989 resultados para sensor platform


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This paper describes middleware-level support for agent mobility, targeted at hierarchically structured wireless sensor and actuator network applications. Agent mobility enables a dynamic deployment and adaptation of the application on top of the wireless network at runtime, while allowing the middleware to optimize the placement of agents, e.g., to reduce wireless network traffic, transparently to the application programmer. The paper presents the design of the mechanisms and protocols employed to instantiate agents on nodes and to move agents between nodes. It also gives an evaluation of a middleware prototype running on Imote2 nodes that communicate over ZigBee. The results show that our implementation is reasonably efficient and fast enough to support the envisioned functionality on top of a commodity multi-hop wireless technology. Our work is to a large extent platform-neutral, thus it can inform the design of other systems that adopt a hierarchical structuring of mobile components. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

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This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system

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This paper is focused on the robot mobile platform PRIM (platform robot information multimedia). This robot has been made in order to cover two main needs of our group, on one hand the need for a full open mobile robotic platform that is very useful in fulfilling the teaching and research activity of our school community, and on the other hand with the idea of introducing an ethical product which would be useful as mobile multimedia information point as a service tool. This paper introduces exactly how the system is made up and explains just what the philosophy is behind this work. The navigation strategies and sensor fusion, where machine vision system is the most important one, are oriented towards goal achievement and are the key to the behaviour of the robot

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Charged aerosol particles and water droplets are abundant throughout the lower atmosphere, and may influence interactions between small cloud droplets. This note describes a small, disposable sensor for the measurement of charge in non-thunderstorm cloud, which is an improvement of an earlier sensor [K. A. Nicoll and R. G. Harrison, Rev. Sci. Instrum. 80, 014501 (2009)]. The sensor utilizes a self-calibrating current measurement method. It is designed for use on a free balloon platform alongside a standard meteorological radiosonde, measuring currents from 2 fA to 15 pA and is stable to within 5 fA over a temperature range of 5 °C to −60 °C. During a balloon flight with the charge sensor through a stratocumulus cloud, charge layers up to 40 pC m−3 were detected on the cloud edges.

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Body Sensor Networks (BSNs) have been recently introduced for the remote monitoring of human activities in a broad range of application domains, such as health care, emergency management, fitness and behaviour surveillance. BSNs can be deployed in a community of people and can generate large amounts of contextual data that require a scalable approach for storage, processing and analysis. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of data streams generated in BSNs. This paper proposes BodyCloud, a SaaS approach for community BSNs that supports the development and deployment of Cloud-assisted BSN applications. BodyCloud is a multi-tier application-level architecture that integrates a Cloud computing platform and BSN data streams middleware. BodyCloud provides programming abstractions that allow the rapid development of community BSN applications. This work describes the general architecture of the proposed approach and presents a case study for the real-time monitoring and analysis of cardiac data streams of many individuals.

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A continued increase in computing power, sensor capability, software functionality, immersive interfaces and hardware modularity has given robot designers seemingly endless potential in the area of mobile robotics.  While some mobile robotic system designers are focusing on expensive, full-featured platforms, developers are realising the advantages of emerging technology in providing small, low-cost mobile reconnaissance vehicles as expendable teleoperated robotic systems.  The OzBotTM mobile reconnaissance platform presents one such system.  The design objectives of the OzBotTM platform focus on the development of inexpensive, lightweight carry-case sized robots for search and rescue operations, law enforcement scenarios and hazardous environment inspection.  The incorporation of Haptic augmentation provides the teleoperator with improved task immersion for an outdoor search and rescue scenario.  Achieved in cooperation with law enforcement agencies within Australia, this paper discusses the performance of the first four revisions of the OzBotTM platform.

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Recent developments in sensor networks and cloud computing saw the emergence of a new platform called sensor-clouds. While the proposition of such a platform is to virtualise the management of physical sensor devices, we foresee novel applications being created based on a new class of social sensors. Social sensors are effectively a human-device combination that sends torrents of data as a result of social interactions. The data generated appear in different formats such as photographs, videos, or short texts, etc. Unlike other sensor devices, social sensors operate on the control of individuals via their mobile devices like smart phones, tablets or laptops. Further, they do not generate data at a constant rate or format like other sensors do. Instead, data from social sensors are spurious and varied, often in response to social events, or a news announcement of interests to the public. This collective presence of social data creates opportunities for novel applications never experienced before. This paper discusses three such applications utilising social sensors within a sensor-cloud environment. Consequently, the associated research problems are also presented.

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Recent developments in sensor networks and cloud computing saw the emergence of a new platform called sensor-clouds. While the proposition of such a platform is to virtualise the management of physical sensor devices, we are seeing novel applications been created based on a new class of social sensors. Social sensors are effectively a human-device combination that sends torrent of data as a result of social interactions and social events. The data generated appear in different formats such as photographs, videos and short text messages. Unlike other sensor devices, social sensors operate on the control of individuals via their mobile devices such as a phone or a laptop. And unlike other sensors that generate data at a constant rate or format, social sensors generate data that are spurious and varied, often in response to events as individual as a dinner outing, or a news announcement of interests to the public. This collective presence of social data creates opportunities for novel applications never experienced before. This paper discusses such applications as a result of utilising social sensors within a sensor-cloud environment. Consequently, the associated research problems are also presented.

