Relevant bibliographies by topics / Sensor networks – Quality control

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Sensor networks – Quality control'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Sensor networks – Quality control"

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Bruneo, D., A. Puliafito, and M. Scarpa. "Energy control in dependable wireless sensor networks: a modelling perspective." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 225, no. 4 (July 20, 2011): 424–34. http://dx.doi.org/10.1177/1748006x10397845.

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Wireless sensor networks (WSN) are composed of a large number of tiny sensor nodes randomly distributed over a geographical region. In order to reduce power consumption, battery-operated sensors undergo cycles of sleeping–active periods that reduce their ability to send/receive data. Starting from the Markov reward model theory, this paper presents a dependability model to analyse the reliability of a sensor node. Also, a new dependability parameter is introduced, referred to as producibility, which is able to capture the capability of a sensor to accomplish its mission. Two different model solution techniques are proposed, one based on the evaluation of the accumulated reward distribution and the other based on an equivalent model based on non-Markovian stochastic Petri nets. The obtained results are used to investigate the dependability of a whole WSN taking into account the presence of redundant nodes. Topological aspects are taken into account, providing a quantitative comparison among three typical network topologies: star, tree, and mesh. Numerical results are provided in order to highlight the advantages of the proposed technique and to demonstrate the equivalence of the proposed approaches.
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Bok, Kyoungsoo, Eunkyung Ryu, Junho Park, Jaijin Jung, and Jaesoo Yoo. "Multimedia congestion control in wireless sensor networks." Computer Science and Information Systems 12, no. 2 (2015): 801–21. http://dx.doi.org/10.2298/csis141009027b.

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In this paper, we propose a new congestion control scheme to minimize data loss and maintain data quality in wireless multimedia sensor networks. The proposed scheme extracts and transfers dynamic regions by considering monitoring characteristics over multimedia sensor network environments to reduce the transferred data. Furthermore, it can reduce the packet size by deleting and transferring low-priority bit data by considering multimedia data characteristics during congestion situations to minimize packet loss. To show the superiority of the proposed scheme, we compare it with the existing congestion control schemes through simulation.
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Taylor, J. R., and H. L. Loescher. "Automated quality control methods for sensor data: a novel observatory approach." Biogeosciences 10, no. 7 (July 24, 2013): 4957–71. http://dx.doi.org/10.5194/bg-10-4957-2013.

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Abstract. National and international networks and observatories of terrestrial-based sensors are emerging rapidly. As such, there is demand for a standardized approach to data quality control, as well as interoperability of data among sensor networks. The National Ecological Observatory Network (NEON) has begun constructing their first terrestrial observing sites, with 60 locations expected to be distributed across the US by 2017. This will result in over 14 000 automated sensors recording more than > 100 Tb of data per year. These data are then used to create other datasets and subsequent "higher-level" data products. In anticipation of this challenge, an overall data quality assurance plan has been developed and the first suite of data quality control measures defined. This data-driven approach focuses on automated methods for defining a suite of plausibility test parameter thresholds. Specifically, these plausibility tests scrutinize the data range and variance of each measurement type by employing a suite of binary checks. The statistical basis for each of these tests is developed, and the methods for calculating test parameter thresholds are explored here. While these tests have been used elsewhere, we apply them in a novel approach by calculating their relevant test parameter thresholds. Finally, implementing automated quality control is demonstrated with preliminary data from a NEON prototype site.
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Taylor, J. R., and H. L. Loescher. "Automated quality control methods for sensor data: a novel observatory approach." Biogeosciences Discussions 9, no. 12 (December 14, 2012): 18175–210. http://dx.doi.org/10.5194/bgd-9-18175-2012.

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Abstract. National and international networks and observatories of terrestrial-based sensors are emerging rapidly. As such, there is demand for a standardized approach to data quality control, as well as interoperability of data among sensor networks. The National Ecological Observatory Network (NEON) has begun constructing their first terrestrial observing sites with 60 locations expected to be distributed across the US by 2017. This will result in over 14 000 automated sensors recording more than > 100 Tb of data per year. These data are then used to create other datasets and subsequent "higher-level" data products. In anticipation of this challenge, an overall data quality assurance plan has been developed and the first suite of data quality control measures defined. This data-driven approach focuses on automated methods for defining a suite of plausibility test parameter thresholds. Specifically, these plausibility tests scrutinize data range, persistence, and stochasticity on each measurement type by employing a suite of binary checks. The statistical basis for each of these tests is developed and the methods for calculating test parameter thresholds are explored here. While these tests have been used elsewhere, we apply them in a novel approach by calculating their relevant test parameter thresholds. Finally, implementing automated quality control is demonstrated with preliminary data from a NEON prototype site.
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Tati, Reza, Fariborz Ahmadi, Farhad Jafari, and Mostafa Tofighi. "Quality of Service Support in Wireless Sensor Networks." Key Engineering Materials 467-469 (February 2011): 2078–84. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.2078.

