New Intermediate band sulphide nanoparticles acting in the full visible light range spectra as an active photocatalyst

Nowadays one of the challenges of materials science is to find new technologies that will be able to make the most of renewable energies. An example of new proposals in this field are the intermediate-band (IB) materials, which promise higher efficiencies in photovoltaic applications (through the intermediate band solar cells), or in heterogeneous photocatalysis (using nanoparticles of them, for the light-induced degradation of pollutants or for the efficient photoevolution of hydrogen from water). An IB material consists in a semiconductor in which gap a new level is introduced [1], the intermediate band (IB), which should be partially filled by electrons and completely separated of the valence band (VB) and of the conduction band (CB). This scheme (figure 1) allows an electron from the VB to be promoted to the IB, and from the latter to the CB, upon absorption of photons with energy below the band gap Eg, so that energy can be absorbed in a wider range of the solar spectrum and a higher current can be obtained without sacrificing the photovoltage (or the chemical driving force) corresponding to the full bandgap Eg, thus increasing the overall efficiency. This concept, applied to photocatalysis, would allow using photons of a wider visible range while keeping the same redox capacity. It is important to note that this concept differs from the classic photocatalyst doping principle, which essentially tries just to decrease the bandgap. This new type of materials would keep the full bandgap potential but would use also lower energy photons. In our group several IB materials have been proposed, mainly for the photovoltaic application, based on extensively doping known semiconductors with transition metals [2], examining with DFT calculations their electronic structures. Here we refer to In2S3 and SnS2, which contain octahedral cations; when doped with Ti or V an IB is formed according to quantum calculations (see e.g. figure 2). We have used a solvotermal synthesis method to prepare in nanocrystalline form the In2S3 thiospinel and the layered compound SnS2 (which when undoped have bandgaps of 2.0 and 2.2 eV respectively) where the cation is substituted by vanadium at a ?10% level. This substitution has been studied, characterizing the materials by different physical and chemical techniques (TXRF, XRD, HR-TEM/EDS) (see e.g. figure 3) and verifying with UV spectrometry that this substitution introduces in the spectrum the sub-bandgap features predicted by the calculations (figure 4). For both sulphide type nanoparticles (doped and undoped) the photocatalytic activity was studied by following at room temperature the oxidation of formic acid in aqueous suspension, a simple reaction which is easily monitored by UV-Vis spectroscopy. The spectral response of the process is measured using a collection of band pass filters that allow only some wavelengths into the reaction system. Thanks to this method the spectral range in which the materials are active in the photodecomposition (which coincides with the band gap for the undoped samples) can be checked, proving that for the vanadium substituted samples this range is increased, making possible to cover all the visible light range. Furthermore it is checked that these new materials are more photocorrosion resistant than the toxic CdS witch is a well know compound frequently used in tests of visible light photocatalysis. These materials are thus promising not only for degradation of pollutants (or for photovoltaic cells) but also for efficient photoevolution of hydrogen from water; work in this direction is now being pursued.

A Model-Based Monitoring Architecture for Heterogeneous Enterprise Services and Information Systems

Runtime management of distributed information systems is a complex and costly activity. One of the main challenges that must be addressed is obtaining a complete and updated view of all the managed runtime resources. This article presents a monitoring architecture for heterogeneous and distributed information systems. It is composed of two elements: an information model and an agent infrastructure. The model negates the complexity and variability of these systems and enables the abstraction over non-relevant details. The infrastructure uses this information model to monitor and manage the modeled environment, performing and detecting changes in execution time. The agents infrastructure is further detailed and its components and the relationships between them are explained. Moreover, the proposal is validated through a set of agents that instrument the JEE Glassfish application server, paying special attention to support distributed configuration scenarios.

Multi-agent Architecture for Heterogeneous Reasoning under Uncertainty Combining MSBN and Ontologies in Distributed Network Diagnosis

This article proposes a MAS architecture for network diagnosis under uncertainty. Network diagnosis is divided into two inference processes: hypothesis generation and hypothesis confirmation. The first process is distributed among several agents based on a MSBN, while the second one is carried out by agents using semantic reasoning. A diagnosis ontology has been defined in order to combine both inference processes. To drive the deliberation process, dynamic data about the influence of observations are taken during diagnosis process. In order to achieve quick and reliable diagnoses, this influence is used to choose the best action to perform. This approach has been evaluated in a P2P video streaming scenario. Computational and time improvements are highlight as conclusions.

