A learning model for battery lifetime prediction of LoRa sensors in additive manufacturing

Today, an innovative leap for wireless sensor networks, leading to the realization of novel and intelligent industrial measurement systems, is represented by the requirements arising from the Industry 4.0 and Industrial Internet of Things (IIoT) paradigms. In fact, unprecedented challenges to measurement capabilities are being faced, with the ever-increasing need to collect reliable yet accurate data from mobile, battery-powered nodes over potentially large areas. Therefore, optimizing energy consumption and predicting battery life are key issues that need to be accurately addressed in such IoT-based measurement systems. This is the case for the additive manufacturing application considered in this work, where smart battery-powered sensors embedded in manufactured artifacts need to reliably transmit their measured data to better control production and final use, despite being physically inaccessible. A Low Power Wide Area Network (LPWAN), and in particular LoRaWAN (Long Range WAN), represents a promising solution to ensure sensor connectivity in the aforementioned scenario, being optimized to minimize energy consumption while guaranteeing long-range operation and low-cost deployment. In the presented application, LoRa equipped sensors are embedded in artifacts to monitor a set of meaningful parameters throughout their lifetime. In this context, once the sensors are embedded, they are inaccessible, and their only power source is the originally installed battery. Therefore, in this paper, the battery lifetime prediction and estimation problems are thoroughly investigated. For this purpose, an innovative model based on an Artificial Neural Network (ANN) is proposed, developed starting from the discharge curve of lithium-thionyl chloride batteries used in the additive manufacturing application. The results of experimental campaigns carried out on real sensors were compared with those of the model and used to tune it appropriately. The results obtained are encouraging and pave the way for interesting future developments

A Comprehensive Review on Time Sensitive Networks with a Special Focus on Its Applicability to Industrial Smart and Distributed Measurement Systems

The groundbreaking transformations triggered by the Industry 4.0 paradigm have dramati-cally reshaped the requirements for control and communication systems within the factory systems of the future. The aforementioned technological revolution strongly affects industrial smart and distributed measurement systems as well, pointing to ever more integrated and intelligent equipment devoted to derive accurate measurements. Moreover, as factory automation uses ever wider and complex smart distributed measurement systems, the well-known Internet of Things (IoT) paradigm finds its viability also in the industrial context, namely Industrial IoT (IIoT). In this context, communication networks and protocols play a key role, directly impacting on the measurement accuracy, causality, reliability and safety. The requirements coming both from Industry 4.0 and the IIoT, such as the coexistence of time-sensitive and best effort traffic, the need for enhanced horizontal and vertical integration, and interoperability between Information Technology (IT) and Operational Technology (OT), fostered the development of enhanced communication subsystems. Indeed, established tech-nologies, such as Ethernet and Wi-Fi, widespread in the consumer and office fields, are intrinsically non-deterministic and unable to support critical traffic. In the last years, the IEEE 802.1 Working Group defined an extensive set of standards, comprehensively known as Time Sensitive Networking (TSN), aiming at reshaping the Ethernet standard to support for time-, mission-and safety-critical traffic. In this paper, a comprehensive overview of the TSN Working Group standardization activity is provided, while contextualizing TSN within the complex existing industrial technological panorama, particularly focusing on industrial distributed measurement systems. In particular, this paper has to be considered a technical review of the most important features of TSN, while underlining its applicability to the measurement field. Furthermore, the adoption of TSN within the Wi-Fi technology is addressed in the last part of the survey, since wireless communication represents an appealing opportunity in the industrial measurement context. In this respect, a test case is presented, to point out the need for wirelessly connected sensors networks. In particular, by reviewing some literature contributions it has been possible to show how wireless technologies offer the flexibility necessary to support advanced mobile IIoT applications

An IoT Measurement System Based on LoRaWAN for Additive Manufacturing

The Industrial Internet of Things (IIoT) paradigm represents a significant leap forward for sensor networks, potentially enabling wide-area and innovative measurement systems. In this scenario, smart sensors might be equipped with novel low-power and long range communication technologies to realize a so-called low-power wide-area network (LPWAN). One of the most popular representative cases is the LoRaWAN (Long Range WAN) network, where nodes are based on the widespread LoRa physical layer, generally optimized to minimize energy consumption, while guaranteeing long-range coverage and low-cost deployment. Additive manufacturing is a further pillar of the IIoT paradigm, and advanced measurement capabilities may be required to monitor significant parameters during the production of artifacts, as well as to evaluate environmental indicators in the deployment site. To this end, this study addresses some specific LoRa-based smart sensors embedded within artifacts during the early stage of the production phase, as well as their behavior once they have been deployed in the final location. An experimental evaluation was carried out considering two different LoRa end-nodes, namely, the Microchip RN2483 LoRa Mote and the Tinovi PM-IO-5-SM LoRaWAN IO Module. The final goal of this research was to assess the effectiveness of the LoRa-based sensor network design, both in terms of suitability for the aforementioned application and, specifically, in terms of energy consumption and long-range operation capabilities. Energy optimization, battery life prediction, and connectivity range evaluation are key aspects in this application context, since, once the sensors are embedded into artifacts, they will no longer be accessible

