataformas digitais : emprego, empreendedorismo ou terceira via?

Orientador : Prof. Dr. Marco Aurélio Serau JúniorMonografia (graduação) - Universidade Federal do Paraná, Setor de Ciências Jurídicas, Curso de Graduação em DireitoInclui referências: p. 48-51Resumo: Os avanços das tecnologias de informação e comunicação no contexto da quarta Revolução Industrial, ou Indústria 4.0, propiciaram as condições ideais para o desenvolvimento do trabalho sob demanda por meio de plataformas digitais. Contudo, apesar dos benefícios dessa economia plataformizada para a economia em geral, encontra-se ainda sem solução definitiva no Brasil o problema do desamparo legal suportado pelos(as) trabalhadores(as) desse trabalho uberizado. Três hipóteses de solução a essa questão foram suscitadas por esta pesquisa bibliográfica: a classificação como empregado formal, a saída via empreendedorismo, e uma hipótese alternativa, via legislação específica. Como temática ligada ao Direito do Trabalho, foi dada ênfase à busca pela solução mais protetiva possível a essa nova classe de trabalhadores. Para tanto, resgatou-se o histórico do Direito do Trabalho em âmbito internacional e, especialmente, nacional. Em seguida, delineou-se as características do trabalho on-demand, suas espécies e perfil dos seus trabalhadores. Diante das hipóteses elencadas, a da classificação como emprego formal mostrou-se a mais protetiva, enquanto a solução alternativa, por meio da criação de lei que atenda às especificidades desta nova configuração trabalhista, despontou como a mais factível do ponto de vista pragmático.Abstract: Advances in information and communication technologies in the context of the fourth Industrial Revolution, or Industry 4.0, provided the ideal conditions for the development of work on demand through digital platforms. However, despite the benefits of this platform economy for the economy in general, the problem of legal helplessness borne by workers in this uberized work is still unresolved in Brazil. Three hypotheses for solving this question were raised by this bibliographical research: classification as a formal employee, exit via entrepreneurship, and an alternative hypothesis, via specific legislation. As a theme linked to Labor Law, emphasis was placed on the search for the most protective solution possible for this new class of workers. For this purpose, the history of Labor Law at an international and, especially, national level was retrieved. Then, the characteristics of on-demand work, its species and the profile of its workers were outlined. Given the hypotheses listed, the classification as formal employment proved to be the most protective, while the alternative solution, through the creation of a law that meets the specificities of this new labor configuration, emerged as the most feasible from a pragmatic point of view

Predicting school achievement rather than intelligence: does metacognition matter?

This paper investigates the role of specific and general metacognitive ability on specific and general academic achievement, controlling for the effects of intelligence. Four hypotheses were elaborated and empirically tested through structural equation modelling. The sample was composed by 684 students (6th to 12th graders) from a private Brazilian school, which answered to three intelligence tests and three metacognitive tests. The modeled hypotheses presented a good data-fit (χ² = 51.18; df = 19; CFI = 1.00; RMSEA = 0.05), showing that the general metacognitive ability explained general academic achievement rather than intelligence, but did not explain specific academic achievement. On the other hand, specific metacognitive ability explained specific academic achievement rather than intelligence, but did not explain general academic achievement. The predictive power of the general metacognitive ability was greater than fluid intelligence in the explanation of general academic achievement. In the same line, specific metacognitive ability had a greater predictive power than intelligence and specific knowledge in the explanation of specific academic achievement. Finally, a new structural model of metacognition and its role in academic achievement are proposed

Quantifying the degradation of radio maps in Wi-Fi fingerprinting

One of the most common assumptions regarding indoor positioning systems based on Wi-Fi fingerprinting is that the Radio Map (RM) becomes outdated and has to be updated to maintain the positioning performance. It is known that propagation effects, the addition/removal of Access Points (APs), changes in the indoor layout, among others, cause RMs to become outdated. However, there is a lack of studies that show how the RM degrades over time. In this paper, we describe an empirical study, based on real-world experiments, to evaluate how and why RMs degrade over time. We conducted site surveys and deployed monitoring devices to analyse the radio environment of one building over 2+ years, which allowed us to identify significant changes/events that caused the degradation of RMs. To quantify the RM degradation, we use the positioning error and propose the RM degradation ratio, a metric to directly compare two RMs and measure how different they are. Obtained results show that the positioning performance is much better when RMs are collected on the same day as the test data, and although RM degradation tends to increase over time, it only leads to large positioning errors when significant changes occur in the Wi-Fi infrastructure, making previous RMs outdated.This work has been supported by FCT - Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020 and the PhD fellowship PD/BD/137401/2018. J. Torres-Sospedra acknowledges funding from Torres Quevedo programme (PTQ2018-009981)

Floor plan-free particle filter for indoor positioning of industrial vehicles

Industry 4.0 is triggering the rapid development of solutions for indoor localization of industrial ve- hicles in the factories of the future. Either to support indoor navigation or to improve the operations of the factory, the localization of industrial vehicles imposes demanding requirements such as high accuracy, coverage of the entire operating area, low convergence time and high reliability. Industrial vehicles can be located using Wi-Fi fingerprinting, although with large positioning errors. In addition, these vehicles may be tracked with motion sensors, however an initial position is necessary and these sensors often suffer from cumulative errors (e.g. drift in the heading). To overcome these problems, we propose an indoor positioning system (IPS) based on a particle filter that combines Wi-Fi fingerprinting with data from motion sensors (displacement and heading). Wi-Fi position estimates are obtained using a novel approach, which explores signal strength measurements from multiple Wi-Fi interfaces. This IPS is capable of locating a vehicle prototype without prior knowledge of the starting position and heading, without depending on the building’s floor plan. An average positioning error of 0.74 m was achieved in performed tests in a factory-like building.FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020, the PhD fellowship PD/BD/137401/2018 and the Technological Development in the scope of the projects in co-promotion no 002814/2015 (iFACTORY 2015-2018

Dioptra - A Data Generation Application for Indoor Positioning Systems

Indoor Positioning Systems (IPSs) based on different approaches and technologies have been proposed to support localization and navigation applications in indoor environments. The fair benchmarking and comparison of these IPSs is a difficult task since each IPS is usually evaluated in very specific and controlled conditions and using private data sets, not allowing reproducibility and direct comparison between the reported results and other competing solutions. In addition, testing and evaluating an IPS in the real world is difficult and time-consuming, especially when considering evaluation in multiple environments and conditions. To enhance IPS assessment, we propose Dioptra, an open access and user-friendly application to support research, development and evaluation of IPSs through simulation. To the best of our knowledge, Dioptra is the first application specially developed to generate synthetic datasets to promote reproducibility and fair benchmarking between IPSs.This work has been supported by FCT - Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020 and the PhD fellowship PD/BD/137401/2018. J. Torres-Sospedra acknowledges funding from Programa Torres Quevedo (PTQ2018-009981)