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[EN] In recent years, there is an important trend in the organization of cross country races and popular races where hundred people usually participate. In these events, runners usually subject the body to extreme situations that can lead to various types of indisposition and they can also suffer falls. Currently, the electronic systems used in this type of racing refer only to whether a runner has passed through a checkpoint. However, it is necessary to implement systems that allow controlling the population of runners knowing their status all the time. For this reason, this paper proposes the design of a low-cost system for monitoring and controlling runners in this type of event. The system is formed by a network architecture in infrastructure mode based on Low-Power Wide-Area Network (LPWAN) technology. Each runner will carry an electronic device that will give their position and vital signs to be monitored. Likewise, it will incorporate an S.O.S. button that will allow sending a warning to the organization in order to help the person. All these data will be sent through the network to a database that will allow the organization and the public attending the race to check where the runner is and the history of their vital signs. This paper shows the proposed design to our system. Therefore, the paper will show the different practical experiments we have been carried out with the devices that have allowed proposing this design.

[EN] In recent years, there is an important trend in the organization of cross country races and popular races where hundred people usually participate. In these events, runners usually subject the body to extreme situations that can lead to various types of indisposition and they can also suffer falls. Currently, the electronic systems used in this type of racing refer only to whether a runner has passed through a checkpoint. However, it is necessary to implement systems that allow controlling the population of runners knowing their status all the time. For this reason, this paper proposes the design of a low-cost system for monitoring and controlling runners in this type of event. The system is formed by a network architecture in infrastructure mode based on Low-Power Wide-Area Network (LPWAN) technology. Each runner will carry an electronic device that will give their position and vital signs to be monitored. Likewise, it will incorporate an S.O.S. button that will allow sending a warning to the organization in order to help the person. All these data will be sent through the network to a database that will allow the organization and the public attending the race to check where the runner is and the history of their vital signs. This paper shows the proposed design to our system. Therefore, the paper will show the different practical experiments we have been carried out with the devices that have allowed proposing this design.

The construction of bridges has been necessary for societies since ancient times, when the communication between and within towns, cities or communities was established. Until recently, the economic factor has been the only one considered in the decision-making of any type of construction process for bridges. However, nowadays, the objective should not be just the construction of bridges, but of sustainable bridges. Economic, social and environmental factors, which form the three pillars of sustainability, have been recently added. These three factors usually have conflicting perspectives. The decision-making process allows the conversion of a judgment into a rational procedure to reach a compromise solution. The aim of this paper is to review different methods and sustainable criteria used for decision-making at each life-cycle phase of a bridge, from design to recycling or demolition. This paper examines 77 journal articles for which different methods have been used. The most used methods are briefly described. In addition, a statistical study was carried out on the Multiple Attribute Decision-making papers reviewed.

The construction of bridges has been necessary for societies since ancient times, when the communication between and within towns, cities or communities was established. Until recently, the economic factor has been the only one considered in the decision-making of any type of construction process for bridges. However, nowadays, the objective should not be just the construction of bridges, but of sustainable bridges. Economic, social and environmental factors, which form the three pillars of sustainability, have been recently added. These three factors usually have conflicting perspectives. The decision-making process allows the conversion of a judgment into a rational procedure to reach a compromise solution. The aim of this paper is to review different methods and sustainable criteria used for decision-making at each life-cycle phase of a bridge, from design to recycling or demolition. This paper examines 77 journal articles for which different methods have been used. The most used methods are briefly described. In addition, a statistical study was carried out on the Multiple Attribute Decision-making papers reviewed.

In this paper, we consider an extended version of Whitehead s theory of gravity in connection with the flyby anomaly. Whitehead s theory is a linear approximation defined in a background Minkowski spacetime, which gives the same solutions as standard general relativity for the Schwarzschild and Kerr metrics cast in Kerr Schild coordinates. For a long time and because it gives the same results for the three classical tests perihelion advance, light bending and gravitational redshift it was considered a viable alternative to general relativity, but as it is really a linear approximation, it fails in more stringent tests. The model considered in this paper is a formal generalization of Whitehead s theory, including all possible bilinear forms. In the resulting theory, a circulating vector field of force in the low velocities approximation for a rotating planet is deduced, in addition to Newtonian gravity. This extra force gives rise to small variations in the asymptotic velocities of flybys around the Earth to be compared to the recently reported flyby anomaly.

In this paper, we consider an extended version of Whitehead s theory of gravity in connection with the flyby anomaly. Whitehead s theory is a linear approximation defined in a background Minkowski spacetime, which gives the same solutions as standard general relativity for the Schwarzschild and Kerr metrics cast in Kerr Schild coordinates. For a long time and because it gives the same results for the three classical tests perihelion advance, light bending and gravitational redshift it was considered a viable alternative to general relativity, but as it is really a linear approximation, it fails in more stringent tests. The model considered in this paper is a formal generalization of Whitehead s theory, including all possible bilinear forms. In the resulting theory, a circulating vector field of force in the low velocities approximation for a rotating planet is deduced, in addition to Newtonian gravity. This extra force gives rise to small variations in the asymptotic velocities of flybys around the Earth to be compared to the recently reported flyby anomaly.

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client s requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client s requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client s requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client s requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

This paper proposes and assesses an integrated solution to monitor and diagnose photovoltaic (PV) solar modules based on a decentralized wireless sensor acquisition system. Both DC electrical variables and environmental data are collected at PV module level using low-cost and high-energy efficiency node sensors. Data is real-time processed locally and compared with expected PV module performances obtained by a PV module model based on symmetrized-shifted Gompertz functions (as previously developed and assessed by the authors). Sensor nodes send data to a centralized sink-computing module using a multi-hop wireless sensor network architecture. Such integration thus provides extensive analysis of PV installations, and avoids off-line tests or post-processing processes. In comparison with previous approaches, this solution is enhanced with a low-cost system and non-critical performance constraints, and it is suitable for extensive deployment in PV power plants. Moreover, it is easily implemented in existing PV installations, since no additional wiring is required. The system has been implemented and assessed in a Spanish PV power plant connected to the grid. Results and estimations of PV module performances are also included in the paper.