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All of middlewares of modern wireless sensor networks has this weakness that many of these middlewares have the ability to simultaneous support from limit amounts of quality of service parameters. Our aim is simultaneous and dynamic support from several quality of service measure in middleware layer with obtained weight coefficients. In this paper, we add a layer of Quality of service management to middleware, in which this layer has duty of service of Quality of service management and control. This layer answers demanded Quality of service improvement from application by wireless sensor network.
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Li, Xiaomin, Lixue Zhu, Xuan Chu, and Han Fu. "Edge Computing-Enabled Wireless Sensor Networks for Multiple Data Collection Tasks in Smart Agriculture." Journal of Sensors 2020 (February 25, 2020): 1–9. http://dx.doi.org/10.1155/2020/4398061.

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At present, precision agriculture and smart agriculture are the hot topics, which are based on the efficient data collection by using wireless sensor networks (WSNs). However, agricultural WSNs are still facing many challenges such as multitasks, data quality, and latency. In this paper, we propose an efficient solution for multiple data collection tasks exploiting edge computing-enabled wireless sensor networks in smart agriculture. First, a novel data collection framework is presented by merging WSN and edge computing. Second, the data collection process is modeled, including a plurality of sensors and tasks. Next, according to each specific task and correlation between task and sensors, on the edge computing server, a double selecting strategy is established to determine the best node and sensor network that fulfills quality of data and data collection time constraints of tasks. Furthermore, a data collection algorithm is designed, based on set values for quality of data. Finally, a simulation environment is constructed where the proposed strategy is applied, and results are analyzed and compared to the traditional methods. According to the comparison results, the proposal outperforms the traditional methods in metrics.
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Mwashita, Weston, and Marcel Ohanga Odhiambo. "A Power Control Strategy for IoT Sensors Developed for 5G Networks." International Journal of Smart Sensor Technologies and Applications 1, no. 1 (January 2020): 22–41. http://dx.doi.org/10.4018/ijssta.2020010103.

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This research work presents a power control mechanism developed for ProSe-enabled sensors so that the sensors can be smoothly integrated into the fifth generation (5G) of mobile networks. It is strongly anticipated that 5G networks will provide an enabling environment for the 21st century innovations like the internet of things (IoT). Sensors are pivotal in IoT. The proposed power control mechanism involves an open loop power control (OLPC) mechanism that a ProSe-enabled sensor has to use to establish communication with a base station (BS) and a closed loop power control (CLPC) the BS then has use to establish transmit power levels for devices to be involved in a device to device (D2D) communication depending on the prevailing channel conditions. The results obtained demonstrate that the developed scheme does not adversely affect the quality of service (QoS) of a 5G mobile network.
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Ogbodo, Emmanuel, David Dorrell, and Adnan Abu-Mahfouz. "Energy-efficient distributed heterogeneous clustered spectrum-aware cognitive radio sensor network for guaranteed quality of service in smart grid." International Journal of Distributed Sensor Networks 17, no. 7 (July 2021): 155014772110283. http://dx.doi.org/10.1177/15501477211028399.

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The development of a modern electric power grid has triggered the need for large-scale monitoring and communication in smart grids for efficient grid automation. This has led to the development of smart grids, which utilize cognitive radio sensor networks, which are combinations of cognitive radios and wireless sensor networks. Cognitive radio sensor networks can overcome spectrum limitations and interference challenges. The implementation of dense cognitive radio sensor networks, based on the specific topology of smart grids, is one of the critical issues for guaranteed quality of service through a communication network. In this article, various topologies of ZigBee cognitive radio sensor networks are investigated. Suitable topologies with energy-efficient spectrum-aware algorithms of ZigBee cognitive radio sensor networks in smart grids are proposed. The performance of the proposed ZigBee cognitive radio sensor network model with its control algorithms is analyzed and compared with existing ZigBee sensor network topologies within the smart grid environment. The quality of service metrics used for evaluating the performance are the end-to-end delay, bit error rate, and energy consumption. The simulation results confirm that the proposed topology model is preferable for sensor network deployment in smart grids based on reduced bit error rate, end-to-end delay (latency), and energy consumption. Smart grid applications require prompt, reliable, and efficient communication with low latency. Hence, the proposed topology model supports heterogeneous cognitive radio sensor networks and guarantees network connectivity with spectrum-awareness. Hence, it is suitable for efficient grid automation in cognitive radio sensor network–based smart grids. The traditional model lacks these capability features.
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Ganesan, Sangeetha, Vijayalakshmi Muthuswamy, Ganapathy Sannasi, and Kannan Arputharaj. "A Comprehensive Analysis of Congestion Control Models in Wireless Sensor Networks." International Journal of Strategic Information Technology and Applications 9, no. 4 (October 2018): 15–37. http://dx.doi.org/10.4018/ijsita.2018100102.