Breathlessness and presentation to the emergency department : a survey and clinical record review

BACKGROUND: Breathlessness is a frequently occurring symptom of cardiorespiratory conditions and is a common cause of emergency department presentation. The aim of this study was to estimate the prevalence of acute-on-chronic breathlessness as a cause for presentation to the major emergencies area of the emergency department. METHODS: A prospective patient self-report survey and clinical record review of consecutive attendees to the major emergencies area of the emergency department in a single tertiary hospital between 12/5/14 and 29/5/14 was conducted. Eligible patients were clinically stable and had mental capacity to provide data. RESULTS: There were 2,041 presentations during the study period, of whom 1,345 (66%) were eligible. There was a 90% survey response rate (1,212/1,345); 424/1,212 (35%) self-reported breathlessness most days over the past month of whom 245 gave breathlessness as a reason for this presentation. Therefore, the prevalence of acute-on-chronic breathlessness as a reason to present to the major emergencies area was 20.2% (245/1,212, 95% CI 17.9% to 22.5%). During this period there were 4,692 major and minor presentations; breathlessness was therefore a cause of at least 5.2% (245/4,692, 95% CI 4.6 to 5.9%) of all emergency department presentations. CONCLUSIONS: This study found that one in five ambulance presentations to the ED were due to acute-on-chronic breathlessness. Most patients had non-malignant underlying conditions, had experienced considerable breathlessness for an extended period, had discussed breathlessness with their GP and presented out of daytime hours. Others were often involved in their decision to present. This represents clinically significant burden for patients, their family carers and the emergency health services

Vitamin A deficiency alters the pulmonary parenchymal elastic modulus and elastic fiber concentration in rats

BACKGROUND: Bronchial hyperreactivity is influenced by properties of the conducting airways and the surrounding pulmonary parenchyma, which is tethered to the conducting airways. Vitamin A deficiency (VAD) is associated with an increase in airway hyperreactivity in rats and a decrease in the volume density of alveoli and alveolar ducts. To better define the effects of VAD on the mechanical properties of the pulmonary parenchyma, we have studied the elastic modulus, elastic fibers and elastin gene-expression in rats with VAD, which were supplemented with retinoic acid (RA) or remained unsupplemented. METHODS: Parenchymal mechanics were assessed before and after the administration of carbamylcholine (CCh) by determining the bulk and shear moduli of lungs that that had been removed from rats which were vitamin A deficient or received a control diet. Elastin mRNA and insoluble elastin were quantified and elastic fibers were enumerated using morphometric methods. Additional morphometric studies were performed to assess airway contraction and alveolar distortion. RESULTS: VAD produced an approximately 2-fold augmentation in the CCh-mediated increase of the bulk modulus and a significant dampening of the increase in shear modulus after CCh, compared to vitamin A sufficient (VAS) rats. RA-supplementation for up to 21 days did not reverse the effects of VAD on the elastic modulus. VAD was also associated with a decrease in the concentration of parenchymal elastic fibers, which was restored and was accompanied by an increase in tropoelastin mRNA after 12 days of RA-treatment. Lung elastin, which was resistant to 0.1 N NaOH at 98°, decreased in VAD and was not restored after 21 days of RA-treatment. CONCLUSION: Alterations in parenchymal mechanics and structure contribute to bronchial hyperreactivity in VAD but they are not reversed by RA-treatment, in contrast to the VAD-related alterations in the airways

Pulmonary Arterial Stent Implantation in an Adult with Williams Syndrome

We report a 38-year-old patient who presented with pulmonary hypertension and right ventricular dysfunction due to pulmonary artery stenoses as a manifestation of Williams syndrome, mimicking chronic thromboembolic pulmonary hypertension. The patient was treated with balloon angioplasty and stent implantation. Short-term follow-up showed a good clinical result with excellent patency of the stents but early restenosis of the segments in which only balloon angioplasty was performed. These stenoses were subsequently also treated successfully by stent implantation. Stent patency was observed 3 years after the first procedure

The impact of rate adaptation algorithms on wi-fi-based factory automation systems

Factory automation systems based on the IEEE 802.11 Wi-Fi standard may benefit from its Multi-Rate Support (MRS) feature, which allows for dynamically selecting the most suitable transmission rate for the targeted application context. The MRS is implemented by means of rate adaptation algorithms (RAAs), which has already demonstrated to be effective to improve both timeliness and reliability, which are typically strict requirements of industrial real-time communication systems. Indeed, some of such algorithms have been specifically conceived for reliable real-time communications. However, the computational complexity of such algorithms has not been effectively investigated yet. In this paper, we address such an issue, particularly focusing on the execution times of some specific rate adaptation algorithms, as well as on their impact on the automation tasks. In this respect, after a formal description of the algorithms, we present the outcomes of an extensive experimental session, which includes practical measurements and realistic simulations. The obtained results are encouraging, since the measured execution times indicate that rate adaptation algorithms can be profitably adopted by industrial automation systems, allowing for improving their reliability and timeliness without impacting on the overall performance