[EN] In many control applications, the sensor technology used for the measurement of the variable to be controlled is not able to maintain a restricted sampling period. In this context, the assumption of regular and uniform sampling pattern is questionable. Moreover, if the control action updating can be faster than the output measurement frequency in order to fulfill the proposed closed loop behavior, the solution is usually a multirate controller. There are some known aspects to be careful of when a multirate system (MR) is going to be designed. The proper multiplicity between input-output sampling periods, the proper controller structure, the existence of ripples and others issues need to be considered. A useful way to save time and achieve good results is to have an assisted computer design tool. An interactive simulation tool to deal with MR seems to be the right solution. In this paper this kind of simulation application is presented. It allows an easy understanding of the performance degrading or improvement when changing the multirate sampling pattern parameters. The tool was developed using Sysquake, a Matlab-like language with fast execution and powerful graphic facilities. It can be delivered as an executable. In the paper a detailed explanation of MR treatment is also included and the design of four different MR controllers with flexible structure to be adapted to different schemes will also be presented. The Smith's predictor in these MR schemes is also explained, justified and used when time delays appear. Finally some interesting observations achieved using this interactive tool are included.

[EN] Artificial Intelligence techniques have being applied to many problems in manufacturing systems in recent years. In the specific field of manufacturing scheduling many studies have been published trying to cope with the complexity of the manufacturing environment. One of the most utilized approaches is (multi) agent-based scheduling. Nevertheless, despite the large list of studies reported in this field, there is no resource or scientific study on the performance measure of this type of approach under very common and critical execution situations. This paper focuses on multi-agent systems (MAS) based algorithms for task allocation, particularly in manufacturing applications. The goal is to provide a mechanism to measure the performance of agent-based scheduling approaches for manufacturing systems under key critical situations such as: dynamic environment, rescheduling, and priority change. With this mechanism it will be possible to simulate critical situations and to stress the system in order to measure the performance of a given agent-based scheduling method. The proposed mechanism is a pioneering approach for performance evaluation of bidding-based MAS approaches for manufacturing scheduling. The proposed method and evaluation methodology can be used to run tests in different manufacturing floors since it is independent of the workshop configuration. Moreover, the evaluation results presented in this paper show the key factors and scenarios that most affect the market-like MAS approaches for manufacturing scheduling.

Missing traces in ground penetrating radar (GPR) B-scans (radargrams) may appear because of limited scanning resolution, failures during the acquisition process or the lack of accessibility to some areas under test. Four statistical interpolation methods for recovering these missing traces are compared in this paper: Kriging, Wiener structures, Splines and the expectation assuming an independent component analyzers mixture model (E-ICAMM). Kriging is an adaptation to the spatial context of the linear least mean squared error estimator. Wiener structures improve the linear estimator by including a nonlinear scalar function. Splines are a commonly used method to interpolate GPR traces. This consists of piecewise-defined polynomial curves that are smooth at the connections (or knots) between pieces. E-ICAMM is a new method proposed in this paper. E-ICAMM consists of computing the optimum nonlinear estimator (the conditional mean) assuming a non-Gaussian mixture model for the joint probability density in the observation space. The proposed methods were tested on a set of simulated data and a set of real data, and four performance indicators were computed. Real data were obtained by GPR inspection of two replicas of historical walls. Results show the superiority of E-ICAMM in comparison with the other three methods in the application of reconstructing incomplete B-scans.

[EN] Artificial Intelligence techniques have being applied to many problems in manufacturing systems in recent years. In the specific field of manufacturing scheduling many studies have been published trying to cope with the complexity of the manufacturing environment. One of the most utilized approaches is (multi) agent-based scheduling. Nevertheless, despite the large list of studies reported in this field, there is no resource or scientific study on the performance measure of this type of approach under very common and critical execution situations. This paper focuses on multi-agent systems (MAS) based algorithms for task allocation, particularly in manufacturing applications. The goal is to provide a mechanism to measure the performance of agent-based scheduling approaches for manufacturing systems under key critical situations such as: dynamic environment, rescheduling, and priority change. With this mechanism it will be possible to simulate critical situations and to stress the system in order to measure the performance of a given agent-based scheduling method. The proposed mechanism is a pioneering approach for performance evaluation of bidding-based MAS approaches for manufacturing scheduling. The proposed method and evaluation methodology can be used to run tests in different manufacturing floors since it is independent of the workshop configuration. Moreover, the evaluation results presented in this paper show the key factors and scenarios that most affect the market-like MAS approaches for manufacturing scheduling.

[EN] Artificial Intelligence techniques have being applied to many problems in manufacturing systems in recent years. In the specific field of manufacturing scheduling many studies have been published trying to cope with the complexity of the manufacturing environment. One of the most utilized approaches is (multi) agent-based scheduling. Nevertheless, despite the large list of studies reported in this field, there is no resource or scientific study on the performance measure of this type of approach under very common and critical execution situations. This paper focuses on multi-agent systems (MAS) based algorithms for task allocation, particularly in manufacturing applications. The goal is to provide a mechanism to measure the performance of agent-based scheduling approaches for manufacturing systems under key critical situations such as: dynamic environment, rescheduling, and priority change. With this mechanism it will be possible to simulate critical situations and to stress the system in order to measure the performance of a given agent-based scheduling method. The proposed mechanism is a pioneering approach for performance evaluation of bidding-based MAS approaches for manufacturing scheduling. The proposed method and evaluation methodology can be used to run tests in different manufacturing floors since it is independent of the workshop configuration. Moreover, the evaluation results presented in this paper show the key factors and scenarios that most affect the market-like MAS approaches for manufacturing scheduling.