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An overview is given of the design and implementation of a platform for fast external sensor integration in an industrial robot system called ABB S4CPlus. As an application and motivating example, the implementation of force-controlled grinding and deburring within the AUTOFETT-project is discussed. Experiences from industrial usage of the fully developed prototype confirms the appropriateness of the design choices, thus also confirming the fact that control and software need to be tightly integrated. The new sensor can be used for the prototyping and development of a wide variety of new applications

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Sensor grid is a platform that combines wireless sensor networks and grid computing with the aim of exploiting the complementary advantages of the two systems. Proper integration of these distinct systems into effective, logically single platform is challenging. This paper presents an approach for practical sensor grid implementation and management. The proposed approach uses a metamodeling technique and performance analysis and tuning as well as a middleware infrastructure that enable practical sensor grid implementation and management. The paper presents our implementation and analysis of the sensor grid. © 2014 Srimathi Chandrasekaran et al.

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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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DNA biosensors have gained increased attention over traditional diagnostic methods due to their fast and responsive operation and cost-effective design. The specificity of DNA biosensors relies on single-stranded oligonucleotide probes immobilized to a transduction platform. Here, we report the development of biosensors to detect the hippuricase gene (hipO) from Campylobacter jejuni using direct covalent coupling of thiol- and biotin-labeled single-stranded DNA (ssDNA) on both surface plasmon resonance (SPR) and diffraction optics technology (DOT, dotLab) transduction platforms. This is the first known report of the dotLab to detect targeted DNA. Application of 6-mercapto-1-hexanol as a spacer thiol for SPR gold surface created a self-assembled monolayer that removed unbound ssDNA and minimized non-specific detection. The detection limit of SPR sensors was shown to be 2.5 nM DNA while dotLab sensors demonstrated a slightly decreased detection limit of 5.0 nM (0.005 μM). It was possible to reuse the SPR sensor due to the negligible changes in sensor sensitivity (∼9.7 × 10 -7 ΔRU) and minimal damage to immobilized probes following use, whereas dotLab sensors could not be reused. Results indicated feasibility of optical biosensors for rapid and sensitive detection of the hipO gene of Campylobacter jejuni using specific ssDNA as a probe. © 2011 Elsevier B.V.

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The detection of pertinent biomarkers has the potential provide an early indication of disease progression before considerable damage has been incurred. A decrease in an individual’s sensitivity to insulin, which may be quantified as the ratio of insulin to glucose in the blood after a glucose pulse, has recently been reported as an early predictor of insulin-dependent diabetes mellitus. Routine measurement of insulin levels is therefore desirable in the care of diabetes-prone individuals. A rapid, simple, and reagentless method for insulin detection would allow for wide-spread screenings that provide earlier signs of diabetes onset. The aim of this thesis is to develop a folding-base electrochemical sensor for the detection of insulin. The sensor described herein consists of a DNA probe immobilized on a gold disc electrode via an alkanethiol linker and embedded in an alkanethiol self-assembled monolayer. The probe is labeled with a redox reporter, which readily transfers electrons to the gold electrode in the absence of insulin. In the presence of insulin, electron transfer is inhibited, presumably due to a binding-induced conformational or dynamic change in the DNA probe that significantly alters the electron-tunneling pathway. A 28-base segment of the insulin-linked polymorphic region that has been reported to bind insulin with high affinity serves as the capture element of the DNA probe. Three probe constructs that vary in their secondary structure and position of the redox label are evaluated for their utility as insulin-sensing elements on the electrochemical platform. The effects of probe modification on secondary structure are also evaluated using circular dichroism spectroscopy.

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This paper describes a long-range remotely controlled CE system built on an all-terrain vehicle. A four-stroke engine and a set of 12-V batteries were used to provide power to a series of subsystems that include drivers, communication, computers, and a capillary electrophoresis module. This dedicated instrument allows air sampling using a polypropylene porous tube, coupled to a flow system that transports the sample to the inlet of a fused-silica capillary. A hybrid approach was used for the construction of the analytical subsystem combining a conventional fused-silica capillary (used for separation) and a laser machined microfluidic block, made of PMMA. A solid-state cooling approach was also integrated in the CE module to enable controlling the temperature and therefore increasing the useful range of the robot. Although ultimately intended for detection of chemical warfare agents, the proposed system was used to analyze a series of volatile organic acids. As such, the system allowed the separation and detection of formic, acetic, and propionic acids with signal-to-noise ratios of 414, 150, and 115, respectively, after sampling by only 30 s and performing an electrokinetic injection during 2.0 s at 1.0 kV.

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[EN]Detecting people is a key capability for robots that operate in populated environments. In this paper, we have adopted a hierarchical approach that combines classifiers created using supervised learning in order to identify whether a person is in the view-scope of the robot or not. Our approach makes use of vision, depth and thermal sensors mounted on top of a mobile platform.