基于WEB支持的市场客户管理系统的设计

本文阐述了采用Ｉｎｔｅｒｎｅｔ／Ｉｎｔｒａｎｅｔ技术和利用ＡＳＰ实现数据的动态发布技术以及基于分布网络环境下的异地设计与制造技术，设计了基于ｗｅｂ的支持机器人异地设计制造的市场客户管理系统，从而探讨了Ｂｒｏｗｓｅｒ／Ｓｅｒｖｅｒ结构的数据库发布系统的设计方法。

On the Complexity of Universal Leader Election

Electing a leader is a fundamental task in distributed computing. In its implicit version, only the leader must know who is the elected leader. This paper focuses on studying the message and time complexity of randomized implicit leader election in synchronous distributed networks. Surprisingly, the most "obvious" complexity bounds have not been proven for randomized algorithms. The "obvious" lower bounds of O(m) messages (m is the number of edges in the network) and O(D) time (D is the network diameter) are non-trivial to show for randomized (Monte Carlo) algorithms. (Recent results that show that even O(n) (n is the number of nodes in the network) is not a lower bound on the messages in complete networks, make the above bounds somewhat less obvious). To the best of our knowledge, these basic lower bounds have not been established even for deterministic algorithms (except for the limited case of comparison algorithms, where it was also required that some nodes may not wake up spontaneously, and that D and n were not known).

We establish these fundamental lower bounds in this paper for the general case, even for randomized Monte Carlo algorithms. Our lower bounds are universal in the sense that they hold for all universal algorithms (such algorithms should work for all graphs), apply to every D, m, and n, and hold even if D, m, and n are known, all the nodes wake up simultaneously, and the algorithms can make anyuse of node's identities. To show that these bounds are tight, we present an O(m) messages algorithm. An O(D) time algorithm is known. A slight adaptation of our lower bound technique gives rise to an O(m) message lower bound for randomized broadcast algorithms.

An interesting fundamental problem is whether both upper bounds (messages and time) can be reached simultaneously in the randomized setting for all graphs. (The answer is known to be negative in the deterministic setting). We answer this problem partially by presenting a randomized algorithm that matches both complexities in some cases. This already separates (for some cases) randomized algorithms from deterministic ones. As first steps towards the general case, we present several universal leader election algorithms with bounds that trade-off messages versus time. We view our results as a step towards understanding the complexity of universal leader election in distributed networks.

Sublinear Bounds for Randomized Leader Election

This paper concerns randomized leader election in synchronous distributed networks. A distributed leader election algorithm is presented for complete n-node networks that runs in O(1) rounds and (with high probability) takes only O(n-vlog3/2n) messages to elect a unique leader (with high probability). This algorithm is then extended to solve leader election on any connected non-bipartiten-node graph G in O(t(G)) time and O(t(G)n-vlog3/2n) messages, where t(G) is the mixing time of a random walk on G. The above result implies highly efficient (sublinear running time and messages) leader election algorithms for networks with small mixing times, such as expanders and hypercubes. In contrast, previous leader election algorithms had at least linear message complexity even in complete graphs. Moreover, super-linear message lower bounds are known for time-efficientdeterministic leader election algorithms. Finally, an almost-tight lower bound is presented for randomized leader election, showing that O(n-v) messages are needed for any O(1) time leader election algorithm which succeeds with high probability. It is also shown that O(n 1/3) messages are needed by any leader election algorithm that succeeds with high probability, regardless of the number of the rounds. We view our results as a step towards understanding the randomized complexity of leader election in distributed networks.

Edge-preserving self-healing: Keeping network backbones densely connected

Healing algorithms play a crucial part in distributed peer-to-peer networks where failures occur continuously and frequently. Whereas there are approaches for robustness that rely largely on built-in redundancy, we adopt a responsive approach that is more akin to that of biological networks e.g. the brain. The general goal of self-healing distributed graphs is to maintain certain network properties while recovering from failure quickly and making bounded alterations locally. Several self-healing algorithms have been suggested in the recent literature [IPDPS'08, PODC'08, PODC'09, PODC'11]; they heal various network properties while fulfilling competing requirements such as having low degree increase while maintaining connectivity, expansion and low stretch of the network. In this work, we augment the previous algorithms by adding the notion of edge-preserving self-healing which requires the healing algorithm to not delete any edges originally present or adversarialy inserted. This reflects the cost of adding additional edges but more importantly it immediately follows that edge preservation helps maintain any subgraph induced property that is monotonic, in particular important properties such as graph and subgraph densities. Density is an important network property and in certain distributed networks, maintaining it preserves high connectivity among certain subgraphs and backbones. We introduce a general model of self-healing, and introduce xheal+, an edge-preserving version of xheal[PODC'11]. © 2012 IEEE.