Missing traces in ground penetrating radar (GPR) B-scans (radargrams) may appear because of limited scanning resolution, failures during the acquisition process or the lack of accessibility to some areas under test. Four statistical interpolation methods for recovering these missing traces are compared in this paper: Kriging, Wiener structures, Splines and the expectation assuming an independent component analyzers mixture model (E-ICAMM). Kriging is an adaptation to the spatial context of the linear least mean squared error estimator. Wiener structures improve the linear estimator by including a nonlinear scalar function. Splines are a commonly used method to interpolate GPR traces. This consists of piecewise-defined polynomial curves that are smooth at the connections (or knots) between pieces. E-ICAMM is a new method proposed in this paper. E-ICAMM consists of computing the optimum nonlinear estimator (the conditional mean) assuming a non-Gaussian mixture model for the joint probability density in the observation space. The proposed methods were tested on a set of simulated data and a set of real data, and four performance indicators were computed. Real data were obtained by GPR inspection of two replicas of historical walls. Results show the superiority of E-ICAMM in comparison with the other three methods in the application of reconstructing incomplete B-scans.

[EN] In many control applications, the sensor technology used for the measurement of the variable to be controlled is not able to maintain a restricted sampling period. In this context, the assumption of regular and uniform sampling pattern is questionable. Moreover, if the control action updating can be faster than the output measurement frequency in order to fulfill the proposed closed loop behavior, the solution is usually a multirate controller. There are some known aspects to be careful of when a multirate system (MR) is going to be designed. The proper multiplicity between input-output sampling periods, the proper controller structure, the existence of ripples and others issues need to be considered. A useful way to save time and achieve good results is to have an assisted computer design tool. An interactive simulation tool to deal with MR seems to be the right solution. In this paper this kind of simulation application is presented. It allows an easy understanding of the performance degrading or improvement when changing the multirate sampling pattern parameters. The tool was developed using Sysquake, a Matlab-like language with fast execution and powerful graphic facilities. It can be delivered as an executable. In the paper a detailed explanation of MR treatment is also included and the design of four different MR controllers with flexible structure to be adapted to different schemes will also be presented. The Smith's predictor in these MR schemes is also explained, justified and used when time delays appear. Finally some interesting observations achieved using this interactive tool are included.

[EN] Abiotic stress represents a main constraint for agriculture, affecting plant growth and productivity. Drought and soil salinity, especially, are major causes of reduction of crop yields and food production worldwide. It is not unexpected, therefore, that the study of plant responses to abiotic stress and stress tolerance mechanisms is one of the most active research fields in plant biology. This Special Issue compiles 22 research papers and 4 reviews covering different aspects of these responses and mechanisms, addressing environmental stress factors such as drought, salinity, flooding, heat and cold stress, deficiency or toxicity of compounds in the soil (e.g., macro and micronutrients), and combination of different stresses. The approaches used are also diverse, including, among others, the analysis of agronomic traits based on morphological characteristics, physiological and biochemical studies, and transcriptomics or transgenics. Despite its complexity, we believe that this Special Issue provides a useful overview of the topic, including basic information on the mechanisms of abiotic stress tolerance as well as practical aspects such as the alleviation of the deleterious effects of stress by different means, or the use of local landraces as a source of genetic material adapted to combined stresses. This knowledge should help to develop the agriculture of the (near) future, sustainable and better adapted to the conditions ahead, in a scenario of global warming and environmental pollution.

[EN] Abiotic stress represents a main constraint for agriculture, affecting plant growth and productivity. Drought and soil salinity, especially, are major causes of reduction of crop yields and food production worldwide. It is not unexpected, therefore, that the study of plant responses to abiotic stress and stress tolerance mechanisms is one of the most active research fields in plant biology. This Special Issue compiles 22 research papers and 4 reviews covering different aspects of these responses and mechanisms, addressing environmental stress factors such as drought, salinity, flooding, heat and cold stress, deficiency or toxicity of compounds in the soil (e.g., macro and micronutrients), and combination of different stresses. The approaches used are also diverse, including, among others, the analysis of agronomic traits based on morphological characteristics, physiological and biochemical studies, and transcriptomics or transgenics. Despite its complexity, we believe that this Special Issue provides a useful overview of the topic, including basic information on the mechanisms of abiotic stress tolerance as well as practical aspects such as the alleviation of the deleterious effects of stress by different means, or the use of local landraces as a source of genetic material adapted to combined stresses. This knowledge should help to develop the agriculture of the (near) future, sustainable and better adapted to the conditions ahead, in a scenario of global warming and environmental pollution.

[EN] To understand soil erosion processes, it is vital to know how the weather types and atmospheric situations, and their distribution throughout the year, affect the soil erosion rates. This will allow for the development of efficient land management practices to mitigate water-induced soil losses. Vineyards are one of the cultivated areas susceptible to high soil erosion rates. However, there is a lack of studies that link weather types and atmospheric conditions to soil erosion responses in viticultural areas. Thus, the main aim of this research is to assess the impacts of weather types and atmospheric conditions on soil erosion processes in a conventional vineyard with tillage in eastern Spain. To achieve this goal, rainfall events from 2006 to 2017 were monitored and the associated runoff and soil loss were collected from experimental plots. Our results showed that the highest volume of runoff and soil erosion is linked to rainfall associated with the eastern winds that accounted for 59.7% of runoff and 63.9% of soil loss, while cold drops in the atmospheric situation classifications emerged as the highest contributor of 40.9% in runoff and 44.1% in soil loss. This paper provides new insights into the development of soil erosion control measures that help to mitigate the negative impact of extreme rainfall and runoff considering atmospheric conditions.

