Industrial Internet of Things over 5G: A Practical Implementation.

The next generation of mobile broadband communication, 5G, is seen as a driver for the industrial Internet of things (IIoT). The expected 5G-increased performance spanning across different indicators, flexibility to tailor the network to the needs of specific use cases, and the inherent security that offers guarantees both in terms of performance and data isolation have triggered the emergence of the concept of public network integrated non-public network (PNI-NPN) 5G networks. These networks might be a flexible alternative for the well-known (albeit mostly proprietary) Ethernet wired connections and protocols commonly used in the industry setting. With that in mind, this paper presents a practical implementation of IIoT over 5G composed of different infrastructure and application components. From the infrastructure perspective, the implementation includes a 5G Internet of things (IoT) end device that collects sensing data from shop floor assets and the surrounding environment and makes these data available over an industrial 5G Network. Application-wise, the implementation includes an intelligent assistant that consumes such data to generate valuable insights that allow for the sustainable operation of assets. These components have been tested and validated in a real shop floor environment at Bosch Termotecnologia (Bosch TT). Results show the potential of 5G as an enhancer of IIoT towards smarter, more sustainable, green, and environmentally friendly factories.

Planning and Optimization of Software-Defined and Virtualized IoT Gateway Deployment for Smart Campuses.

The Internet of Things (IoT) is based on objects or "things" that have the ability to communicate and transfer data. Due to the large number of connected objects and devices, there has been a rapid growth in the amount of data that are transferred over the Internet. To support this increase, the heterogeneity of devices and their geographical distributions, there is a need for IoT gateways that can cope with this demand. The SOFTWAY4IoT project, which was funded by the National Education and Research Network (RNP), has developed a software-defined and virtualized IoT gateway that supports multiple wireless communication technologies and fog/cloud environment integration. In this work, we propose a planning method that uses optimization models for the deployment of IoT gateways in smart campuses. The presented models aimed to quantify the minimum number of IoT gateways that is necessary to cover the desired area and their positions and to distribute IoT devices to the respective gateways. For this purpose, the communication technology range and the data link consumption were defined as the parameters for the optimization models. Three models are presented, which use LoRa, Wi-Fi, and BLE communication technologies. The gateway deployment problem was solved in two steps: first, the gateways were quantified using a linear programming model; second, the gateway positions and the distribution of IoT devices were calculated using the classical K-means clustering algorithm and the metaheuristic particle swarm optimization. Case studies and experiments were conducted at the Samambaia Campus of the Federal University of Goiás as an example. Finally, an analysis of the three models was performed, using metrics such as the silhouette coefficient. Non-parametric hypothesis tests were also applied to the performed experiments to verify that the proposed models did not produce results using the same population.

Flight Planning Optimization of Multiple UAVs for Internet of Things.

This article presents an approach to autonomous flight planning of Unmanned Aerial Vehicles (UAVs)-Drones as data collectors to the Internet of Things (IoT). We have proposed a model for only one aircraft, as well as for multiple ones. A clustering technique that extends the scope of the number of IoT devices (e.g., sensors) visited by UAVs is also addressed. The flight plan generated from the model focuses on preventing breakdowns due to a lack of battery charge to maximize the number of nodes visited. In addition to the drone autonomous flight planning, a data storage limitation aspect is also considered. We have presented the energy consumption of drones based on the aerodynamic characteristics of the type of aircraft. Simulations show the algorithm's behavior in generating routes, and the model is evaluated using a reliability metric.

A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring.

The environment consists of the interaction between the physical, biotic, and anthropic means. As this interaction is dynamic, environmental characteristics tend to change naturally over time, requiring continuous monitoring. In this scenario, the internet of things (IoT), together with traditional sensor networks, allows for the monitoring of various environmental aspects such as air, water, atmospheric, and soil conditions, and sending data to different users and remote applications. This paper proposes a Standard-based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring. The platform consists of an IoT network based on the IEEE 1451 standard which has the network capable application processor (NCAP) node (coordinator) and multiple wireless transducers interface module (WTIM) nodes. A WTIM node consists of one or more transducers, a data transfer interface and a processing unit. Thus, with the developed network, it is possible to collect environmental data at different points within a city landscape, to perform analysis of the communication distance between the WTIM nodes, and monitor the number of bytes transferred according to each network node. In addition, a dynamic model of data flow is proposed where the performance of the NCAP and WTIM nodes are described through state variables, relating directly to the information exchange dynamics between the communicating nodes in the mesh network. The modeling results showed stability in the network. Such stability means that the network has capacity of preserve its flow of information, for a long period of time, without loss frames or packets due to congestion.

TIP4.0: Industrial Internet of Things Platform for Predictive Maintenance.