Sublinear bounds for randomized leader election

This paper concerns randomized leader election in synchronous distributed networks. A distributed leader election algorithm is presented for complete n-node networks that runs in O(1) rounds and (with high probability) uses only O(√ √nlog^3/2n) messages to elect a unique leader (with high probability). When considering the "explicit" variant of leader election where eventually every node knows the identity of the leader, our algorithm yields the asymptotically optimal bounds of O(1) rounds and O(. n) messages. This algorithm is then extended to one solving leader election on any connected non-bipartite n-node graph G in O(τ(. G)) time and O(τ(G)n√log^3/2n) messages, where τ(. G) is the mixing time of a random walk on G. The above result implies highly efficient (sublinear running time and messages) leader election algorithms for networks with small mixing times, such as expanders and hypercubes. In contrast, previous leader election algorithms had at least linear message complexity even in complete graphs. Moreover, super-linear message lower bounds are known for time-efficient deterministic leader election algorithms. Finally, we present an almost matching lower bound for randomized leader election, showing that Ω(n) messages are needed for any leader election algorithm that succeeds with probability at least 1/. e+. ε, for any small constant ε. >. 0. We view our results as a step towards understanding the randomized complexity of leader election in distributed networks.

On the Complexity of Universal Leader Election

Electing a leader is a fundamental task in distributed computing. In its implicit version, only the leader must know who is the elected leader. This article focuses on studying the message and time complexity of randomized implicit leader election in synchronous distributed networks. Surprisingly, the most "obvious" complexity bounds have not been proven for randomized algorithms. In particular, the seemingly obvious lower bounds of Ω(m) messages, where m is the number of edges in the network, and Ω(D) time, where D is the network diameter, are nontrivial to show for randomized (Monte Carlo) algorithms. (Recent results, showing that even Ω(n), where n is the number of nodes in the network, is not a lower bound on the messages in complete networks, make the above bounds somewhat less obvious). To the best of our knowledge, these basic lower bounds have not been established even for deterministic algorithms, except for the restricted case of comparison algorithms, where it was also required that nodes may not wake up spontaneously and that D and n were not known. We establish these fundamental lower bounds in this article for the general case, even for randomized Monte Carlo algorithms. Our lower bounds are universal in the sense that they hold for all universal algorithms (namely, algorithms that work for all graphs), apply to every D, m, and n, and hold even if D, m, and n are known, all the nodes wake up simultaneously, and the algorithms can make any use of node's identities. To show that these bounds are tight, we present an O(m) messages algorithm. An O(D) time leader election algorithm is known. A slight adaptation of our lower bound technique gives rise to an Ω(m) message lower bound for randomized broadcast algorithms. 

An interesting fundamental problem is whether both upper bounds (messages and time) can be reached simultaneously in the randomized setting for all graphs. The answer is known to be negative in the deterministic setting. We answer this problem partially by presenting a randomized algorithm that matches both complexities in some cases. This already separates (for some cases) randomized algorithms from deterministic ones. As first steps towards the general case, we present several universal leader election algorithms with bounds that tradeoff messages versus time. We view our results as a step towards understanding the complexity of universal leader election in distributed networks.