[EN] Improving water efficiency in farming systems is one of the major challenges of these decades. Water scarcity due to climate change, together with the increasing demand of food, is leading experts from around the world find appropriate indicators for water-use efficiency. In this paper we propose and test different indicators for service delivery performance, productive efficiency, and economic efficiency. Since the characteristics of the studied area and the citrus cropping system in the East of Spain are particular, we include in our analysis two other variables which are key to understanding the changes in the indicators: the obtained productivity, and the applied irrigation. The indicators and these two variables are tested with the information provided by farmers of citrus orchards belonging to an irrigation community from the East of Spain. The effect of different factors, such as cultivated varieties, type of farmer (professional or non-professional), or plantations' size, are evaluated against the productivity and irrigation performance of the evaluated orchards. The effect of excess of irrigation on the indicators is also studied with the previous factors. Finally, an artificial intelligence system is used to predict productive efficiency of an orchard, based on the size and the water supply. Among the proposed indicators, the service delivery performance indicators came out to be the least useful and might provoke overirrigation due to the lack of accuracy of the data used for its calculation. The productive and economic efficiency indicators have been useful to illustrate the remarkable effect that excess of irrigation has on water efficiency, since a reduction of 66% of productive efficiency is found for some of the analysed varieties. On other cases, a reduction of 50% in economic efficiency is detected due to the excess of irrigation. Moreover, the excess of irrigation implied higher economic efficiency in only one of the evaluated varieties.

[EN] Metal containers are the most commonly used packaging worldwide in both the food and beverage industry. Some manufacturing processes in the canning industry include multi-step transformations that take large aluminum or steel coils and make them into two or three-piece cans. During this process, the containers are sprayed to obtain a better surface for the contents; however, this spray produces volatile organic compounds (VOC). This paper presents a new and environmentally friendly can manufacturing method, which uses a novel pre-laminated two-layer polymer steel. As experimentally proven, this innovative polymer-coated steel successfully withstands every manufacturing requirement. The specimens were tested in an ironing simulator, measuring roughness and friction coefficients. The development of an upper bound ironing model, along with a supporting neural network, allows an insight into the design of new materials for can manufacturing.

[EN] Risk management in agriculture is at the heart of major reforms in many OECD countries and European agricultural policies. Price risks, which are generally not insurable per se, have been covered by the Common Agricultural Policy (CAP), which has been shaped as a system of protection against market shocks and an instrument for income stabilization. However, there is an increasing propensity to combine the use of public and private risk management tools as well. In Spain, revenue insurance has not yet developed in the same way as other risk coverage insurance, although it is an upcoming target of agricultural insurance policies with the aim of ensuring income stability for agricultural producers. This paper presents the results of the methodology used to draw up a composition index or model of the average price for the season or representative market field price to be used for revenue insurance purposes in citrus fruit. High explanatory power regression models and the analytic hierarchy process (AHP) were used. The results show that the average price for the season obtained reliably represents the market field prices in the country's various producer areas.

[EN] To understand soil erosion processes, it is vital to know how the weather types and atmospheric situations, and their distribution throughout the year, affect the soil erosion rates. This will allow for the development of efficient land management practices to mitigate water-induced soil losses. Vineyards are one of the cultivated areas susceptible to high soil erosion rates. However, there is a lack of studies that link weather types and atmospheric conditions to soil erosion responses in viticultural areas. Thus, the main aim of this research is to assess the impacts of weather types and atmospheric conditions on soil erosion processes in a conventional vineyard with tillage in eastern Spain. To achieve this goal, rainfall events from 2006 to 2017 were monitored and the associated runoff and soil loss were collected from experimental plots. Our results showed that the highest volume of runoff and soil erosion is linked to rainfall associated with the eastern winds that accounted for 59.7% of runoff and 63.9% of soil loss, while cold drops in the atmospheric situation classifications emerged as the highest contributor of 40.9% in runoff and 44.1% in soil loss. This paper provides new insights into the development of soil erosion control measures that help to mitigate the negative impact of extreme rainfall and runoff considering atmospheric conditions.

[EN] Improving water efficiency in farming systems is one of the major challenges of these decades. Water scarcity due to climate change, together with the increasing demand of food, is leading experts from around the world find appropriate indicators for water-use efficiency. In this paper we propose and test different indicators for service delivery performance, productive efficiency, and economic efficiency. Since the characteristics of the studied area and the citrus cropping system in the East of Spain are particular, we include in our analysis two other variables which are key to understanding the changes in the indicators: the obtained productivity, and the applied irrigation. The indicators and these two variables are tested with the information provided by farmers of citrus orchards belonging to an irrigation community from the East of Spain. The effect of different factors, such as cultivated varieties, type of farmer (professional or non-professional), or plantations' size, are evaluated against the productivity and irrigation performance of the evaluated orchards. The effect of excess of irrigation on the indicators is also studied with the previous factors. Finally, an artificial intelligence system is used to predict productive efficiency of an orchard, based on the size and the water supply. Among the proposed indicators, the service delivery performance indicators came out to be the least useful and might provoke overirrigation due to the lack of accuracy of the data used for its calculation. The productive and economic efficiency indicators have been useful to illustrate the remarkable effect that excess of irrigation has on water efficiency, since a reduction of 66% of productive efficiency is found for some of the analysed varieties. On other cases, a reduction of 50% in economic efficiency is detected due to the excess of irrigation. Moreover, the excess of irrigation implied higher economic efficiency in only one of the evaluated varieties.

