830 resultados para Internet-of-Things, Wireless Sensor Network, CoAP
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In recent years, the network vulnerability to natural hazards has been noticed. Moreover, operating on the limits of the network transmission capabilities have resulted in major outages during the past decade. One of the reasons for operating on these limits is that the network has become outdated. Therefore, new technical solutions are studied that could provide more reliable and more energy efficient power distributionand also a better profitability for the network owner. It is the development and price of power electronics that have made the DC distribution an attractive alternative again. In this doctoral thesis, one type of a low-voltage DC distribution system is investigated. Morespecifically, it is studied which current technological solutions, used at the customer-end, could provide better power quality for the customer when compared with the current system. To study the effect of a DC network on the customer-end power quality, a bipolar DC network model is derived. The model can also be used to identify the supply parameters when the V/kW ratio is approximately known. Although the model provides knowledge of the average behavior, it is shown that the instantaneous DC voltage ripple should be limited. The guidelines to choose an appropriate capacitance value for the capacitor located at the input DC terminals of the customer-end are given. Also the structure of the customer-end is considered. A comparison between the most common solutions is made based on their cost, energy efficiency, and reliability. In the comparison, special attention is paid to the passive filtering solutions since the filter is considered a crucial element when the lifetime expenses are determined. It is found out that the filter topology most commonly used today, namely the LC filter, does not provide economical advantage over the hybrid filter structure. Finally, some of the typical control system solutions are introduced and their shortcomings are presented. As a solution to the customer-end voltage regulation problem, an observer-based control scheme is proposed. It is shown how different control system structures affect the performance. The performance meeting the requirements is achieved by using only one output measurement, when operating in a rigid network. Similar performance can be achieved in a weak grid by DC voltage measurement. An additional improvement can be achieved when an adaptive gain scheduling-based control is introduced. As a conclusion, the final power quality is determined by a sum of various factors, and the thesis provides the guidelines for designing the system that improves the power quality experienced by the customer.
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Today's networked systems are becoming increasingly complex and diverse. The current simulation and runtime verification techniques do not provide support for developing such systems efficiently; moreover, the reliability of the simulated/verified systems is not thoroughly ensured. To address these challenges, the use of formal techniques to reason about network system development is growing, while at the same time, the mathematical background necessary for using formal techniques is a barrier for network designers to efficiently employ them. Thus, these techniques are not vastly used for developing networked systems. The objective of this thesis is to propose formal approaches for the development of reliable networked systems, by taking efficiency into account. With respect to reliability, we propose the architectural development of correct-by-construction networked system models. With respect to efficiency, we propose reusable network architectures as well as network development. At the core of our development methodology, we employ the abstraction and refinement techniques for the development and analysis of networked systems. We evaluate our proposal by employing the proposed architectures to a pervasive class of dynamic networks, i.e., wireless sensor network architectures as well as to a pervasive class of static networks, i.e., network-on-chip architectures. The ultimate goal of our research is to put forward the idea of building libraries of pre-proved rules for the efficient modelling, development, and analysis of networked systems. We take into account both qualitative and quantitative analysis of networks via varied formal tool support, using a theorem prover the Rodin platform and a statistical model checker the SMC-Uppaal.
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In the 2000’s Finland suffered from storms that caused long outages in electricity distribution, longest up to two weeks. These major disturbances increased the importance of supply security. In 2013 new Electricity Market Act was announced. It defined maximum duration for outages, 6 h for city plan areas and 36 h for other areas. The aim for this work is to determine required major disturbance proof level for a study area and find tools for prioritizing overhead lines for cabling renovation to improve supply security. Three prioritization methods were chosen to be studied: A: prioritization line sections by customer outage costs they cause, B: maximizing customers major disturbance proof network and C: minimizing excavation costs in medium voltage network. Profitability calculations showed that prioritization method A was the most profitable and C had the weakest profitability. The prioritization method C drove renovation into unreasonable locations in the study area in reliability point of view. Therefore universal rule prioritization methods couldn’t be made from the prioritization methods. This led to the conclusion that every renewing area need to be evaluated in a case by case basis.
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Manufacturing industry has been always facing challenge to improve the production efficiency, product quality, innovation ability and struggling to adopt cost-effective manufacturing system. In recent years cloud computing is emerging as one of the major enablers for the manufacturing industry. Combining the emerged cloud computing and other advanced manufacturing technologies such as Internet of Things, service-oriented architecture (SOA), networked manufacturing (NM) and manufacturing grid (MGrid), with existing manufacturing models and enterprise information technologies, a new paradigm called cloud manufacturing is proposed by the recent literature. This study presents concepts and ideas of cloud computing and cloud manufacturing. The concept, architecture, core enabling technologies, and typical characteristics of cloud manufacturing are discussed, as well as the difference and relationship between cloud computing and cloud manufacturing. The research is based on mixed qualitative and quantitative methods, and a case study. The case is a prototype of cloud manufacturing solution, which is software platform cooperated by ATR Soft Oy and SW Company China office. This study tries to understand the practical impacts and challenges that are derived from cloud manufacturing. The main conclusion of this study is that cloud manufacturing is an approach to achieve the transformation from traditional production-oriented manufacturing to next generation service-oriented manufacturing. Many manufacturing enterprises are already using a form of cloud computing in their existing network infrastructure to increase flexibility of its supply chain, reduce resources consumption, the study finds out the shift from cloud computing to cloud manufacturing is feasible. Meanwhile, the study points out the related theory, methodology and application of cloud manufacturing system are far from maturity, it is still an open field where many new technologies need to be studied.