Industry 4.0, allied with the growth and democratization of Artificial Intelligence (AI) and the advent of IoT, is paving the way for the complete digitization and automation of industrial processes. Maintenance is one of these processes, where the introduction of a predictive approach, as opposed to the traditional techniques, is expected to considerably improve the industry maintenance strategies with gains such as reduced downtime, improved equipment effectiveness, lower maintenance costs, increased return on assets, risk mitigation, and, ultimately, profitable growth. With predictive maintenance, dedicated sensors monitor the critical points of assets. The sensor data then feed into machine learning algorithms that can infer the asset health status and inform operators and decision-makers. With this in mind, in this paper, we present TIP4.0, a platform for predictive maintenance based on a modular software solution for edge computing gateways. TIP4.0 is built around Yocto, which makes it readily available and compliant with Commercial Off-the-Shelf (COTS) or proprietary hardware. TIP4.0 was conceived with an industry mindset with communication interfaces that allow it to serve sensor networks in the shop floor and modular software architecture that allows it to be easily adjusted to new deployment scenarios. To showcase its potential, the TIP4.0 platform was validated over COTS hardware, and we considered a public data-set for the simulation of predictive maintenance scenarios. We used a Convolution Neural Network (CNN) architecture, which provided competitive performance over the state-of-the-art approaches, while being approximately four-times and two-times faster than the uncompressed model inference on the Central Processing Unit (CPU) and Graphical Processing Unit, respectively. These results highlight the capabilities of distributed large-scale edge computing over industrial scenarios.

IoT Sensing Platform as a Driver for Digital Farming in Rural Africa.

Small-scale farming can benefit from the usage of information and communication technology (ICT) to improve crop and soil management and increase yield. However, in order to introduce digital farming in rural areas, related ICT solutions must be viable, seamless and easy to use, since most farmers are not acquainted with technology. With that in mind, this paper proposes an Internet of Things (IoT) sensing platform that provides information on the state of the soil and surrounding environment in terms of pH, moisture, texture, colour, air temperature, and light. This platform is coupled with computer vision to further analyze and understand soil characteristics. Moreover, the platform hardware is housed in a specifically designed robust casing to allow easy assembly, transport, and protection from the deployment environment. To achieve requirements of usability and reproducibility, the architecture of the IoT sensing platform is based on low-cost, off-the-shelf hardware and software modularity, following a do-it-yourself approach and supporting further extension. In-lab validations of the platform were carried out to finetune its components, showing the platform's potential for application in rural areas by introducing digital farming to small-scale farmers, and help them delivering better produce and increasing income.

DYNASTI-Dynamic Multiple RPL Instances for Multiple IoT Applications in Smart City.

Internet of Things (IoT) is evolving to multi-application scenarios in smart cities, which demand specific traffic patterns and requirements. Multi-applications share resources from a single multi-hop wireless networks, where smart devices collaborate to send collected data over a Low-Power and Lossy Networks (LLNs). Routing Protocol for LLNs (RPL) emerged as a routing protocol to be used in IoT scenarios where the devices have limited resources. Instances are RPL mechanisms that play a key role in order to support the IoT scenarios with multiple applications, but it is not standardized yet. Although there are related works proposing multiple instances in RPL on the same IoT network, those works still have limitations to support multiple applications. For instance, there is a lack of flexibility and dynamism in management of multiple instances and service differentiation for applications. In this context, the goal of this work is to develop a solution called DYNAmic multiple RPL instanceS for multiple ioT applicatIons (DYNASTI), which provides more dynamism and flexibility by managing multiple instances of RPL. As a result of this, the traffic performance of multiple applications is enhanced through the routing, taking into consideration the distinct requirements of the applications. In addition, DYNASTI enables the support of sporadic applications as well as the coexistence between regular and sporadic applications. DYNASTI achieved results that demonstrate a significant improvement in reducing the number of control messages, which resulted in increased packet received, decreased end-to-end delay, reduced energy consumption, and an improvement in service differentiation to multiple applications.

A review of Cushing's disease treatment by the Department of Neuroendocrinology of the Brazilian Society of Endocrinology and Metabolism

ABSTRACT The treatment objectives for a patient with Cushing's disease (CD) are remission of hypercortisolism, adequate management of co-morbidities, restoration of the hypothalamic-pituitary-adrenal axis, preservation of fertility and pituitary function, and improvement of visual defects in cases of macroadenomas with suprasellar extension. Transsphenoidal pituitary surgery is the main treatment option for the majority of cases, even in macroadenomas with low probability of remission. In cases of surgical failure, another subsequent pituitary surgery might be indicated in cases with persistent tumor imaging at post surgical magnetic resonance imaging (MRI) and/or pathology analysis of adrenocorticotropic hormone-positive (ACTH+) positive pituitary adenoma in the first procedure. Medical treatment, radiotherapy and adrenalectomy are the other options when transsphenoidal pituitary surgery fails. There are several options of medical treatment, although cabergoline and ketoconazole are the most commonly used alone or in combination. Novel treatments are also addressed in this review. Different therapeutic approaches are frequently needed on an individual basis, both before and, particularly, after surgery, and they should be individualized. The objective of the present review is to provide the necessary information to achieve a more effective treatment for CD. It is recommended that patients with CD be followed at tertiary care centers with experience in treating this condition.

