937 resultados para sensor location problem
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We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.
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We construct a model in which a first mover decides on its location before it knows the identity of the second mover; joint location results in a negative extemality. Contracts are inherently incomplete since the first mover's initial decision cannot be specified. We analyze several kinds of rights, including damages, injunctions, and rights to exclude (arising from covenants or land ownership). There are cases in which allocating any of these basic rights to the first mover-i.e., first-party rights-is dominated by second-party rights, and cases in which the reverse is true. A Coasian result (efficiency regardless of the rights allocation) only holds under a limited set of conditions. As corollaries of a theorem ranking the basic rights regimes, a number of results emerge contradicting conventional wisdom, including the relative inefficiency of concentrated land ownership and the relevance of the generator's identity. We conclude with a mechanism and a new rights regime that each yield the first best in all cases.
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With the current proliferation of sensor equipped mobile devices such as smartphones and tablets, location aware services are expanding beyond the mere efficiency and work related needs of users, evolving in order to incorporate fun, culture and the social life of users. Today people on the move have more and more connectivity and are expected to be able to communicate with their usual and familiar social networks. That means communications not only with their peers and colleagues, friends and family but also with unknown people that might share their interests, curiosities or happen to use the same social network. Through social networks, location aware blogging, cultural mobile applications relevant information is now available at specific geographical locations and open to feedback and conversations among friends as well as strangers. In fact, nowadays smartphone technologies aloud users to post and retrieve content while on the move, often relating to specific physical landmarks or locations, engaging and being engaged in conversations with strangers as much as their own social network. The use of such technologies and applications while on the move can often lead people to serendipitous discoveries and interactions. Throughout our thesis we are engaging on a two folded investigation: how can we foster and support serendipitous discoveries and what are the best interfaces for it? In fact, to read and write content while on the move is a cognitively intensive task. While the map serves the function of orienting the user, it also absorbs most of the user’s concentration. In order to address this kind of cognitive overload issue with Breadcrumbs we propose a 360 degrees interface that enables the user to find content around them by means of scanning the surrounding space with the mobile device. By using a loose metaphor of a periscope, harnessing the power of the smartphone sensors we designed an interactive interface capable of detecting content around the users and display it in the form of 2 dimensional bubbles which diameter depends on their distance from the users. Users will navigate the space in relation to the content that they are curious about, rather than in relation to the traditional geographical map. Through this model we envisage alleviating a certain cognitive overload generated by having to continuously confront a two dimensional map with the real three dimensional space surrounding the user, but also use the content as a navigational filter. Furthermore this alternative mean of navigating space might bring serendipitous discovery about places that user where not aware of or intending to reach. We hence conclude our thesis with the evaluation of the Breadcrumbs application and the comparison of the 360 degrees interface with a traditional 2 dimensional map displayed on the devise screen. Results from the evaluation are compiled in findings and insights for future use in designing and developing context aware mobile applications.
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In Simultaneous Localization and Mapping (SLAM - Simultaneous Localization and Mapping), a robot placed in an unknown location in any environment must be able to create a perspective of this environment (a map) and is situated in the same simultaneously, using only information captured by the robot s sensors and control signals known. Recently, driven by the advance of computing power, work in this area have proposed to use video camera as a sensor and it came so Visual SLAM. This has several approaches and the vast majority of them work basically extracting features of the environment, calculating the necessary correspondence and through these estimate the required parameters. This work presented a monocular visual SLAM system that uses direct image registration to calculate the image reprojection error and optimization methods that minimize this error and thus obtain the parameters for the robot pose and map of the environment directly from the pixels of the images. Thus the steps of extracting and matching features are not needed, enabling our system works well in environments where traditional approaches have difficulty. Moreover, when addressing the problem of SLAM as proposed in this work we avoid a very common problem in traditional approaches, known as error propagation. Worrying about the high computational cost of this approach have been tested several types of optimization methods in order to find a good balance between good estimates and processing time. The results presented in this work show the success of this system in different environments
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Traditional irrigation projects do not locally determine the water availability in the soil. Then, irregular irrigation cycles may occur: some with insufficient amount that leads to water deficit, other with excessive watering that causes lack of oxygen in plants. Due to the nonlinear nature of this problem and the multivariable context of irrigation processes, fuzzy logic is suggested to replace commercial ON-OFF irrigation system with predefined timing. Other limitation of commercial solutions is that irrigation processes either consider the different watering needs throughout plant growth cycles or the climate changes. In order to fulfill location based agricultural needs, it is indicated to monitor environmental data using wireless sensors connected to an intelligent control system. This is more evident in applications as precision agriculture. This work presents the theoretical and experimental development of a fuzzy system to implement a spatially differentiated control of an irrigation system, based on soil moisture measurement with wireless sensor nodes. The control system architecture is modular: a fuzzy supervisor determines the soil moisture set point of each sensor node area (according to the soil-plant set) and another fuzzy system, embedded in the sensor node, does the local control and actuates in the irrigation system. The fuzzy control system was simulated with SIMULINK® programming tool and was experimentally built embedded in mobile device SunSPOTTM operating in ZigBee. Controller models were designed and evaluated in different combinations of input variables and inference rules base
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Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.
