11 resultados para sistema embarcado

em Universidade Federal do Rio Grande do Norte(UFRN)


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Hypertension is a dangerous disease that can cause serious harm to a patient health. In some situations the necessity to control this pressure is even greater, as in surgical procedures and post-surgical patients. To decrease the chances of a complication, it is necessary to reduce blood pressure as soon as possible. Continuous infusion of vasodilators drugs, such as sodium nitroprusside (SNP), rapidly decreased blood pressure in most patients, avoiding major problems. Maintaining the desired blood pressure requires constant monitoring of arterial blood pressure and frequently adjusting the drug infusion rate. Manual control of arterial blood pressure by clinical personnel is very demanding, time consuming and, as a result, sometimes of poor quality. Thus, the aim of this work is the design and implementation of a database of tuned controllers based on patients models, in order to find a suitable PID to be embedded in a Programmable Integrated Circuit (PIC), which has a smaller cost, smaller size and lower power consumption. For best results in controlling the blood pressure and choosing the adequate controller, tuning algorithms, system identification techniques and Smith predictor are used. This work also introduces a monitoring system to assist in detecting anomalies and optimize the process of patient care.

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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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The number of applications based on embedded systems grows significantly every year, even with the fact that embedded systems have restrictions, and simple processing units, the performance of these has improved every day. However the complexity of applications also increase, a better performance will always be necessary. So even such advances, there are cases, which an embedded system with a single unit of processing is not sufficient to achieve the information processing in real time. To improve the performance of these systems, an implementation with parallel processing can be used in more complex applications that require high performance. The idea is to move beyond applications that already use embedded systems, exploring the use of a set of units processing working together to implement an intelligent algorithm. The number of existing works in the areas of parallel processing, systems intelligent and embedded systems is wide. However works that link these three areas to solve any problem are reduced. In this context, this work aimed to use tools available for FPGA architectures, to develop a platform with multiple processors to use in pattern classification with artificial neural networks

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Fuzzy intelligent systems are present in a variety of equipment ranging from household appliances to Fuzzy intelligent systems are present in a variety of equipment ranging from household appliances to small devices such as digital cameras and cell phones being used primarily for dealing with the uncertainties in the modeling of real systems. However, commercial implementations of Fuzzy systems are not general purpose and do not have portability to different hardware platforms. Thinking about these issues this work presents the implementation of an open source development environment that consists of a desktop system capable of generate Graphically a general purpose Fuzzy controller and export these parameters for an embedded system with a Fuzzy controller written in Java Platform Micro Edition To (J2ME), whose modular design makes it portable to any mobile device that supports J2ME. Thus, the proposed development platform is capable of generating all the parameters of a Fuzzy controller and export it in XML file, and the code responsible for the control logic that is embedded in the mobile device is able to read this file and start the controller. All the parameters of a Fuzzy controller are configurable using the desktop system, since the membership functions and rule base, even the universe of discourse of the linguistic terms of output variables. This system generates Fuzzy controllers for the interpolation model of Takagi-Sugeno. As the validation process and testing of the proposed solution the Fuzzy controller was embedded on the mobile device Sun SPOT ® and used to control a plant-level Quanser®, and to compare the Fuzzy controller generated by the system with other types of controllers was implemented and embedded in sun spot a PID controller to control the same level plant of Quanser®

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In practically all vertical markets and in every region of the planet, loyalty marketers have adopted the tactic of recognition and reward to identify, maintain and increase the yield of their customers. Several strategies have been adopted by companies, and the most popular among them is the loyalty program, which displays a loyalty club to manage these rewards. But the problem with loyalty programs is that customer identification and transfer of loyalty points are made in a semiautomatic. Aiming at this, this paper presents a master's embedded business automation solution called e-Points. The goal of e-Points is munir clubs allegiances with fully automated tooling technology to identify customers directly at the point of sales, ensuring greater control over the loyalty of associate members. For this, we developed a hardware platform with embedded system and RFID technology to be used in PCs tenant, a smart card to accumulate points with every purchase and a web server, which will provide services of interest to retailers and customers membership to the club

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Embedded systems are widely spread nowadays. An example is the Digital Signal Processor (DSP), which is a high processing power device. This work s contribution consist of exposing DSP implementation of the system logic for detecting leaks in real time. Among the various methods of leak detection available today this work uses a technique based on the pipe pressure analysis and usesWavelet Transform and Neural Networks. In this context, the DSP, in addition to do the pressure signal digital processing, also communicates to a Global Positioning System (GPS), which helps in situating the leak, and to a SCADA, sharing information. To ensure robustness and reliability in communication between DSP and SCADA the Modbus protocol is used. As it is a real time application, special attention is given to the response time of each of the tasks performed by the DSP. Tests and leak simulations were performed using the structure of Laboratory of Evaluation of Measurement in Oil (LAMP), at Federal University of Rio Grande do Norte (UFRN)