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This research is the continuation and a joint work with a master thesis that has been done in this department recently by Hemamali Chathurangani Yashika Jayathunga. The mathematical system of the equations in the designed Heat Exchanger Network synthesis has been extended by adding a number of equipment; such as heat exchangers, mixers and dividers. The solutions of the system is obtained and the optimal setting of the valves (Each divider contains a valve) is calculated by introducing grid-based optimization. Finding the best position of the valves will lead to maximization of the transferred heat in the hot stream and minimization of the pressure drop in the cold stream. The aim of the following thesis will be achieved by practicing the cost optimization to model an optimized network.
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Internet of Things or IoT is revolutionizing the world we are living in, similarly the way Internet and the web did few decades ago. It is changing how we interact with the things surrounding us. Electronic health and remote patient monitoring are the ways of utilizing these technological improvements towards the healthcare. There are many applications of IoT in eHealth such as, it will open the gate to provide healthcare to the remote areas of the world, where healthcare through traditional hospital systems cannot be provided. To connect these new eHealth IoT systems with the existing healthcare information systems, we can use the existing interoperability standards commonly used in healthcare information systems. In this thesis we implemented an eHealth IoT system based on Health Level 7 interoperability standard for continuous data transmission. There is not much previous work done in implementing the HL7 for continuous sensor data transmission. Some of the previous work was limited to sensors which are not continuous in nature and some of it is only theatrical architecture. This thesis aims to prove that it is possible to implement an eHealth IoT system by using sensors which require continues data transmission, such as respiratory sensors, and to connect it with the existing eHealth information system semantically by using HL7 interoperability standard. This system will be beneficial in implementing eHealth IoT systems for those patients, who requires continuous healthcare personal monitoring. This includes elderly people and patients, whose health need to be monitored constantly. To implement the architecture, HL7 v2.5 is selected due to its ease of implementation and low size. We selected some open source technologies because of their open licenses and large developer community. We will also review the most efficient technology available in every layer of eHealth IoT system and will propose an efficient system.
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Tunable Optical Sensor Arrays (TOSA) based on Fabry-Pérot (FP) filters, for high quality spectroscopic applications in the visible and near infrared spectral range are investigated within this work. The optical performance of the FP filters is improved by using ion beam sputtered niobium pentoxide (Nb2O5) and silicon dioxide (SiO2) Distributed Bragg Reflectors (DBRs) as mirrors. Due to their high refractive index contrast, only a few alternating pairs of Nb2O5 and SiO2 films can achieve DBRs with high reflectivity in a wide spectral range, while ion beam sputter deposition (IBSD) is utilized due to its ability to produce films with high optical purity. However, IBSD films are highly stressed; resulting in stress induced mirror curvature and suspension bending in the free standing filter suspensions of the MEMS (Micro-Electro-Mechanical Systems) FP filters. Stress induced mirror curvature results in filter transmission line degradation, while suspension bending results in high required filter tuning voltages. Moreover, stress induced suspension bending results in higher order mode filter operation which in turn degrades the optical resolution of the filter. Therefore, the deposition process is optimized to achieve both near zero absorption and low residual stress. High energy ion bombardment during film deposition is utilized to reduce the film density, and hence the film compressive stress. Utilizing this technique, the compressive stress of Nb2O5 is reduced by ~43%, while that for SiO2 is reduced by ~40%. Filters fabricated with stress reduced films show curvatures as low as 100 nm for 70 μm mirrors. To reduce the stress induced bending in the free standing filter suspensions, a stress optimized multi-layer suspension design is presented; with a tensile stressed metal sandwiched between two compressively stressed films. The stress in Physical Vapor Deposited (PVD) metals is therefore characterized for use as filter top-electrode and stress compensating layer. Surface micromachining is used to fabricate tunable FP filters in the visible spectral range using the above mentioned design. The upward bending of the suspensions is reduced from several micrometers to less than 100 nm and 250 nm for two different suspension layer combinations. Mechanical tuning of up to 188 nm is obtained by applying 40 V of actuation voltage. Alternatively, a filter line with transmission of 65.5%, Full Width at Half Maximum (FWHM) of 10.5 nm and a stopband of 170 nm (at an output wavelength of 594 nm) is achieved. Numerical model simulations are also performed to study the validity of the stress optimized suspension design for the near infrared spectral range, wherein membrane displacement and suspension deformation due to material residual stress is studied. Two bandpass filter designs based on quarter-wave and non-quarter-wave layers are presented as integral components of the TOSA. With a filter passband of 135 nm and a broad stopband of over 650 nm, high average filter transmission of 88% is achieved inside the passband, while maximum filter transmission of less than 1.6% outside the passband is achieved.
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Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a satellite-only method. All algorithms were validated against rain gauge data. Overall, the neural network performs best, but the extent to which it does so depends on the calibration/validation protocol. The advantages of the neural network are most evident when calibration data are numerous and close in space and time to the validation data. This result emphasizes the importance of a real-time calibration system.
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A wireless sensor network (WSN) is a group of sensors linked by wireless medium to perform distributed sensing tasks. WSNs have attracted a wide interest from academia and industry alike due to their diversity of applications, including home automation, smart environment, and emergency services, in various buildings. The primary goal of a WSN is to collect data sensed by sensors. These data are characteristic of being heavily noisy, exhibiting temporal and spatial correlation. In order to extract useful information from such data, as this paper will demonstrate, people need to utilise various techniques to analyse the data. Data mining is a process in which a wide spectrum of data analysis methods is used. It is applied in the paper to analyse data collected from WSNs monitoring an indoor environment in a building. A case study is given to demonstrate how data mining can be used to optimise the use of the office space in a building.
Research agenda in context-specific semantic resolution of security and QoS for ambient intelligence