Heterogeneous Collaborative Sensor Network for Electrical Management of an Automated House with PV Energy

In this paper we present a heterogeneous collaborative sensor network for electrical management in the residential sector. Improving demand-side management is very important in distributed energy generation applications. Sensing and control are the foundations of the “Smart Grid” which is the future of large-scale energy management. The system presented in this paper has been developed on a self-sufficient solar house called “MagicBox” equipped with grid connection, PV generation, lead-acid batteries, controllable appliances and smart metering. Therefore, there is a large number of energy variables to be monitored that allow us to precisely manage the energy performance of the house by means of collaborative sensors. The experimental results, performed on a real house, demonstrate the feasibility of the proposed collaborative system to reduce the consumption of electrical power and to increase energy efficiency.

Fractal Behaviour and Irregularity of Wetting Fronts in Heterogeneous Porous Media

The wetting front is the zone where water invades and advances into an initially dry porous material and it plays a crucial role in solute transport through the unsaturated zone. Water is an essential part of the physiological process of all plants. Through water, necessary minerals are moved from the roots to the parts of the plants that require them. Water moves chemicals from one part of the plant to another. It is also required for photosynthesis, for metabolism and for transpiration. The leaching of chemicals by wetting fronts is influenced by two major factors, namely: the irregularity of the fronts and heterogeneity in the distribution of chemicals, both of which have been described by using fractal techniques. Soil structure can significantly modify infiltration rates and flow pathways in soils. Relations between features of soil structure and features of infiltration could be elucidated from the velocities and the structure of wetting fronts. When rainwater falls onto soil, it doesn?t just pool on surfaces. Water ?or another fluid- acts differently on porous surfaces. If the surface is permeable (porous) it seeps down through layers of soil, filling that layer to capacity. Once that layer is filled, it moves down into the next layer. In sandy soil, water moves quickly, while it moves much slower through clay soil. The movement of water through soil layers is called the the wetting front. Our research concerns the motion of a liquid into an initially dry porous medium. Our work presents a theoretical framework for studying the physical interplay between a stationary wetting front of fractal dimension D with different porous materials. The aim was to model the mass geometry interplay by using the fractal dimension D of a stationary wetting front. The plane corresponding to the image is divided in several squares (the minimum correspond to the pixel size) of size length ". We acknowledge the help of Prof. M. García Velarde and the facilities offered by the Pluri-Disciplinary Institute of the Complutense University of Madrid. We also acknowledge the help of European Community under project Multi-scale complex fluid flows and interfacial phenomena (PITN-GA-2008-214919). Thanks are also due to ERCOFTAC (PELNoT, SIG 14)

Inmovilización de TiO2 sobre polímeros transparentes en el UV-A para la eliminación fotocatalítica de tricloroetileno en aire