Dynamic Network Mechanisms of Relational Integration

A prominent hypothesis states that specialized neural modules within the human lateral frontopolar cortices (LFPCs) support “relational integration” (RI), the solving of complex problems using inter-related rules. However, it has been proposed that LFPC activity during RI could reflect the recruitment of additional “domain-general” resources when processing more difficult problems in general as opposed to RI specifi- cally. Moreover, theoretical research with computational models has demonstrated that RI may be supported by dynamic processes that occur throughout distributed networks of brain regions as opposed to within a discrete computational module. Here, we present fMRI findings from a novel deductive reasoning paradigm that controls for general difficulty while manipulating RI demands. In accordance with the domain- general perspective, we observe an increase in frontoparietal activation during challenging problems in general as opposed to RI specifically. Nonetheless, when examining frontoparietal activity using analyses of phase synchrony and psychophysiological interactions, we observe increased network connectivity during RI alone. Moreover, dynamic causal modeling with Bayesian model selection identifies the LFPC as the effective connectivity source. Based on these results, we propose that during RI an increase in network connectivity and a decrease in network metastability allows rules that are coded throughout working memory systems to be dynamically bound. This change in connectivity state is top-down propagated via a hierarchical system of domain-general networks with the LFPC at the apex. In this manner, the functional network perspective reconciles key propositions of the globalist, modular, and computational accounts of RI within a single unified framework.

Controlo preditivo distribuído para conforto térmico em edifícios

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

A mesoscopic modelling approach to anaesthetic action on brain electrical activity

Relating the measurable, large scale, effects of anaesthetic agents to their molecular and cellular targets of action is necessary to better understand the principles by which they affect behavior, as well as enabling the design and evaluation of more effective agents and the better clinical monitoring of existing and future drugs. Volatile and intravenous general anaesthetic agents (GAs) are now known to exert their effects on a variety of protein targets, the most important of which seem to be the neuronal ion channels. It is hence unlikely that anaesthetic effect is the result of a unitary mechanism at the single cell level. However, by altering the behavior of ion channels GAs are believed to change the overall dynamics of distributed networks of neurons. This disruption of regular network activity can be hypothesized to cause the hypnotic and analgesic effects of GAs and may well present more stereotypical characteristics than its underlying microscopic causes. Nevertheless, there have been surprisingly few theories that have attempted to integrate, in a quantitative manner, the empirically well documented alterations in neuronal ion channel behavior with the corresponding macroscopic effects. Here we outline one such approach, and show that a range of well documented effects of anaesthetics on the electroencephalogram (EEG) may be putatively accounted for. In particular we parameterize, on the basis of detailed empirical data, the effects of halogenated volatile ethers (a clinically widely used class of general anaesthetic agent). The resulting model is able to provisionally account for a range of anaesthetically induced EEG phenomena that include EEG slowing, biphasic changes in EEG power, and the dose dependent appearance of anomalous ictal activity, as well as providing a basis for novel approaches to monitoring brain function in both health and disease.

Editorial : advances in network and system security

Current parallel and distributed networks/systems are facing serious threats from network terrorism and crime, which cause huge financial loss and potential life hazard. As attacking tools are becoming more widely available, more easy-to-use, more sophisticated, and more powerful, more efforts have been made in building more effective, more intelligent, and more adaptive defense systems which are of distributed and networked nature. This special issue focuses on issues related to Network and System Security, such as authentication, access control, availability, integrity, privacy, confidentiality, dependability and sustainability of computer networks and systems.

