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The increasing prominence of concepts such as Smart Production and Industrial Internet of Things (IIoT) within the context of Industry 4.0 has introduced a new set of requirements for the engineering of industrial systems, including support for dynamic environments, timeliness guarantees, support for heterogeneity, interoperability and reliability. These requirements are further exacerbated at the network level by the notable rise in the number and variety of devices involved. To stay competitive in this ever-changing industrial landscape while boosting productivity, it is vital to meet those requirements, combining established protocols with emerging technologies. Software-Defined Networking (SDN) is the forefront traffic management paradigm that offers flexibility for complex industrial networks, enabling efficient resource allocation and dynamic reconfiguration. Message Queuing Telemetry Transport (MQTT) is a low-overhead protocol of the application layer that is gaining popularity in the scope of the IoT and IIoT. However, its Quality-of-Service (QoS) policies do not support timeliness requirements. This article presents a framework that seamlessly integrates SDN and MQTT, enhancing network management flexibility while satisfying real-time requirements found in industrial environments. It leverages the User Properties of MQTTv5 to allow specifying real-time requirements. MQTT traffic is intercepted by a Network Manager that extracts real-time information and instructs an SDN controller to deploy corresponding network reservations. MQTT traffic across multiple edge networks is propagated by selected brokers using multicasting. Extensive experiments validate the proposed approach, demonstrating its superiority over MQTT and Direct Multicast-MQTT (DM-MQTT) DM-MQTT in latency reduction. A response time analysis, validated experimentally, emphasizes robust performance across metrics.

The main purpose of this project was the eco-valorisation of the tomato plant residues. The chemical product design method was used to select the best idea based on 4 steps: needs, ideas, selection, and manufacturing. Liquid xylitol is here proposed for the valorisation of tomato plant residues, which is an alternative sweetener with a lower glycemic index that can be produced from the hemicellulose found in leaves and stems. Its production would require an alkaline extraction with sodium hydroxide, enzymatic hydrolyses using endo-1,4-β-xylanase, and yeast fermentation with Candida tropicalis. Liquid sweetener with 72% xylitol and other components (D-glucose, D-mannose, D-galactose, L-arabinose, and lignin), commercialised as NITS - Natural Incredible Tomato Sweetener, could be sold for 2.25 €·L-1 for companies and the same price per bottle of 500 mL for individual consumption.

Background: The COVID-19 pandemic has posed greater financial pressure on health systems and institutions that had to respond to the specific needs of COVID-19 patients while ensuring the safety of the diagnosis and treatment of all patients and healthcare professionals. To assess the financial impact of COVID-19 patients admitted to hospitals, we have characterized the cost of COVID-19 admissions, using inpatient data from a Portuguese Tertiary Care University Centre. Methods: We analysed inpatient data from adult patients diagnosed with COVID-19 who were admitted between March 1, 2020 and May 31, 2020. Admissions were eligible if the ICD-10-CM principal diagnosis was coded U07.1. We excluded admissions from patients under 18 years old, admissions with incomplete records, admissions from patients who had been transferred to or from other hospitals or those whose inpatient stay was under 24 h. Pregnancy, childbirth, and puerperium admissions were also excluded, as well as admissions from patients who had undergone surgery. Results: We identified 223 admissions of patients diagnosed with COVID-19. Most were men (64.1%) and aged 45–64 years (30.5%). Around 13.0% of patients were admitted to intensive care units and 9.9% died in hospital. The average length of hospital stay was 12.7 days (SD = 10.2) and the average estimated cost per admission was EUR 8,177 (SD = 11,534), which represents more than triple the inpatient base price (EUR 2,386). Human resources accounted for the highest proportion of the total costs per admission (50.8%). About 92.4% of the admissions were assigned to Diagnosis Related Group (DRG) 723, whose inpatient price is lower than COVID-19 inpatient costs for all degrees of severity. Conclusion: COVID-19 admissions represent a substantial financial burden for the Portuguese NHS. For each COVID-19 hospitalized patient it would have been possible to treat three other hospitalized patients. Also, the price set for DRG 723 is not adjusted to the cost of COVID-19 patients. These findings highlight the need for additional financial resources for the health system and, in particular, for hospitals that have treated high volumes of hospitalized patients diagnosed with COVID-19.

Industry 4.0 and Autonomous Driving are emerging resource-intensive distributed application domains that deal with open and evolving environments. These systems are subject to stringent resource, timing, and other non-functional constraints, as well as frequent reconfiguration. Thus, real-time behavior must not preclude operational flexibility. This combination is motivating ongoing efforts within the Time Sensitive Networking (TSN) standardization committee to define admission control mechanisms for Ethernet. Existing mechanisms in TSN, like those of AVB, its predecessor, follow a distributed architecture that favors scalability. Conversely, the new mechanisms envisaged for TSN (IEEE 802.1Qcc) follow a (partially) centralized architecture, favoring short reconfiguration latency. This paper shows the first quantitative comparison between distributed and centralized admission control architectures concerning reconfiguration latency. Here, we compare AVB against a dynamic real-time reconfigurable Ethernet technology with centralized management, namely HaRTES. Our experiments show a significantly lower latency using the centralized architecture. We also observe the dependence of the distributed architecture in the end nodes' performance and the benefit of having a protected channel for the admission control transactions.