El gran desarrollo industrial y demográfico de las últimas décadas ha dado lugar a un consumo crecientemente insostenible de energía y materias primas, que influye negativamente en el ambiente por la gran cantidad de contaminantes generados. Entre las emisiones tienen gran importancia los compuestos orgánicos volátiles (COV), y entre ellos los compuestos halogenados como el tricloroetileno, debido a su elevada toxicidad y resistencia a la degradación. Las tecnologías generalmente empleadas para la degradación de estos compuestos presentan inconvenientes derivados de la generación de productos tóxicos intermedios o su elevado coste. Dentro de los procesos avanzados de oxidación (Advanced Oxidation Processes AOP), la fotocatálisis resulta una técnica atractiva e innovadora de interés creciente en su aplicación para la eliminación de multitud de compuestos orgánicos e inorgánicos, y se ha revelado como una tecnología efectiva en la eliminación de compuestos orgánicos volátiles clorados como el tricloroetileno. Además, al poder aprovechar la luz solar como fuente de radiación UV permite una reducción significativa de costes energéticos y de operación. Los semiconductores más adecuados para su empleo como fotocatalizadores con aprovechamiento de la luz solar son aquellos que tienen una banda de energía comparable a la de los fotones de luz visible o, en su defecto, de luz ultravioleta A (Eg < 3,5 eV), siendo el más empleado el dióxido de titanio (TiO2). El objetivo principal de este trabajo es el estudio de polímeros orgánicos comerciales como soporte para el TiO2 en fotocatálisis heterogénea y su ensayo para la eliminación de tricloroetileno en aire. Para ello, se han evaluado sus propiedades ópticas y su resistencia a la fotodegradación, y se ha optimizado la fijación del fotocatalizador para conseguir un recubrimiento homogéneo, duradero y con elevada actividad fotocatalítica en diversas condiciones de operación. Los materiales plásticos ensayados fueron el polietileno (PE), copolímero de etil vinil acetato con distintos aditivos (EVA, EVA-H y EVA-SH), polipropileno (PP), polimetil (metacrilato) fabricado en colada y extrusión (PMMA-C y PMMA-E), policarbonato compacto y celular (PC-C y PC-Ce), polivinilo rígido y flexible (PVC-R y PVC-F), poliestireno (PS) y poliésteres (PET y PETG). En base a sus propiedades ópticas se seleccionaron el PP, PS, PMMA-C, EVA-SH y PVC-R, los cuales mostraron un valor de transmitancia superior al 80% en el entorno de la región estudiada (λ=365nm). Para la síntesis del fotocatalizador se empleó la tecnología sol-gel y la impregnación multicapa de los polímeros seleccionados por el método de dip-coating con secado intermedio a temperaturas moderadas. Con el fin de evaluar el envejecimiento de los polímeros bajo la radiación UV, y el efecto sobre éste del recubrimiento fotoactivo, se realizó un estudio en una cámara de exposición a la luz solar durante 150 días, evaluándose la resistencia química y la resistencia mecánica. Los resultados de espectroscopía infrarroja y del test de tracción tras el envejecimiento revelaron una mayor resistencia del PMMA y una degradación mayor en el PS, PVC-R y EVA SH, con una apreciable pérdida del recubrimiento en todos los polímeros. Los fotocatalizadores preparados sobre soportes sin tratamiento y con tres capas de óxido de titanio mostraron mejores resultados de actividad con PMMA-C, PET y PS, con buenos resultados de mineralización. Para conseguir una mayor y mejor fijación de la película al soporte se realizaron tratamientos químicos abrasivos con H2SO4 y NaOH y tratamientos de funcionalización superficial por tecnología de plasma a presión atmosférica (APP) y a baja presión (LPP). Con los tratamientos de plasma se consiguió una excelente mojabilidad de los soportes, que dio lugar a una distribución uniforme y más abundante del fotocatalizador, mientras que con los tratamientos químicos no se obtuvo una mejora significativa. Asimismo, se prepararon fotocatalizadores con una capa previa de dióxido de silicio con la intervención de surfactantes (PDDA-SiO2-3TiO2 y SiO2FC-3TiO2), consiguiéndose buenas propiedades de la película en todos los casos. Los mejores resultados de actividad con tratamiento LPP y tres capas de TiO2 se lograron con PMMA-C (91% de conversión a 30 ppm de TCE y caudal 200 ml·min-1) mejorando significativamente también la actividad fotocatalítica en PVC-R y PS. Sin embargo, el material más activo de todos los ensayados fue el PMMA-C con el recubrimiento SiO2FC-3TiO2, logrando el mejor grado de mineralización, del 45%, y una velocidad de 1,89 x 10-6 mol· m-2 · s-1, que dio lugar a la eliminación del 100 % del tricloroetileno en las condiciones anteriormente descritas. A modo comparativo se realizaron ensayos de actividad con otro contaminante orgánico tipo, el formaldehído, cuya degradación fotocatalítica fue también excelente (100% de conversión y 80% de mineralización con 24 ppm de HCHO en un caudal de aire seco de 200 ml·min-1). Los buenos resultados de actividad obtenidos confirman las enormes posibilidades que