Contributions to the Resilience Management in the Internet of Things

El auge del "Internet de las Cosas" (IoT, "Internet of Things") y sus tecnologías asociadas han permitido su aplicación en diversos dominios de la aplicación, entre los que se encuentran la monitorización de ecosistemas forestales, la gestión de catástrofes y emergencias, la domótica, la automatización industrial, los servicios para ciudades inteligentes, la eficiencia energética de edificios, la detección de intrusos, la gestión de desastres y emergencias o la monitorización de señales corporales, entre muchas otras. La desventaja de una red IoT es que una vez desplegada, ésta queda desatendida, es decir queda sujeta, entre otras cosas, a condiciones climáticas cambiantes y expuestas a catástrofes naturales, fallos de software o hardware, o ataques maliciosos de terceros, por lo que se puede considerar que dichas redes son propensas a fallos. El principal requisito de los nodos constituyentes de una red IoT es que estos deben ser capaces de seguir funcionando a pesar de sufrir errores en el propio sistema. La capacidad de la red para recuperarse ante fallos internos y externos inesperados es lo que se conoce actualmente como "Resiliencia" de la red. Por tanto, a la hora de diseñar y desplegar aplicaciones o servicios para IoT, se espera que la red sea tolerante a fallos, que sea auto-configurable, auto-adaptable, auto-optimizable con respecto a nuevas condiciones que puedan aparecer durante su ejecución. Esto lleva al análisis de un problema fundamental en el estudio de las redes IoT, el problema de la "Conectividad". Se dice que una red está conectada si todo par de nodos en la red son capaces de encontrar al menos un camino de comunicación entre ambos. Sin embargo, la red puede desconectarse debido a varias razones, como que se agote la batería, que un nodo sea destruido, etc. Por tanto, se hace necesario gestionar la resiliencia de la red con el objeto de mantener la conectividad entre sus nodos, de tal manera que cada nodo IoT sea capaz de proveer servicios continuos, a otros nodos, a otras redes o, a otros servicios y aplicaciones. En este contexto, el objetivo principal de esta tesis doctoral se centra en el estudio del problema de conectividad IoT, más concretamente en el desarrollo de modelos para el análisis y gestión de la Resiliencia, llevado a la práctica a través de las redes WSN, con el fin de mejorar la capacidad la tolerancia a fallos de los nodos que componen la red. Este reto se aborda teniendo en cuenta dos enfoques distintos, por una parte, a diferencia de otro tipo de redes de dispositivos convencionales, los nodos en una red IoT son propensos a perder la conexión, debido a que se despliegan en entornos aislados, o en entornos con condiciones extremas; por otra parte, los nodos suelen ser recursos con bajas capacidades en términos de procesamiento, almacenamiento y batería, entre otros, por lo que requiere que el diseño de la gestión de su resiliencia sea ligero, distribuido y energéticamente eficiente. En este sentido, esta tesis desarrolla técnicas auto-adaptativas que permiten a una red IoT, desde la perspectiva del control de su topología, ser resiliente ante fallos en sus nodos. Para ello, se utilizan técnicas basadas en lógica difusa y técnicas de control proporcional, integral y derivativa (PID - "proportional-integral-derivative"), con el objeto de mejorar la conectividad de la red, teniendo en cuenta que el consumo de energía debe preservarse tanto como sea posible. De igual manera, se ha tenido en cuenta que el algoritmo de control debe ser distribuido debido a que, en general, los enfoques centralizados no suelen ser factibles a despliegues a gran escala. El presente trabajo de tesis implica varios retos que conciernen a la conectividad de red, entre los que se incluyen: la creación y el análisis de modelos matemáticos que describan la red, una propuesta de sistema de control auto-adaptativo en respuesta a fallos en los nodos, la optimización de los parámetros del sistema de control, la validación mediante una implementación siguiendo un enfoque de ingeniería del software y finalmente la evaluación en una aplicación real. Atendiendo a los retos anteriormente mencionados, el presente trabajo justifica, mediante una análisis matemático, la relación existente entre el "grado de un nodo" (definido como el número de nodos en la vecindad del nodo en cuestión) y la conectividad de la red, y prueba la eficacia de varios tipos de controladores que permiten ajustar la potencia de trasmisión de los nodos de red en respuesta a eventuales fallos, teniendo en cuenta el consumo de energía como parte de los objetivos de control. Así mismo, este trabajo realiza una evaluación y comparación con otros algoritmos representativos; en donde se demuestra que el enfoque desarrollado es más tolerante a fallos aleatorios en los nodos de la red, así como en su eficiencia energética. Adicionalmente, el uso de algoritmos bioinspirados ha permitido la optimización de los parámetros de control de redes dinámicas de gran tamaño. Con respecto a la implementación en un sistema real, se han integrado las propuestas de esta tesis en un modelo de programación OSGi ("Open Services Gateway Initiative") con el objeto de crear un middleware auto-adaptativo que mejore la gestión de la resiliencia, especialmente la reconfiguración en tiempo de ejecución de componentes software cuando se ha producido un fallo. Como conclusión, los resultados de esta tesis doctoral contribuyen a la investigación teórica y, a la aplicación práctica del control resiliente de la topología en redes distribuidas de gran tamaño. Los diseños y algoritmos presentados pueden ser vistos como una prueba novedosa de algunas técnicas para la próxima era de IoT. A continuación, se enuncian de forma resumida las principales contribuciones de esta tesis: (1) Se han analizado matemáticamente propiedades relacionadas con la conectividad de la red. Se estudia, por ejemplo, cómo varía la probabilidad de conexión de la red al modificar el alcance de comunicación de los nodos, así como cuál es el mínimo número de nodos que hay que añadir al sistema desconectado para su re-conexión. (2) Se han propuesto sistemas de control basados en lógica difusa para alcanzar el grado de los nodos deseado, manteniendo la conectividad completa de la red. Se han