In recent decades, the perception of the impact of humanity’s ecological footprint has changed dramatically; it is now widely recognized that natural resources are limited and sensitive, and that their indiscriminate use is unsustainable and deeply impacts the well-being of people, animals and plants [...]

Industry 4.0 brings in a whole set of new requirements to engineering industrial systems, with notorious impact at the networking layer. A key challenge posed by Industry 4.0 is the operational flexibility needed to support on-the-fly reconfiguration of production cells, stations, and machines. At the networking layer, this flexibility implies dynamic packet handling, scheduling, and dispatching. SoftwareDefined Networking (SDN) provides this level of flexibility in the general Local Area Network (LAN) domain. However, its application in the industry has been hindered by a lack of support for real-time services. This paper addresses this limitation, proposing an extended SDN OpenFlow framework that includes realtime services, leveraging existing real-time data plane Ethernet technologies. We show the OpenFlow enhancements, a real-time SDN controller, and experimental validation and performance assessment. Using a proof-of-concept prototype with 3 switches and cycles of 250μs, we could achieve 1μs jitter on timetriggered traffic and a reconfiguration time between operational modes below 10ms.

MQTT is one of the most popular application-layer protocols used in the scope of the Internet-of-Things (IoT) and Industrial-Internet-of-Things (IIoT), given its suitability for resource-constrained embedded systems. However, MQTT Quality-of-Service policies do not support timeliness requirements, which is common in IIoT. The literature reports several research works that address this limitation, but they are limited in scope (e.g., improvements in the broker’s internal operation, control of the publisher’s data rate, and path optimizations). Conversely, this paper presents a comprehensive architectural approach, proposing a set of extensions to the MQTT protocol that allow applications to explicitly specify real-time requirements and instantiate corresponding network reservations to enforce the desired temporal behavior. Such reservations are enforced via Software Defined Networking, specifically the OpenFlow protocol, but other protocols that allow bandwidth reservations, e.g., TSN, can also be used. This paper presents the proposed system architecture together with extensive emulation and implementation results that validate the feasibility of the approach, showing that time-sensitive MQTT traffic can be effectively segregated and prioritized to meet application-defined real-time requirements. Using several combinations of network topologies and load levels and comparing to the absence of the proposed real-time mechanisms, both average and worst-case latencies of the time-sensitive traffic decreased to approximately half, while for the normal traffic, they increased by approximately 10%.

The Digital Transformation, which has the Internet of Things (IoT) as one of its pillars, is penetrating all aspects of our society with dramatic effects [...]

Weed control in vineyards demands regular interventions that currently consist of the use of machinery, such as plows and brush-cutters, and the application of herbicides. These methods have several drawbacks, including cost, chemical pollution, and the emission of greenhouse gases. The use of animals to weed vineyards, usually ovines, is an ancestral, environmentally friendly, and sustainable practice that was abandoned because of the scarcity and cost of shepherds, which were essential for preventing animals from damaging the vines and grapes. The SheepIT project was developed to automate the role of human shepherds, by monitoring and conditioning the behaviour of grazing animals. Additionally, the data collected in real-time can be used for improving the efficiency of the whole process, e.g., by detecting abnormal situations such as health conditions or attacks and manage the weeding areas. This paper presents a comprehensive set of field-test results, obtained with the SheepIT infrastructure, addressing several dimensions, from the animals’ well-being and their impact on the cultures, to technical aspects, such as system autonomy. The results show that the core objectives of the project have been attained and that it is feasible to use this system, at an industrial scale, in vineyards.

Currently, it is becoming increasingly common to find numerous electronic devices installed in office and residential spaces as part of building automation solutions. These devices provide a rich set of data related to the inside and outside environment, such as indoor and outdoor temperature, humidity, and solar radiation. However, commercial of-the-shelf climatic control systems continue to rely on simple controllers like proportional-integral-derivative or even on-off, which do not take into account such variables. This work evaluates the potential performance gains of adopting more advanced controllers, in this case based on pole-placement, enhanced with additional variables, namely solar radiation and external temperature, obtained with dedicated low-cost sensors. This approach is evaluated both in simulated and real-world environments. The obtained results show that pole-placement controllers clearly outperform on-off controllers and that the use of the additional variables in pole-placement controllers allows relevant performance gains in key parameters such as error signal MSE (17%) and control signal variance (40%), when compared with simple PP controllers. The observed energy consumption savings obtained by using the additional variables are marginal (≈1%, but the reduction of the error signal MSE and control signal variance have a significant impact on energy consumption peaks and on equipment lifetime, thus largely compensating the increase in the system complexity.