[EN] The information that crops offer is turned into profitable decisions only when efficiently managed. Current advances in data management are making Smart Farming grow exponentially as data have become the key element in modern agriculture to help producers with critical decision-making. Valuable advantages appear with objective information acquired through sensors with the aim of maximizing productivity and sustainability. This kind of data-based managed farms rely on data that can increase efficiency by avoiding the misuse of resources and the pollution of the environment. Data-driven agriculture, with the help of robotic solutions incorporating artificial intelligent techniques, sets the grounds for the sustainable agriculture of the future. This paper reviews the current status of advanced farm management systems by revisiting each crucial step, from data acquisition in crop fields to variable rate applications, so that growers can make optimized decisions to save money while protecting the environment and transforming how food will be produced to sustainably match the forthcoming population growth.

[EN] To understand soil erosion processes, it is vital to know how the weather types and atmospheric situations, and their distribution throughout the year, affect the soil erosion rates. This will allow for the development of efficient land management practices to mitigate water-induced soil losses. Vineyards are one of the cultivated areas susceptible to high soil erosion rates. However, there is a lack of studies that link weather types and atmospheric conditions to soil erosion responses in viticultural areas. Thus, the main aim of this research is to assess the impacts of weather types and atmospheric conditions on soil erosion processes in a conventional vineyard with tillage in eastern Spain. To achieve this goal, rainfall events from 2006 to 2017 were monitored and the associated runoff and soil loss were collected from experimental plots. Our results showed that the highest volume of runoff and soil erosion is linked to rainfall associated with the eastern winds that accounted for 59.7% of runoff and 63.9% of soil loss, while cold drops in the atmospheric situation classifications emerged as the highest contributor of 40.9% in runoff and 44.1% in soil loss. This paper provides new insights into the development of soil erosion control measures that help to mitigate the negative impact of extreme rainfall and runoff considering atmospheric conditions.

[EN] Improving water efficiency in farming systems is one of the major challenges of these decades. Water scarcity due to climate change, together with the increasing demand of food, is leading experts from around the world find appropriate indicators for water-use efficiency. In this paper we propose and test different indicators for service delivery performance, productive efficiency, and economic efficiency. Since the characteristics of the studied area and the citrus cropping system in the East of Spain are particular, we include in our analysis two other variables which are key to understanding the changes in the indicators: the obtained productivity, and the applied irrigation. The indicators and these two variables are tested with the information provided by farmers of citrus orchards belonging to an irrigation community from the East of Spain. The effect of different factors, such as cultivated varieties, type of farmer (professional or non-professional), or plantations' size, are evaluated against the productivity and irrigation performance of the evaluated orchards. The effect of excess of irrigation on the indicators is also studied with the previous factors. Finally, an artificial intelligence system is used to predict productive efficiency of an orchard, based on the size and the water supply. Among the proposed indicators, the service delivery performance indicators came out to be the least useful and might provoke overirrigation due to the lack of accuracy of the data used for its calculation. The productive and economic efficiency indicators have been useful to illustrate the remarkable effect that excess of irrigation has on water efficiency, since a reduction of 66% of productive efficiency is found for some of the analysed varieties. On other cases, a reduction of 50% in economic efficiency is detected due to the excess of irrigation. Moreover, the excess of irrigation implied higher economic efficiency in only one of the evaluated varieties.

[EN] The information that crops offer is turned into profitable decisions only when efficiently managed. Current advances in data management are making Smart Farming grow exponentially as data have become the key element in modern agriculture to help producers with critical decision-making. Valuable advantages appear with objective information acquired through sensors with the aim of maximizing productivity and sustainability. This kind of data-based managed farms rely on data that can increase efficiency by avoiding the misuse of resources and the pollution of the environment. Data-driven agriculture, with the help of robotic solutions incorporating artificial intelligent techniques, sets the grounds for the sustainable agriculture of the future. This paper reviews the current status of advanced farm management systems by revisiting each crucial step, from data acquisition in crop fields to variable rate applications, so that growers can make optimized decisions to save money while protecting the environment and transforming how food will be produced to sustainably match the forthcoming population growth.

[EN] Norharmane is a secondary metabolite that appears in different species of land plants. In this paper, we investigated for the first time the specificity of norharmane through germination and growth tests on some crops as Zea mays L. (maize), Triticum aestivum L. (wheat), Oryza sativa L. (rice) and Lactuca sativa L. (lettuce) and weeds as Amaranthus retroflexus L. (amaranth), Echinochloa crus-galli L. (barnyard grass), Plantago lanceolata L. (ribwort), Portulaca oleracea L. (common purslane) and Avena fatua L. (wild oat), and its phytotoxic capacity on the metabolism of adult Arabidopsis thaliana L. (thale cress) by measuring chlorophyll a fluorescence, pigment content, total proteins, osmotic potential and morphological analysis. Norharmane had an inhibitory effect on the germination of A. fatua and P. lanceolata, and the growth of P. oleracea, E. crus-galli and A. retroflexus. On adult A. thaliana plants, the compound was more effective to watering, leading to water stress that compromised the growth of the plants and ultimately affected the photosynthetic apparatus. Therefore, this research shows that norharmane not only affects seedlings' metabolism, but also damages the metabolism of adult plants and can be a potential model for a future bioherbicide given its specificity.

