31 resultados para Intelligent automation
Resumo:
Intelligent environments aim at supporting the user in executing her everyday tasks, e.g. by guiding her through a maintenance or cooking procedure. This requires a machine processable representation of the tasks for which workflows have proven an efficient means. The increasing number of available sensors in intelligent environments can facilitate the execution of workflows. The sensors can help to recognize when a user has finished a step in the workflow and thus to automatically proceed to the next step. This can heavily reduce the amount of required user interaction. However, manually specifying the conditions for triggering the next step in a workflow is very cumbersome and almost impossible for environments which are not known at design time. In this paper, we present a novel approach for learning and adapting these conditions from observation. We show that the learned conditions can even outperform the quality as conditions manually specified by workflow experts. Thus, the presented approach is very well suited for automatically adapting workflows in intelligent environments and can in that way increase the efficiency of the workflow execution. © 2011 IEEE.
Resumo:
Hospitals everywhere are integrating health data using electronic health record (EHR) systems, and disparate and multimedia patient data can be input by different caregivers at different locations as encapsulated patient profiles. Healthcare institutions are also using the flexibility and speed of wireless computing to improve quality and reduce costs. We are developing a mobile application that allows doctors to efficiently record and access complete and accurate real-time patient information. The system integrates medical imagery with textual patient profiles as well as expert interactions by healthcare personnel using knowledge management and case-based reasoning techniques. The application can assist other caregivers in searching large repositories of previous patient cases. Patients' symptoms can be input to a portable device and the application can quickly retrieve similar profiles which can be used to support effective diagnoses and prognoses by comparing symptoms, treatments, diagnosis, test results and other patient information. © 2007 Sage Publications.
Resumo:
In-Motes is a mobile agent middleware that generates an intelligent framework for deploying applications in Wireless Sensor Networks (WSNs). In-Motes is based on the injection of mobile agents into the network that can migrate or clone following specific rules and performing application specific tasks. By doing so, each mote is given a certain degree of perception, cognition and control, forming the basis for its intelligence. Our middleware incorporates technologies such as Linda-like tuplespaces and federated system architecture in order to obtain a high degree of collaboration and coordination for the agent society. A set of behavioral rules inspired by a community of bacterial strains is also generated as the means for robustness of the WSN. In this paper, we present In-Motes and provide a detailed evaluation of its implementation for MICA2 motes.
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Modern advances in technology have led to more complex manufacturing processes whose success centres on the ability to control these processes with a very high level of accuracy. Plant complexity inevitably leads to poor models that exhibit a high degree of parametric or functional uncertainty. The situation becomes even more complex if the plant to be controlled is characterised by a multivalued function or even if it exhibits a number of modes of behaviour during its operation. Since an intelligent controller is expected to operate and guarantee the best performance where complexity and uncertainty coexist and interact, control engineers and theorists have recently developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants. These techniques are based on incorporating model uncertainty. The newly developed control algorithms for incorporating model uncertainty are proven to give more accurate control results under uncertain conditions. In this paper, we survey some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty.
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This paper details the development and evaluation of AstonTAC, an energy broker that successfully participated in the 2012 Power Trading Agent Competition (Power TAC). AstonTAC buys electrical energy from the wholesale market and sells it in the retail market. The main focus of the paper is on the broker’s bidding strategy in the wholesale market. In particular, it employs Markov Decision Processes (MDP) to purchase energy at low prices in a day-ahead power wholesale market, and keeps energy supply and demand balanced. Moreover, we explain how the agent uses Non-Homogeneous Hidden Markov Model (NHHMM) to forecast energy demand and price. An evaluation and analysis of the 2012 Power TAC finals show that AstonTAC is the only agent that can buy energy at low price in the wholesale market and keep energy imbalance low.
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Editorial
Resumo:
Agents inhabiting large scale environments are faced with the problem of generating maps by which they can navigate. One solution to this problem is to use probabilistic roadmaps which rely on selecting and connecting a set of points that describe the interconnectivity of free space. However, the time required to generate these maps can be prohibitive, and agents do not typically know the environment in advance. In this paper we show that the optimal combination of different point selection methods used to create the map is dependent on the environment, no point selection method dominates. This motivates a novel self-adaptive approach for an agent to combine several point selection methods. The success rate of our approach is comparable to the state of the art and the generation cost is substantially reduced. Self-adaptation therefore enables a more efficient use of the agent's resources. Results are presented for both a set of archetypal scenarios and large scale virtual environments based in Second Life, representing real locations in London.