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Smart material technology has become an area of increasing interest for the development of lighter and stronger structures which are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains, is a very important issue. For that purpose, smart material modelling, modal analysis methods, control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first one is related to the discrete optimal actuator location selection problem which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Smart material technology has become an area of increasing interest for the development of lighter and stronger structures which are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains, is a very important issue. For that purpose, smart material modelling, modal analysis methods, control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first one is related to the discrete optimal actuator location selection problem, which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.
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This paper investigates both theoretically and experimentally the effect of the location and number of sensors and magnetic bearing actuators on both global and local vibration reduction along a rotor using a feedforward control scheme. Theoretical approaches developed for the active control of beams have been shown to be useful as simplified models for the rotor scenario. This paper also introduces the time-domain LMS feedforward control strategy, used widely in the active control of sound and vibration, as an alternative control methodology to the frequency-domain feedforward approaches commonly presented in the literature. Results are presented showing that for any case where the same number of actuators and error sensors are used there can be frequencies at which large increases in vibration away from the error sensors can occur. It is also shown that using a larger number of error sensors than actuators results in better global reduction of vibration but decreased local reduction. Overall, the study demonstrated that an analysis of actuator and sensor locations when feedforward control schemes are used is necessary to ensure that harmful increased vibrations do not occur at frequencies away from rotor-bearing natural frequencies or at points along the rotor not monitored by error sensors.
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In this work the problem of defects location in power systems is formulated through a binary linear programming (BLP) model based on alarms historical database of control and protection devices from the system control center, sets theory of minimal coverage (AI) and protection philosophy adopted by the electric utility. In this model, circuit breaker operations are compared to their expected states in a strictly mathematical manner. For solving this BLP problem, which presents a great number of decision variables, a dedicated Genetic Algorithm (GA), is proposed. Control parameters of the GA, such as crossing over and mutation rates, population size, iterations number and population diversification, are calibrated in order to obtain efficiency and robustness. Results for a test system found in literature, are presented and discussed. © 2004 IEEE.
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Phasor Measurement Units (PMUs) optimized allocation allows control, monitoring and accurate operation of electric power distribution systems, improving reliability and service quality. Good quality and considerable results are obtained for transmission systems using fault location techniques based on voltage measurements. Based on these techniques and performing PMUs optimized allocation it is possible to develop an electric power distribution system fault locator, which provides accurate results. The PMUs allocation problem presents combinatorial features related to devices number that can be allocated, and also probably places for allocation. Tabu search algorithm is the proposed technique to carry out PMUs allocation. This technique applied in a 141 buses real-life distribution urban feeder improved significantly the fault location results. © 2004 IEEE.
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In many production processes, a key material is prepared and then transformed into different final products. The lot sizing decisions concern not only the production of final products, but also that of material preparation in order to take account of their sequence-dependent setup costs and times. The amount of research in recent years indicates the relevance of this problem in various industrial settings. In this paper, facility location reformulation and strengthening constraints are newly applied to a previous lot-sizing model in order to improve solution quality and computing time. Three alternative metaheuristics are used to fix the setup variables, resulting in much improved performance over previous research, especially regarding the use of the metaheuristics for larger instances. © 2013 Elsevier Ltd. All rights reserved.
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In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two-agent relationship is modelled in a bilevel scheme. The upper-level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower-level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single-level mixed-integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. © The Institution of Engineering and Technology 2013.
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To determine the location of leaks in buried water pipes, acoustic methods are often used. These have proven to be very effective in metallic pipes but have been problematic in modern plastic pipes. In this paper the reason why this is so is discussed together with some measurements that were made on a bespoke test rig built by South Staffs Water plc. A particular problem is the estimate of the wavespeed. Tables are frequently used for this purpose, but these are often inaccurate and this means that a leak cannot be located accurately. An in-situ measure of the wavespeed is thus preferable. In this paper it is shown that there are significant issues in obtaining an accurate estimate of the wavespeed when a leak is present in the system. A method is proposed that overcomes some of these problems, which is discussed and is demonstrated using some data from the bespoke test-rig. © (2013) Trans Tech Publications.