[EN] The paper presents a numerical energy harvesting model for sensor nodes, SIVEH (Simulator I–V for EH), based on I–V hardware tracking. I–V tracking is demonstrated to be more accurate than traditional energy modeling techniques when some of the components present different power dissipation at either different operating voltages or drawn currents. SIVEH numerical computing allows fast simulation of long periods of time—days, weeks, months or years—using real solar radiation curves. Moreover, SIVEH modeling has been enhanced with sleep time rate dynamic adjustment, while seeking energy-neutral operation. This paper presents the model description, a functional verification and a critical comparison with the classic energy approach

The mudejar church of Santa Maria (Ateca) is valuable for its architecture and the altarpiece contained inside. Ateca is a village with continental climate characterized by cold winters and hot summers. In this paper we are interested in analysing the effect of temperature and relative humidity (RH) changes produced by the heating system on the altarpiece. Therefore, a monitoring system of 15 temperature and 15 relative humidity sensors was installed with a recording frequency of a data point per minute. The main contribution of this paper is the quantitative study of the effect of the heating system on the thermo-hygrometric parameters using statistical techniques such as ANOVA, mean daily trajectories or bivariate plots, and the proposal of an innovative dynamic contour plot. As results, the heating system produces a substantial increase (decrease) of temperature (RH) causing an hourly variation of these physical parameters detrimental to the conservation of the altarpiece, especially in its higher areas.

[EN] This paper addresses the problem of leakage in water distribution systems through the use of ground penetrating radar (GPR) as a nondestructive method. Laboratory tests are performed to extract features of water leakage from the obtained GPR images. Moreover, a test in a real-world urban system under real conditions is performed. Feature extraction is performed by interpreting GPR images with the support of a pre-processing methodology based on an appropriate combination of statistical methods and multi-agent systems. The results of these tests are presented, interpreted, analyzed and discussed in this paper.

[EN] The paper presents a numerical energy harvesting model for sensor nodes, SIVEH (Simulator I–V for EH), based on I–V hardware tracking. I–V tracking is demonstrated to be more accurate than traditional energy modeling techniques when some of the components present different power dissipation at either different operating voltages or drawn currents. SIVEH numerical computing allows fast simulation of long periods of time—days, weeks, months or years—using real solar radiation curves. Moreover, SIVEH modeling has been enhanced with sleep time rate dynamic adjustment, while seeking energy-neutral operation. This paper presents the model description, a functional verification and a critical comparison with the classic energy approach

Cultural Heritage preventive conservation requires the monitoring of the parameters involved in the process of deterioration of artworks. Thus, both long-term monitoring of the environmental parameters as well as further analysis of the recorded data are necessary. The long-term monitoring at frequencies higher than 1 data point/day generates large volumes of data that are difficult to store, manage and analyze. This paper presents software which uses a free open source database engine that allows managing and interacting with huge amounts of data from environmental monitoring of cultural heritage sites. It is of simple operation and offers multiple capabilities, such as detection of anomalous data, inquiries, graph plotting and mean trajectories. It is also possible to export the data to a spreadsheet for analyses with more advanced statistical methods (principal component analysis, ANOVA, linear regression, etc.). This paper also deals with a practical application developed for the Renaissance frescoes of the Cathedral of Valencia. The results suggest infiltration of rainwater in the vault and weekly relative humidity changes related with the religious service schedules.

The mudejar church of Santa Maria (Ateca) is valuable for its architecture and the altarpiece contained inside. Ateca is a village with continental climate characterized by cold winters and hot summers. In this paper we are interested in analysing the effect of temperature and relative humidity (RH) changes produced by the heating system on the altarpiece. Therefore, a monitoring system of 15 temperature and 15 relative humidity sensors was installed with a recording frequency of a data point per minute. The main contribution of this paper is the quantitative study of the effect of the heating system on the thermo-hygrometric parameters using statistical techniques such as ANOVA, mean daily trajectories or bivariate plots, and the proposal of an innovative dynamic contour plot. As results, the heating system produces a substantial increase (decrease) of temperature (RH) causing an hourly variation of these physical parameters detrimental to the conservation of the altarpiece, especially in its higher areas.

[EN] This paper addresses the problem of leakage in water distribution systems through the use of ground penetrating radar (GPR) as a nondestructive method. Laboratory tests are performed to extract features of water leakage from the obtained GPR images. Moreover, a test in a real-world urban system under real conditions is performed. Feature extraction is performed by interpreting GPR images with the support of a pre-processing methodology based on an appropriate combination of statistical methods and multi-agent systems. The results of these tests are presented, interpreted, analyzed and discussed in this paper.

The number of appliances at home is increasing continuously, mainly because they make our lives easier. Currently, technology is integrated in all objects of our daily life. TCP/IP let us monitor our home in real time and check ubiquitously if something is happening at home. Bearing in mind this idea, we have developed a low-cost system, which can be used in any type of electrical household appliance that takes information from the appliance and posts the information to the Twitter Social network. Several sensors placed in the household appliances gather the sensed data and send them wired or wirelessly, depending on the case, using small and cheap devices to a gateway located in the home. This gateway takes decisions, based on the received data, and sends notifications to Twitter. We have developed a software application that takes the values and decides when to issue an alarm to the registered users (Twitter friends of our smart home). The performance of our system has been measured taking into account the home network (using IEEE 802.3u and IEEE 802.11g) and the data publishing in Twitter. As a result, we have generated an original product and service for any electrical household appliance, regardless of the model and manufacturer, that helps home users improve their quality of life. The paper also shows that there is no system with the same innovative features like the ones presented in this paper.