Resumo:
Discrepancies of materials, tools, and factory environments, as well as human intervention, make variation an integral part of the manufacturing process of any component. In particular, the assembly of large volume, aerospace parts is an area where significant levels of form and dimensional variation are encountered. Corrective actions can usually be taken to reduce the defects, when the sources and levels of variation are known. For the unknown dimensional and form variations, a tolerancing strategy is typically put in place in order to minimize the effects of production inconsistencies related to geometric dimensions. This generates a challenging problem for the automation of the corresponding manufacturing and assembly processes. Metrology is becoming a major contributor to being able to predict, in real time, the automated assembly problems related to the dimensional variation of parts and assemblies. This is done by continuously measuring dimensions and coordinate points, focusing on the product's key characteristics. In this paper, a number of metrology focused activities for large-volume aerospace products, including their implementation and application in the automation of manufacturing and assembly processes, are reviewed. This is done by using a case study approach within the assembly of large-volume aircraft wing structures.
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Today, the question of how to successfully reduce supply chain costs whilst increasing customer satisfaction continues to be the focus of many firms. It is noted in the literature that supply chain automation can increase flexibility whilst reducing inefficiencies. However, in the dynamic and process driven environment of distribution, there is the absence of a cohesive automation approach to guide companies in improving network competitiveness. This paper aims to address the gap in the literature by developing a three-level framework automation application approach with the assistance of radio frequency identification (RFID) technology and returnable transport equipment (RTE). The first level considers the automation of data retrieval and highlights the benefits of RFID. The second level consists of automating distribution processes such as unloading and assembling orders. As the labour is reduced with the introduction of RFID enabled robots, the balance between automation and labour is discussed. Finally, the third level is an analysis of the decision-making process at network points and the application of cognitive automation to objects. A distribution network scenario is formed and used to illustrate network reconfiguration at each level. The research pinpoints that RFID enabled RTE offers a viable tool to assist supply chain automation. Further research is proposed in particular, the area of cognitive automation to aide with decision-making.
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As the pressure continues to grow on Diamond and the world's synchrotrons for higher throughput of diffraction experiments, new and novel techniques are required for presenting micron dimension crystals to the X ray beam. Currently this task is both labour intensive and primarily a serial process. Diffraction measurements typically take milliseconds but sample preparation and presentation can reduce throughput down to 4 measurements an hour. With beamline waiting times as long as two years it is of key importance for researchers to capitalize on available beam time, generating as much data as possible. Other approaches detailed in the literature [1] [2] [3] are very much skewed towards automating, with robotics, the actions of a human protocols. The work detailed here is the development and discussion of a bottom up approach relying on SSAW self assembly, including material selection, microfluidic integration and tuning of the acoustic cavity to order the protein crystals.
Resumo:
As the pressure continues to grow on Diamond and the world's synchrotrons for higher throughput of diffraction experiments, new and novel techniques are required for presenting micron dimension crystals to the X ray beam. Currently this task is both labour intensive and primarily a serial process. Diffraction measurements typically take milliseconds but sample preparation and presentation can reduce throughput down to 4 measurements an hour. With beamline waiting times as long as two years it is of key importance for researchers to capitalize on available beam time, generating as much data as possible. Other approaches detailed in the literature [1] [2] [3] are very much skewed towards automating, with robotics, the actions of a human protocols. The work detailed here is the development and discussion of a bottom up approach relying on SSAW self assembly, including material selection, microfluidic integration and tuning of the acoustic cavity to order the protein crystals.
Resumo:
Metrology processes used in the manufacture of large products include tool setting, product verification and flexible metrology enabled automation. The range of applications and instruments available makes the selection of the appropriate instrument for a given task highly complex. Since metrology is a key manufacturing process it should be considered in the early stages of design. This paper provides an overview of the important selection criteria for typical measurement processes and presents some novel selection strategies. Metrics which can be used to assess measurability are also discussed. A prototype instrument selection and measurability analysis application is presented with discussion of how this can be used as the basis for development of a more sophisticated measurement planning tool. © Springer-Verlag Berlin Heidelberg 2010.
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Nearly a third of UK gas and electricity is used in homes, of which 80% is for space heating and hot water provision. Rising consumer bills, concerns about climate change and the surge in personal digital technology use has provoked the development of intelligent domestic heating controls. Whilst the need for having suitable control of the home heating system is essential for reducing domestic energy use, these heating controls rely on appropriate user interaction to achieve a saving and it is unclear whether these ‘smart’ heating controls enhance the use of domestic heating or reduce energy demand. This paper describes qualitative research undertaken with a small sample of UK householders to understand how people use new heating controls installed in their homes and what the requirements are for improved smart heating control design. The paper identifies, against Nielsen’s usability heuristics, the divergence between the householder’s use, understanding and expectations of the heating system and the actual design of the system. Digital and smart heating control systems should be designed to maximise usability so that they can be effectively used for efficient heating control by all users. The research highlights the need for development of new systems to readdress the needs of users and redefine the system requirements.