In the above article [1], the last funding acknowledgment “[…] and in part by the Research Centre Instituto de Telecomunicações under Grant UID/EEA/50008/2013.” is incorrect and outdated. The correct acknowledgment is “[…] and in part by FCT/MCTES through national funds and when applicable co-funded EU funds under the project UIDB/50008/ 2020-UIDP/50008/2020.”

Intelligent farming is one of the vast range of applications covered by the Internet of Things concept. Notwithstanding, such applications present specific requirements and constraints that are dependent on their purpose. A practical case on which that is particularly relevant is the SheepIT project, where an automated IoT-based system controls grazing sheep within vineyards, guaranteeing that they do not threaten cultures. Due to its rigid requirements, particularly regarding the deployment of the Wireless Sensor Network, Machine-2-Machine communications and necessary interactions with a computational platform available through the Internet, Internet Protocol-based solutions are not suitable. Consequently, a customized communication stack has been developed, that intends to meet the project requirements, from the physical to the Application Layers. Although it has been developed considering the SheepIT requirements, its use may be extended to more generic intelligent farming applications, since most of the requirements are directly related with the farming environment. This paper reviews the proposed stack and details the recent developments. Particularly, we focused on Internet of Things/Machine-2-Machine interaction, describing the design and deployment of a gateway that addresses the SheepIT service requirements. Additionally, and complementary to previously published results, we evaluate the gateway performance and show its feasibility and scalability in a real scenario.

Data networks are naturally prone to interferences that can corrupt messages, leading to performance degradation or even to critical failure of the corresponding distributed system. To improve resilience of critical systems, time-triggered networks are frequently used, based on communication schedules defined at design-time. These networks offer prompt error detection, but slow error recovery that can only be compensated with bandwidth overprovisioning. On the contrary, the Flexible Time-Triggered (FTT) paradigm uses online traffic scheduling, which enables a compromise between error detection and recovery that can achieve timely recovery with a fraction of the needed bandwidth. This article presents a new method to recover transmission errors in a time-triggered Controller Area Network (CAN) network, based on the Flexible Time-Triggered paradigm, namely FTT-CAN. The method is based on using a server (traffic shaper) to regulate the retransmission of corrupted or omitted messages. We show how to design the server to simultaneously: (1) meet a predefined reliability goal, when considering worst case error recovery scenarios bounded probabilistically by a Poisson process that models the fault arrival rate; and, (2) limit the direct and indirect interference in the message set, preserving overall system schedulability. Extensive simulations with multiple scenarios, based on practical and randomly generated systems, show a reduction of two orders of magnitude in the average bandwidth taken by the proposed error recovery mechanism, when compared with traditional approaches available in the literature based on adding extra pre-defined transmission slots.

Background: The COVID-19 pandemic has posed greater financial pressure on health systems and institutions that had to respond to the specific needs of COVID-19 patients while ensuring the safety of the diagnosis and treatment of all patients and healthcare professionals. To assess the financial impact of COVID-19 patients admitted to hospitals, we have characterized the cost of COVID-19 admissions, using inpatient data from a Portuguese Tertiary Care University Centre. Methods: We analysed inpatient data from adult patients diagnosed with COVID-19 who were admitted between March 1, 2020 and May 31, 2020. Admissions were eligible if the ICD-10-CM principal diagnosis was coded U07.1. We excluded admissions from patients under 18 years old, admissions with incomplete records, admissions from patients who had been transferred to or from other hospitals or those whose inpatient stay was under 24 h. Pregnancy, childbirth, and puerperium admissions were also excluded, as well as admissions from patients who had undergone surgery. Results: We identified 223 admissions of patients diagnosed with COVID-19. Most were men (64.1%) and aged 45–64 years (30.5%). Around 13.0% of patients were admitted to intensive care units and 9.9% died in hospital. The average length of hospital stay was 12.7 days (SD = 10.2) and the average estimated cost per admission was EUR 8,177 (SD = 11,534), which represents more than triple the inpatient base price (EUR 2,386). Human resources accounted for the highest proportion of the total costs per admission (50.8%). About 92.4% of the admissions were assigned to Diagnosis Related Group (DRG) 723, whose inpatient price is lower than COVID-19 inpatient costs for all degrees of severity. Conclusion: COVID-19 admissions represent a substantial financial burden for the Portuguese NHS. For each COVID-19 hospitalized patient it would have been possible to treat three other hospitalized patients. Also, the price set for DRG 723 is not adjusted to the cost of COVID-19 patients. These findings highlight the need for additional financial resources for the health system and, in particular, for hospitals that have treated high volumes of hospitalized patients diagnosed with COVID-19. [ABSTRACT FROM AUTHOR]