Current mobile phones come with several sensors and powerful video cameras. These video cameras can be used to capture good quality scenes, which can be complemented with the information gathered by the sensors also embedded in the phones. For example, the surroundings of a beach recorded by the camera of the mobile phone, jointly with the temperature of the site can let users know via the Internet if the weather is nice enough to swim. In this paper, we present a system that tags the video frames of the video recorded from mobile phones with the data collected by the embedded sensors. The tagged video is uploaded to a video server, which is placed on the Internet and is accessible by any user. The proposed system uses a semantic approach with the stored information in order to make easy and efficient video searches. Our experimental results show that it is possible to tag video frames in real time and send the tagged video to the server with very low packet delay variations. As far as we know there is not any other application developed as the one presented in this paper.

The number of appliances at home is increasing continuously, mainly because they make our lives easier. Currently, technology is integrated in all objects of our daily life. TCP/IP let us monitor our home in real time and check ubiquitously if something is happening at home. Bearing in mind this idea, we have developed a low-cost system, which can be used in any type of electrical household appliance that takes information from the appliance and posts the information to the Twitter Social network. Several sensors placed in the household appliances gather the sensed data and send them wired or wirelessly, depending on the case, using small and cheap devices to a gateway located in the home. This gateway takes decisions, based on the received data, and sends notifications to Twitter. We have developed a software application that takes the values and decides when to issue an alarm to the registered users (Twitter friends of our smart home). The performance of our system has been measured taking into account the home network (using IEEE 802.3u and IEEE 802.11g) and the data publishing in Twitter. As a result, we have generated an original product and service for any electrical household appliance, regardless of the model and manufacturer, that helps home users improve their quality of life. The paper also shows that there is no system with the same innovative features like the ones presented in this paper.

The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis. © 2011 by the authors; licensee MDPI, Basel, Switzerland.

The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis. © 2011 by the authors; licensee MDPI, Basel, Switzerland.

[EN] Passive microclimate frames are exhibition enclosures able to modify their internal climate in order to comply with paintings¿ conservation needs. Due to a growing concern about the effects of climate change, future policies in conservation must move towards affordable and sustainable preservation strategies. This study investigated the hygrothermal conditions monitored within a microclimate frame hosting a portrait on cardboard with the aim of discussing its use in view of the climate expected indoors in the period 2041¿2070. Its effectiveness in terms of the ASHRAE classification and of the Lifetime Multiplier for chemical deterioration of paper was assessed comparing temperature and relative humidity values simultaneously measured inside the microclimate frame and in its surrounding environment, first in the Pio V Museum and later in a residential building, both located in the area of Valencia (Spain). Moreover, heat and moisture transfer functions were used to derive projections over the future indoor hygrothermal conditions in response to the ENSEMBLES-A1B outdoor scenario. The adoption of microclimate frames proved to be an effective preventive conservation action in current and future conditions but it may not be sufficient to fully avoid the chemical degradation risk without an additional control over temperature

[EN] New technologies have the potential to transform agriculture and to reduce environmental impact through a green revolution. Internet of Things (IoT)-based application development platforms have the potential to run farm management tools capable of monitoring real-time events when integrated into interactive innovation models for fertirrigation. Their capabilities must extend to flexible reconfiguration of programmed actions. IoT platforms require complex smart decision-making systems based on data-analysis and data mining of big data sets. In this paper, the advantages are demonstrated of a powerful tool that applies real-time decisions from data such as variable rate irrigation, and selected parameters from field and weather conditions. The field parameters, the index vegetation (estimated using aerial images), and the irrigation events, such as flow level, pressure level, and wind speed, are periodically sampled. Data is processed in a decision-making system based on learning prediction rules in conjunction with the Drools rule engine. The multimedia platform can be remotely controlled, and offers a smart farming open data network with shared restriction levels for information exchange oriented to farmers, the fertilizer provider, and agricultural technicians that should provide the farmer with added value in the form of better decision making or more efficient exploitation operations and management.

Several insect species pose a serious threat to different plant species, sometimes becoming a pest that produces significant damage to the landscape, biodiversity, and/or the economy. This is the case of Rhynchophorus ferrugineus Olivier (Coleoptera: Dryophthoridae), Semanotus laurasii Lucas (Coleoptera: Cerambycidae), and Monochamus galloprovincialis Olivier (Coleoptera: Cerambycidae), which have become serious threats to ornamental and productive trees all over the world such as palm trees, cypresses, and pines. Knowledge about their flight potential is very important for designing and applying measures targeted to reduce the negative effects from these pests. Studying the flight capability and behaviour of some insects is difficult due to their small size and the large area wherein they can fly, so we wondered how we could obtain information about their flight capabilities in a controlled environment. The answer came with the design of flight mills. Relevant data about the flight potential of these insects may be recorded and analysed by means of a flight mill. Once an insect is attached to the flight mill, it is able to fly in a circular direction without hitting walls or objects. By adding sensors to the flight mill, it is possible to record the number of revolutions and flight time. This paper presents a full description of a computer monitored flight mill. The description covers both the mechanical and the electronic parts in detail. The mill was designed to easily adapt to the anatomy of different insects and was successfully tested with individuals from three species R. ferrugineus, S. laurasii, and M. galloprovincialis.

[EN] The use of massive multiple-input multiple-output (MIMO) techniques for communication at millimeter-Wave (mmW) frequency bands has become a key enabler to meet the data rate demands of the upcoming fifth generation (5G) cellular systems. In particular, analog and hybrid beamforming solutions are receiving increasing attention as less expensive and more power efficient alternatives to fully digital precoding schemes. Despite their proven good performance in simple setups, their suitability for realistic cellular systems with many interfering base stations and users is still unclear. Furthermore, the performance of massive MIMO beamforming and precoding methods are in practice also affected by practical limitations and hardware constraints. In this sense, this paper assesses the performance of digital precoding and analog beamforming in an urban cellular system with an accurate mmW channel model under both ideal and realistic assumptions. The results show that analog beamforming can reach the performance of fully digital maximum ratio transmission under line of sight conditions and with a sufficient number of parallel radio-frequency (RF) chains, especially when the practical limitations of outdated channel information and per antenna power constraints are considered. This work also shows the impact of the phase shifter errors and combiner losses introduced by real phase shifter and combiner implementations over analog beamforming, where the former ones have minor impact on the performance, while the latter ones determine the optimum number of RF chains to be used in practice.