ofrecen los polímeros transparentes en el UV-A como soportes del dióxido de titanio para la eliminación fotocatalítica de contaminantes en aire. ABSTRACT The great industrial and demographic development of recent decades has led to an unsustainable increase of energy and raw materials consumption that negatively affects the environment due to the large amount of waste and pollutants generated. Between emissions generated organic compounds (VOCs), specially the halogenated ones such as trichloroethylene, are particularly important due to its high toxicity and resistance to degradation. The technologies generally used for the degradation of these compounds have serious inconveniences due to the generation of toxic intermediates turn creating the problem of disposal besides the high cost. Among the advanced oxidation processes (AOP), photocatalysis is an attractive and innovative technique with growing interest in its application for the removal of many organic and inorganic compounds, and has emerged as an effective technology in eliminating chlorinated organic compounds such as trichloroethylene. In addition, as it allows the use of sunlight as a source of UV radiation there is a significant reduction of energy costs and operation. Semiconductors suitable to be used as photocatalyst activated by sunlight are those having an energy band comparable to that of the visible or UV-A light (Eg <3,5 eV), being titanium dioxide (TiO2), the most widely used. The main objective of this study is the test of commercial organic polymers as supports for TiO2 to be applied in heterogeneous photocatalysis and its assay for removing trichloroethylene in air. To accomplish that, its optical properties and resistance to photooxidation have been evaluated, and different operating conditions have been tested in order to optimize the fixation of the photocatalyst to obtain a homogeneous coating, with durable and high photocatalytic activity. The plastic materials tested were: polyethylene (PE), ethyl vinyl acetace copolymers with different additives (EVA, EVA-H and EVA -SH), polypropylene (PP), poly methyl (methacrylate) manufactured by sheet moulding and extrusion (PMMA-C and PMMA-E), compact and cellular polycarbonates (PC-C PC-Ce), rigid and flexible polyvinyl chloride (PVC-R and PVC-F), polystyrene (PS) and polyesters (PET and PETG). On the basis of their optical properties PP, PS, PMMA-C, EVA-SH and PVC-R were selected, as they showed a transmittance value greater than 80% in the range of the studied region (λ = 365nm). For the synthesis of the photocatalyst sol-gel technology was employed with multilayers impregnation of the polymers selected by dip-coating, with intermediate TiO2 drying at moderate temperatures. To evaluate the polymers aging due to UV radiation, and the effect of photoactive coating thereon, a study in an sunlight exposure chamber for 150 days was performed, evaluating the chemical resistance and the mechanical strength. The results of infrared spectroscopy and tensile stress test after aging showed the PMMA is the most resistant sample, but a greater degradation in PS, PVC-R and EVA SH, with a visible loss of the coating in all the polymers tested. The photocatalysts prepared on the untreated substrates with three layers of TiO2 showed better activity results when PMMA-C, PET and PS where used. To achieve greater and better fixation of the film to the support, chemical abrasive treatments, with H2SO4 and NaOH, as well as surface functionalization treatments with atmospheric pressure plasma (APP) and low pressure plasma (LPP) technologies were performed. The plasma treatment showed the best results, with an excellent wettability of the substrates that lead to a better and uniform distribution of the photocatalyst compared to the chemical treatments tested, in which no significant improvement was obtained. Also photocatalysts were prepared with the a silicon dioxide previous layer with the help of surfactants (SiO2- 3TiO2 PDDA-and-3TiO2 SiO2FC), obtaining good properties of the film in all cases. The best activity results for LPP-treated samples with three layers of TiO2 were achieved with PMMA-C (91% conversion, in conditions of 30 ppm of TCE and 200 ml·min-1 air flow rate), with a significant improvement of the photocatalytic activity in PVC-R and PS samples too. However, among all the materials assayed, PMMA-C with SiO2FC-3TiO2 coating was the most active one, achieving the highest mineralization grade (45%) and a reaction rate of 1,89 x 10-6 mol· m-2 · s-1, with total trichloroethylene elimination in the same conditions. As a comparative assay, an activity test was also performed with another typical organic contaminant, formaldehyde, also with good results (100% conversion with 24 ppm of HCHO and 200 ml·min-1 gas flow rate). The good activity results obtained in this study confirm the great potential of organic polymers which are transparent in the UV-A as supports for titanium dioxide for photocatalytic removal of air organic pollutants.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