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This work presents the development of a prototype of an intelligent active orthosis for lower limbs whit an electronic embedded system. The proposed orthosis is an orthopedical device with the main objective of providing walking capacity to people with partial or total loss of lower limbs movements. In order to design the kinematics, dynamics and the mechanical characteristics of the prototype, the biomechanics of the human body was analized. The orthosis was projected to reproduce some of the movements of the human gait as walking in straight forward, sit down, get up, arise and go down steps. The joints of the orthosis are controlled by DC motors equipped with mechanical reductions, whose purpose is to reduce rotational speed and increase the torque, thus generating smooth movements. The electronic embedded system is composed of two motor controller boards with two channels that communicate with a embedded PC, position sensors and limit switches. The gait movements of the orthosis will be controlled by high level commands from a human-machine interface. The embedded electronic system interprets the high level commands, generates the angular references for the joints of the orthosis, controls and drives the actuators in order to execute the desired movements of the user

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We propose a mechatronic system for monitoring water quality in rivers, lakes, dams and sea, able to perform the acquisition, processing and presentation of data via the web in real time, in order to facilitate analysis quickly and needs by interested communities. The hardware architecture and software monitoring system has been developed so that it can be generic, that is, supporting different applications. Nevertheless, as a validation of the proposed system, we built a prototype that operates embarked on an autonomous robotic sailboat, a responsible platform for collecting the data in multiple predefined points from a ground station with a planning system navigation. This final application combines the advantages of autonomy of a robotic sailboat with the need for fast and accurate monitoring of water quality, in addition to the use of an autonomous robotic sailboat unmanned facilitate the development of other research in this area.

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This study developed software rotines, in a system made basically from a processor board producer of signs and supervisory, wich main function was correcting the information measured by a turbine gas meter. This correction is based on the use of an intelligent algorithm formed by an artificial neural net. The rotines were implemented in the habitat of the supervisory as well as in the habitat of the DSP and have three main itens: processing, communication and supervision

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Navigation based on visual feedback for robots, working in a closed environment, can be obtained settling a camera in each robot (local vision system). However, this solution requests a camera and capacity of local processing for each robot. When possible, a global vision system is a cheapest solution for this problem. In this case, one or a little amount of cameras, covering all the workspace, can be shared by the entire team of robots, saving the cost of a great amount of cameras and the associated processing hardware needed in a local vision system. This work presents the implementation and experimental results of a global vision system for mobile mini-robots, using robot soccer as test platform. The proposed vision system consists of a camera, a frame grabber and a computer (PC) for image processing. The PC is responsible for the team motion control, based on the visual feedback, sending commands to the robots through a radio link. In order for the system to be able to unequivocally recognize each robot, each one has a label on its top, consisting of two colored circles. Image processing algorithms were developed for the eficient computation, in real time, of all objects position (robot and ball) and orientation (robot). A great problem found was to label the color, in real time, of each colored point of the image, in time-varying illumination conditions. To overcome this problem, an automatic camera calibration, based on clustering K-means algorithm, was implemented. This method guarantees that similar pixels will be clustered around a unique color class. The obtained experimental results shown that the position and orientation of each robot can be obtained with a precision of few millimeters. The updating of the position and orientation was attained in real time, analyzing 30 frames per second

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This work shows a project method proposed to design and build software components from the software functional m del up to assembly code level in a rigorous fashion. This method is based on the B method, which was developed with support and interest of British Petroleum (BP). One goal of this methodology is to contribute to solve an important problem, known as The Verifying Compiler. Besides, this work describes a formal model of Z80 microcontroller and a real system of petroleum area. To achieve this goal, the formal model of Z80 was developed and documented, as it is one key component for the verification upto the assembly level. In order to improve the mentioned methodology, it was applied on a petroleum production test system, which is presented in this work. Part of this technique is performed manually. However, almost of these activities can be automated by a specific compiler. To build such compiler, the formal modelling of microcontroller and modelling of production test system should provide relevant knowledge and experiences to the design of a new compiler. In ummary, this work should improve the viability of one of the most stringent criteria for formal verification: speeding up the verification process, reducing design time and increasing the quality and reliability of the product of the final software. All these qualities are very important for systems that involve serious risks or in need of a high confidence, which is very common in the petroleum industry