Video surveillance is needed to control many activities performed in underwater environments. The use of wired media can be a problem since the material specially designed for underwater environments is very expensive. In order to transmit the images and videos wirelessly under water, three main technologies can be used: acoustic waves, which do not provide high bandwidth, optical signals, although the effect of light dispersion in water severely penalizes the transmitted signals and therefore, despite offering high transfer rates, the maximum distance is very small, and electromagnetic (EM) waves, which can provide enough bandwidth for video delivery. In the cases where the distance between transmitter and receiver is short, the use of EM waves would be an interesting option since they provide high enough data transfer rates to transmit videos with high resolution. This paper presents a practical study of the behavior of EM waves at 2.4 GHz in freshwater underwater environments. First, we discuss the minimum requirements of a network to allow video delivery. From these results, we measure the maximum distance between nodes and the round trip time (RTT) value depending on several parameters such as data transfer rate, signal modulations, working frequency, and water temperature. The results are statistically analyzed to determine their relation. Finally, the EM waves behavior is modeled by a set of equations. The results show that there are some combinations of working frequency, modulation, transfer rate and temperature that offer better results than others. Our work shows that short communication distances with high data transfer rates is feasible.

Whole-body 123I-Metaiodobenzylguanidine (mIBG) scintigraphy is used as primary image modality to visualize neuroblastoma tumours and metastases because it is the most sensitive and specific radioactive tracer in staging the disease and evaluating the response to treatment. However, especially in paediatric neuroblastoma, information from mIBG scans is difficult to extract because of acquisition difficulties that produce low definition images, with poor contours, resolution and contrast. These problems limit physician assessment. Current oncological guidelines are based on qualitative observer-dependant analysis. This makes comparing results taken at different moments of therapy, or in different institutions, difficult. In this paper, we present a computerized method that processes an image and calculates a quantitative measurement considered as its entropy, suitable for the identification of abnormal uptake regions, for which there is enough suspicion that they may be a tumour or metastatic site. This measurement can also be compared with future scintigraphies of the same patient. Over 46 scintigraphies of 22 anonymous patients were tested; the procedure identified 96.7% of regions of abnormal uptake and it showed a low overall false negative rate of 3.3%. This method provides assistance to physicians in diagnosing tumours and also allows the monitoring of patients’ evolution.

The Internet of Things (IoT) is, at this moment, one of the most promising technologies that has arisen for decades. Wireless Sensor Networks (WSNs) are one of the main pillars for many IoT applications, insofar as they require to obtain context-awareness information. The bibliography shows many difficulties in their real implementation that have prevented its massive deployment. Additionally, in IoT environments where data producers and data consumers are not directly related, compatibility and certification issues become fundamental. Both problems would profit from accurate knowledge of the internal behavior of WSNs that must be obtained by the utilization of appropriate tools. There are many ad-hoc proposals with no common structure or methodology, and intended to monitor a particular WSN. To overcome this problem, this paper proposes a structured three -layer reference model for WSN Monitoring Platforms (WSN-MP), which offers a standard environment for the design of new monitoring platforms to debug, verify and certify a WSN's behavior and performance, and applicable to every WSN. This model also allows the comparative analysis of the current proposals for monitoring the operation of WSNs. Following this methodology, it is possible to achieve a standardization of WSN-MP, promoting new research areas in order to solve the problems of each layer.

[EN] Water scarcity is a critical environmental issue worldwide, especially in arid and semiarid regions. In those regions, climate change projections suggest further reductions in freshwater supplies and increases of the recurrence, longevity and intensity of drought events. At present, one important question for policy debate is the identification of water policies that could address the mounting water scarcity problems. Suitable policies should improve economic efficiency, achieve environmental sustainability, and meet equity needs. This paper develops and applies an integrated hydro-economic model that links hydrological, economic and environmental elements to such issues. The model is used to conduct a direct comparison of water markets, water pricing and institutional cooperation, based on their economic, environmental and equity outcomes. The analysis is performed in the Jucar Basin of Spain, which is a good natural experiment for studying water scarcity and climate change policies. Results indicate that both institutional and water market policies are high performing instruments to limit the economic damage costs of droughts, achieving almost the same social benefits. However, the environmental effects of water markets are worrying. Another important finding is that water pricing is a poor policy option not only in terms of private and environmental benefits but also in terms of equity. Guardar / Salir Siguiente >

[EN] This paper presents a new application of photogrammetric techniques for protecting cultural heritage. The accuracy of the method and the fact that it can be used to carry out different tests without contact between the sample and the instruments can make this technique very useful for authenticating and cataloging artworks. The application focuses on the field of pictorial artworks, and wooden panel paintings in particular. In these works, the orography formed by the brushstrokes can be easily digitalized using a photogrammetric technique, called Structured Light System, with submillimeter accuracy. Thus, some of the physical characteristics of the brushstrokes, like minimum and maximum heights or slopes become a fingerprint of the painting. We explain in detail the general principles of the Structured Light System Technique and the specific characteristics of the commercial set-up used in this work. Some experiments are carried out on a sample painted by us to check the accuracy limits of the technique and to propose some tests that can help to stablish a methodology for authentication purposes. Finally, some preliminary results obtained on a real pictorial artwork are presented, providing geometrical information of its metric features as an example of the possibilities of this application