An optimized QoS scheme for IMS-NEMO in heterogeneous networks

The network mobility (NEMO) is proposed to support the mobility management when users move as a whole. In IP Multimedia Subsystem (IMS), the individual Quality of Service (QoS) control for NEMO results in excessive signaling cost. On the other hand, current QoS schemes have two drawbacks: unawareness of the heterogeneous wireless environment and inefficient utilization of the reserved bandwidth. To solve these problems, we present a novel heterogeneous bandwidth sharing (HBS) scheme for QoS provision under IMS-based NEMO (IMS-NEMO). The HBS scheme selects the most suitable access network for each session and enables the new coming non-real-time sessions to share bandwidth with the Variable Bit Rate (VBR) coded media flows. The modeling and simulation results demonstrate that the HBS can satisfy users' QoS requirement and obtain a more efficient use of the scarce wireless bandwidth.

ARGoS: a modular, multi-engine simulator for heterogeneous swarm robotics

We present ARGoS, a novel open source multi-robot simulator. The main design focus of ARGoS is the real-time simulation of large heterogeneous swarms of robots. Existing robot simulators obtain scalability by imposing limitations on their extensibility and on the accuracy of the robot models. By contrast, in ARGoS we pursue a deeply modular approach that allows the user both to easily add custom features and to allocate computational resources where needed by the experiment. A unique feature of ARGoS is the possibility to use multiple physics engines of different types and to assign them to different parts of the environment. Robots can migrate from one engine to another transparently. This feature enables entirely novel classes of optimizations to improve scalability and paves the way for a new approach to parallelism in robotics simulation. Results show that ARGoS can simulate about 10,000 simple wheeled robots 40% faster than real-time.

Decentralized multi-tasks distribution in heterogeneous robot teams by means of ant colony optimization and learning automata

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-election of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested on decentralized solution where the robots themselves autonomously and in an individual manner, are responsible of selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-tasks distribution problem and we propose a solution using two different approaches by applying Ant Colony Optimization-based deterministic algorithms as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithm, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Application of self-organizing techniques for the distribution of heterogeneous multi-tasks in multi-robot systems

This paper focuses on the general problem of coordinating of multi-robot systems, more specifically, it addresses the self-election of heterogeneous and specialized tasks by autonomous robots. In this regard, it has proposed experimenting with two different techniques based chiefly on selforganization and emergence biologically inspired, by applying response threshold models as well as ant colony optimization. Under this approach it can speak of multi-tasks selection instead of multi-tasks allocation, that means, as the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. It has evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems.

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

An architecture for a heterogeneous private IaaS management system

Cloud computing and, more particularly, private IaaS, is seen as a mature technology with a myriad solutions tochoose from. However, this disparity of solutions and products has instilled in potential adopters the fear of vendor and data lock-in. Several competing and incompatible interfaces and management styles have given even more voice to these fears. On top of this, cloud users might want to work with several solutions at the same time, an integration that is difficult to achieve in practice. In this paper, we propose a management architecture that tries to tackle these problems; it offers a common way of managing several cloud solutions, and an interface that can be tailored to the needs of the user. This management architecture is designed in a modular way, and using a generic information model. We have validated our approach through the implementation of the components needed for this architecture to support a sample private IaaS solution: OpenStack

Replication Data Management,needs and solutions: an initial evaluation of conceptual approaches for integrating heterogeneous replication study data

Replication Data Management (RDM) aims at enabling the use of data collections from several iterations of an experiment. However, there are several major challenges to RDM from integrating data models and data from empirical study infrastructures that were not designed to cooperate, e.g., data model variation of local data sources. [Objective] In this paper we analyze RDM needs and evaluate conceptual RDM approaches to support replication researchers. [Method] We adapted the ATAM evaluation process to (a) analyze RDM use cases and needs of empirical replication study research groups and (b) compare three conceptual approaches to address these RDM needs: central data repositories with a fixed data model, heterogeneous local repositories, and an empirical ecosystem. [Results] While the central and local approaches have major issues that are hard to resolve in practice, the empirical ecosystem allows bridging current gaps in RDM from heterogeneous data sources. [Conclusions] The empirical ecosystem approach should be explored in diverse empirical environments.

Cattle-powered nodes experience in a heterogeneous network for localization of herds

A heterogeneous network, mainly based on nodes that use harvested energy to self-energize is presented and its use demonstrated. The network, mostly kinetically powered, has been used for the localization of herds in grazing areas under extreme climate conditions. The network consists of secondary and primary nodes. The former, powered by a kinetic generator, take advantage of animal movements to broadcast a unique identifier. The latter are battery-powered and gather secondarynode transmitted information to provide it, along with position and time data, to a final base station in charge of the animal monitoring. Because a limited human interaction is desirable, the aim of this network is to reduce the battery count of the system.