evaluado diferentes tipos de controladores basados en lógica difusa mediante simulaciones, y los resultados se han comparado con otros algoritmos representativos. (3) Se ha investigado más a fondo, dando un enfoque más simple y aplicable, el sistema de control de doble bucle, y sus parámetros de control se han optimizado empleando algoritmos heurísticos como el método de la entropía cruzada (CE, "Cross Entropy"), la optimización por enjambre de partículas (PSO, "Particle Swarm Optimization"), y la evolución diferencial (DE, "Differential Evolution"). (4) Se han evaluado mediante simulación, la mayoría de los diseños aquí presentados; además, parte de los trabajos se han implementado y validado en una aplicación real combinando técnicas de software auto-adaptativo, como por ejemplo las de una arquitectura orientada a servicios (SOA, "Service-Oriented Architecture"). ABSTRACT The advent of the Internet of Things (IoT) enables a tremendous number of applications, such as forest monitoring, disaster management, home automation, factory automation, smart city, etc. However, various kinds of unexpected disturbances may cause node failure in the IoT, for example battery depletion, software/hardware malfunction issues and malicious attacks. So, it can be considered that the IoT is prone to failure. The ability of the network to recover from unexpected internal and external failures is known as "resilience" of the network. Resilience usually serves as an important non-functional requirement when designing IoT, which can further be broken down into "self-*" properties, such as self-adaptive, self-healing, self-configuring, self-optimization, etc. One of the consequences that node failure brings to the IoT is that some nodes may be disconnected from others, such that they are not capable of providing continuous services for other nodes, networks, and applications. In this sense, the main objective of this dissertation focuses on the IoT connectivity problem. A network is regarded as connected if any pair of different nodes can communicate with each other either directly or via a limited number of intermediate nodes. More specifically, this thesis focuses on the development of models for analysis and management of resilience, implemented through the Wireless Sensor Networks (WSNs), which is a challenging task. On the one hand, unlike other conventional network devices, nodes in the IoT are more likely to be disconnected from each other due to their deployment in a hostile or isolated environment. On the other hand, nodes are resource-constrained in terms of limited processing capability, storage and battery capacity, which requires that the design of the resilience management for IoT has to be lightweight, distributed and energy-efficient. In this context, the thesis presents self-adaptive techniques for IoT, with the aim of making the IoT resilient against node failures from the network topology control point of view. The fuzzy-logic and proportional-integral-derivative (PID) control techniques are leveraged to improve the network connectivity of the IoT in response to node failures, meanwhile taking into consideration that energy consumption must be preserved as much as possible. The control algorithm itself is designed to be distributed, because the centralized approaches are usually not feasible in large scale IoT deployments. The thesis involves various aspects concerning network connectivity, including: creation and analysis of mathematical models describing the network, proposing self-adaptive control systems in response to node failures, control system parameter optimization, implementation using the software engineering approach, and evaluation in a real application. This thesis also justifies the relations between the "node degree" (the number of neighbor(s) of a node) and network connectivity through mathematic analysis, and proves the effectiveness of various types of controllers that can adjust power transmission of the IoT nodes in response to node failures. The controllers also take into consideration the energy consumption as part of the control goals. The evaluation is performed and comparison is made with other representative algorithms. The simulation results show that the proposals in this thesis can tolerate more random node failures and save more energy when compared with those representative algorithms. Additionally, the simulations demonstrate that the use of the bio-inspired algorithms allows optimizing the parameters of the controller. With respect to the implementation in a real system, the programming model called OSGi (Open Service Gateway Initiative) is integrated with the proposals in order to create a self-adaptive middleware, especially reconfiguring the software components at runtime when failures occur. The outcomes of this thesis contribute to theoretic research and practical applications of resilient topology control for large and distributed networks. The presented controller designs and optimization algorithms can be viewed as novel trials of the control and optimization techniques for the coming era of the IoT. The contributions of this thesis can be summarized as follows: (1) Mathematically, the fault-tolerant probability of a large-scale stochastic network is analyzed. It is studied how the probability of network connectivity depends on the communication range of the nodes, and what is the minimum number of neighbors to be added for network re-connection. (2) A fuzzy-logic control system is proposed, which obtains the desired node degree and in turn maintains the network connectivity when it is subject to node failures. There are different types of fuzzy-logic controllers evaluated by simulations, and the results demonstrate the improvement of fault-tolerant capability as compared to some other representative algorithms. (3) A simpler but more applicable approach, the two-loop control system is further investigated, and its control parameters are optimized by using some heuristic algorithms such as Cross Entropy (CE), Particle Swarm Optimization (PSO), and Differential Evolution (DE). (4) Most of the designs are evaluated by means of simulations, but part of the proposals are implemented and tested in a real-world application by combining the self-adaptive software technique and the control algorithms which are presented in this thesis.