Recommendations of the Neuroendocrinology Department of the Brazilian Society of Endocrinology and Metabolism for the diagnosis of Cushing's disease in Brazil

ABSTRACT Although it is a rare condition, the accurate diagnosis and treatment of Cushing’s disease is important due to its higher morbidity and mortality compared to the general population, which is attributed to cardiovascular diseases, diabetes mellitus and infections. Screening for hypercortisolism is recommended for patients who present multiple and progressive clinical signs and symptoms, especially those who are considered to be more specific to Cushing’s syndrome, abnormal findings relative to age (e.g., spinal osteoporosis and high blood pressure in young patients), weight gain associated with reduced growth rate in the pediatric population and for those with adrenal incidentalomas. Routine screening is not recommended for other groups of patients, such as those with obesity or diabetes mellitus. Magnetic resonance imaging (MRI) of the pituitary, the corticotropin-releasing hormone (CRH) test and the high-dose dexamethasone suppression test are the main tests for the differential diagnosis of ACTH-dependent Cushing’s syndrome. Bilateral and simultaneous petrosal sinus sampling is the gold standard method and is performed when the triad of initial tests is inconclusive, doubtful or conflicting. The aim of this article is to provide information on the early detection and establishment of a proper diagnosis of Cushing’s disease, recommending follow-up of these patients at experienced referral centers. Arch Endocrinol Metab. 2016;60(3):267-86.

Relação da capacidade de exercício com a qualidade de vida de adolescentes asmáticos / Relationship between exercise capacity and quality of life in adolescents with asthma

OBJETIVO: Determinar se parâmetros obtidos antes e depois da realização do teste do degrau de seis minutos (TD6), respostas espirométricas após o TD6 e o nível de atividade física se correlacionam com a qualidade de vida de adolescentes asmáticos. MÉTODOS: Foram avaliados 19 adolescentes asmáticos, com idades variando de 11-15 anos, por meio de espirometria, TD6, International Physical Activity Questionnaire (IPAQ, Questionário Internacional de Atividade Física), Questionário sobre a Qualidade de Vida na Asma Pediátrica (QQVAP) e escala CR10 de Borg. RESULTADOS: Houve correlações negativas entre sensação de dispneia e pontuação total do QQVAP (r = -0,54) e de seus domínios limitação nas atividades (LA) e sintomas (r = -0,64 e r = -0,63, respectivamente), assim como entre fadiga nos membros inferiores (MMII) e os mesmos domínios (r = -0,49 e r = -0,56, respectivamente). O escore total do IPAQ correlacionou-se com a pontuação total do QQVAP (r = 0,47) e o domínio LA (r = 0,51), enquanto o tempo de caminhada correlacionou-se com o domínio sintomas (r = 0,45), e o tempo de atividade intensa correlacionou-se com o domínio LA (r = 0,50). Na análise de regressão, somente a sensação de dispneia associou-se significativamente ao escore total e o domínio limitação nas atividades do QQVAP, e o mesmo ocorreu entre a fadiga dos MMII e o domínio sintomas. CONCLUSÕES: Quanto maior for o nível de atividade física e menor for a dispneia e a fadiga nos MMII, melhor é a qualidade de vida. O TD6 mostrou-se uma opção na avaliação da capacidade ao exercício desses indivíduos por refletir o incômodo que a asma provoca na prática das atividades da vida diária.

OBJECTIVE: To determine whether the quality of life of adolescents with asthma correlates with parameters obtained prior to and after the six-minute step test (6MST); spirometric results after the 6MST; and level of physical activity. METHODS: Nineteen adolescents with asthma, ranging from 11-15 years of age, were assessed with spirometry, 6MST, the International Physical Activity Questionnaire (IPAQ), the Pediatric Asthma Quality of Life Questionnaire (PAQLQ), and the 10-point Borg category-ratio (CR10) scale. RESULTS: Sensation of dyspnea correlated negatively with the total PAQLQ score (r = -0.54) and with the scores of its activity limitation (AL) and symptoms domains (r = -0.64 and r = -0.63, respectively), leg fatigue also correlating negatively with those same domains (r = -0.49 and r = -0.56, respectively). The total IPAQ score correlated with total PAQLQ score (r = 0.47) and with the PAQLQ AL domain (r = 0.51); IPAQ time spent walking correlated with the PAQLQ symptoms domain (r = 0.45); and IPAQ time spent in vigorous activity correlated with the AL domain (r = 0.50). In the regression analysis, only sensation of dyspnea remained significantly correlated with the total PAQLQ score and its AL domain; leg fatigue remained significantly correlated with the symptoms domain. CONCLUSIONS: Higher levels of physical activity indicate better quality of life, as do lower perception of dyspnea and less leg fatigue. The 6MST proved to be a viable option for evaluating exercise capacity in adolescents with asthma, because it reflects the discomfort that asthma causes during activities of daily living.