Supervisión multidistribuida para el control de procesos de conservación de productos agroalimentarios: optimización de calidad del producto

La presente Tesis está orientada al análisis de la supervisión multidistribuida de tres procesos agroalimentarios: el secado solar, el transporte refrigerado y la fermentación de café, a través de la información obtenida de diferentes dispositivos de adquisición de datos, que incorporan sensores, así como el desarrollo de metodologías de análisis de series temporales, modelos y herramientas de control de procesos para la ayuda a la toma de decisiones en las operaciones de estos entornos. En esta tesis se han utilizado: tarjetas RFID (TemTrip®) con sistema de comunicación por radiofrecuencia y sensor de temperatura; el registrador (i-Button®), con sensor integrado de temperatura y humedad relativa y un tercer prototipo empresarial, módulo de comunicación inalámbrico Nlaza, que integra un sensor de temperatura y humedad relativa Sensirion®. Estos dispositivos se han empleado en la conformación de redes multidistribuidas de sensores para la supervisión de: A) Transportes de producto hortofrutícola realizados en condiciones comerciales reales, que son: dos transportes terrestre de producto de IV gama desde Murcia a Madrid; transporte multimodal (barco-barco) de limones desde Montevideo (Uruguay) a Cartagena (España) y transporte multimodal (barco-camión) desde Montevideo (Uruguay) a Verona (Italia). B) dos fermentaciones de café realizadas en Popayán (Colombia) en un beneficiadero. Estas redes han permitido registrar la dinámica espacio-temporal de temperaturas y humedad relativa de los procesos estudiados. En estos procesos de transporte refrigerado y fermentación la aplicación de herramientas de visualización de datos y análisis de conglomerados, han permitido identificar grupos de sensores que presentan patrones análogos de sus series temporales, caracterizando así zonas con dinámicas similares y significativamente diferentes del resto y permitiendo definir redes de sensores de menor densidad cubriendo las diferentes zonas identificadas. Las metodologías de análisis complejo de las series espacio-temporales (modelos psicrométricos, espacio de fases bidimensional e interpolaciones espaciales) permitieron la cuantificación de la variabilidad del proceso supervisado tanto desde el punto de vista dinámico como espacial así como la identificación de eventos. Constituyendo así herramientas adicionales de ayuda a la toma de decisiones en el control de los procesos. Siendo especialmente novedosa la aplicación de la representación bidimensional de los espacios de fases en el estudio de las series espacio-temporales de variables ambientales en aplicaciones agroalimentarias, aproximación que no se había realizado hasta el momento. En esta tesis también se ha querido mostrar el potencial de un sistema de control basado en el conocimiento experto como es el sistema de lógica difusa. Se han desarrollado en primer lugar, los modelos de estimación del contenido en humedad y las reglas semánticas que dirigen el proceso de control, el mejor modelo se ha seleccionado mediante un ensayo de secado realizado sobre bolas de hidrogel como modelo alimentario y finalmente el modelo se ha validado mediante un ensayo en el que se deshidrataban láminas de zanahoria. Los resultados sugirieron que el sistema de control desarrollado, es capaz de hacer frente a dificultades como las variaciones de temperatura día y noche, consiguiendo un producto con buenas características de calidad comparables a las conseguidas sin aplicar ningún control sobre la operación y disminuyendo así el consumo energético en un 98% con respecto al mismo proceso sin control. La instrumentación y las metodologías de análisis de datos implementadas en esta Tesis se han mostrado suficientemente versátiles y transversales para ser aplicadas a diversos procesos agroalimentarios en los que la temperatura y la humedad relativa sean criterios de control en dichos procesos, teniendo una aplicabilidad directa en el sector industrial ABSTRACT This thesis is focused on the analysis of multi-distributed supervision of three agri-food processes: solar drying, refrigerated transport and coffee fermentation, through the information obtained from different data acquisition devices with incorporated sensors, as well as the development of methodologies for analyzing temporary series, models and tools to control processes in order to help in the decision making in the operations within these environments. For this thesis the following has been used: RFID tags (TemTrip®) with a Radiofrequency ID communication system and a temperature sensor; the recorder (i-Button®), with an integrated temperature and relative humidity and a third corporate prototype, a wireless communication module Nlaza, which has an integrated temperature and relative humidity sensor, Sensirion®. These devices have been used in creating three multi-distributed networks of sensors for monitoring: A) Transport of fruits and vegetables made in real commercial conditions, which are: two land trips of IV range products from Murcia to Madrid; multimodal transport (ship - ship) of lemons from Montevideo (Uruguay) to Cartagena (Spain) and multimodal transport (ship - truck) from Montevideo (Uruguay) to Verona (Italy). B) Two coffee fermentations made in Popayan (Colombia) in a coffee processing plant. These networks have allowed recording the time space dynamics of temperatures and relative humidity of the processed under study. Within these refrigerated transport and fermentation processes, the application of data display and cluster analysis tools have allowed identifying sensor groups showing analogical patterns of their temporary series; thus, featuring areas with similar and significantly different dynamics from the others and enabling the definition of lower density sensor networks covering the different identified areas. The complex analysis methodologies of the time space series (psychrometric models, bi-dimensional phase space and spatial interpolation) allowed quantifying the process variability of the supervised process both from the dynamic and spatial points of view; as well as the identification of events. Thus, building additional tools to aid decision-making on process control brought the innovative application of the bi-dimensional representation of phase spaces in the study of time-space series of environmental variables in agri-food applications, an approach that had not been taken before. This thesis also wanted to show the potential of a control system based on specialized knowledge such as the fuzzy logic system. Firstly, moisture content estimation models and semantic rules directing the control process have been developed, the best model has been selected by an drying assay performed on hydrogel beads as food model; and finally the model has been validated through an assay in which carrot sheets were dehydrated. The results suggested that the control system developed is able to cope with difficulties such as changes in temperature daytime and nighttime, getting a product with good quality features comparable to those features achieved without applying any control over the operation and thus decreasing consumption energy by 98% compared to the same uncontrolled process. Instrumentation and data analysis methodologies implemented in this thesis have proved sufficiently versatile and cross-cutting to apply to several agri-food processes in which the temperature and relative humidity are the control criteria in those processes, having a direct effect on the industry sector.

Structural Health Monitoring using Index Based Reasoning for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^

A distributed protocol for object tracking in wireless multimedia sensor networks

We consider the problem of object tracking in a wireless multimedia sensor network (we mainly focus on the camera component in this work). The vast majority of current object tracking techniques, either centralised or distributed, assume unlimited energy, meaning these techniques don't translate well when applied within the constraints of low-power distributed systems. In this paper we develop and analyse a highly-scalable, distributed strategy to object tracking in wireless camera networks with limited resources. In the proposed system, cameras transmit descriptions of objects to a subset of neighbours, determined using a predictive forwarding strategy. The received descriptions are then matched at the next camera on the objects path using a probability maximisation process with locally generated descriptions. We show, via simulation, that our predictive forwarding and probabilistic matching strategy can significantly reduce the number of object-misses, ID-switches and ID-losses; it can also reduce the number of required transmissions over a simple broadcast scenario by up to 67%. We show that our system performs well under realistic assumptions about matching objects appearance using colour.

Distributed object tracking with robot and disjoint camera networks

We describe a novel two stage approach to object localization and tracking using a network of wireless cameras and a mobile robot. In the first stage, a robot travels through the camera network while updating its position in a global coordinate frame which it broadcasts to the cameras. The cameras use this information, along with image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to track the objects. We present results with a nine node indoor camera network to demonstrate that this approach is feasible and offers acceptable level of accuracy in terms of object locations.