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Congestion control is an important factor for performance improvement in wireless sensor networks (WSNs). Congestion occurs due to various reasons including a variation in the data rate between incoming and outgoing links, buffer size, flooding attacks and multiple inputs and minimum output capability. Various outcomes of congestion in sensor networks include immense packet loss or packet drop, fast energy depletion, unfairness across the network, reduced node performance and increased delay in packet delivery. Hence, there is an extreme need to check channel congestion in order to enhance the performance with better congestion management. The job of choosing a suitable congestion control technique is a challenging task for the network designer. In this article, the authors traverse through the underlying conceptual ideas on congestion control schemes which come under six unique models. This article highlights a survey on the existing works done so far on congestion control domains in sensor networks. A comparative analysis based on Quality of Service parameters has been discussed.
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Sastry, Shivakumar, and S. S. Iyengar. "Real-Time Sensor-Actuator Networks." International Journal of Distributed Sensor Networks 1, no. 1 (February 2005): 17–34. http://dx.doi.org/10.1080/15501320490886314.

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Emerging technologies offer new paradigms for computation, control, collaboration, and communication. To realize the full potential of these technologies in industry, defense, and homeland security applications, it is necessary to exploit the real-time distributed computing capabilities of sensor-actuator networks. To reliably design and develop such networks, it is necessary to develop deeper insight into the underlying model for real-time computation and the infrastructure at the node level that supports this model. In this paper, we discuss a new node-level operating system and mechanisms necessary to deploy reliable applications. The overriding issue that guides the design of this operating system is quality of service metric called predictability. A sensor-actuator network is a distributed platform for integrated computation and control in real-time environments. The nodes in such a network are distinguished by being resource constrained. The power of the network arises from the interactions between simple nodes. Such a network extends the popular distributed sensor networks in several dimensions. After identifying a real-time model, we develop a notion of predictability for a sensor-actuator network. We discuss how the node-level operating system is designed in the resource-constrained environment. An efficient multithreading mechanism and scheduling strategy are required to ensure that local tasks are executed within jitter bounds and that end-to-end delays do not violate application constraints. Mechanisms to support communication, monitoring, safety, fault tolerance, programming, diagnosability, reconfiguration, composability, interoperability, and security are discussed.
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Dissertations / Theses on the topic "Sensor networks – Quality control"

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Bildea, Ana. "Link Quality in Wireless Sensor Networks." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENM054/document.

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L'objectif de la thèse est d'étudier la variation temporelle de la qualité des liens dans les réseaux de capteurs sans fil à grande échelle, de concevoir des estimateurs permettant la différenciation, à court terme et long terme, entre liens de qualité hétérogène. Tout d'abord, nous étudions les caractéristiques de deux paramètres de la couche physique: RSSI (l'indicateur de puissance du signal reçu) et LQI (l'indicateur de la qualité de liaison) sur SensLab, une plateforme expérimentale de réseau de capteurs à grande échelle situé à l'intérieur de bâtiments. Nous observons que le RSSI et le LQI permettent de discriminer des liens de différentes qualités. Ensuite, pour obtenir un estimateur de PRR, nous avons approximé le diagramme de dispersion de la moyenne et de l'écart-type du LQI et RSSI par une fonction Fermi-Dirac. La fonction nous permet de trouver le PRR à partir d'un niveau donné de LQI. Nous avons évalué l'estimateur en calculant le PRR sur des fenêtres de tailles variables et en le comparant aux valeurs obtenues avec l'estimateur. Par ailleurs, nous montrons en utilisant le modèle de Gilbert-Elliot (chaîne de Markov à deux états) que la corrélation des pertes de paquets dépend de la catégorie de lien. Le modèle permet de distinguer avec précision les différentes qualités des liens, en se basant sur les probabilités de transition dérivées de la moyenne et de l'écart-type du LQI. Enfin, nous proposons un modèle de routage basé sur la qualité de lien déduite de la fonction de Fermi-Dirac approximant le PRR et du modèle Markov Gilbert-Elliot à deux états. Notre modèle est capable de distinguer avec précision les différentes catégories de liens ainsi que les liens fortement variables
The goal of the thesis is to investigate the issues related to the temporal link quality variation in large scale WSN environments, to design energy efficient link quality estimators able to distinguish among links with different quality on a short and a long term. First, we investigate the characteristics of two physical layer metrics: RSSI (Received Signal Strength Indication) and LQI (Link Quality Indication) on SensLAB, an indoor large scale wireless sensor network testbed. We observe that RSSI and LQI have distinct values that can discriminate the quality of links. Second, to obtain an estimator of PRR, we have fitted a Fermi-Dirac function to the scatter diagram of the average and standard variation of LQI and RSSI. The function enables us to find PRR for a given level of LQI. We evaluate the estimator by computing PRR over a varying size window of transmissions and comparing with the estimator. Furthermore, we show using the Gilbert-Elliot two-state Markov model that the correlation of packet losses and successful receptions depend on the link category. The model allows to accurately distinguish among strongly varying intermediate links based on transition probabilities derived from the average and the standard variation of LQI. Finally, we propose a link quality routing model driven from the F-D fitting functions and the Markov model able to discriminate accurately link categories as well as high variable links
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LI, I.-HUNG. "Phase and Rate Control for Improving Information Quality in 802.15.4 Wireless Sensor." OpenSIUC, 2010. https://opensiuc.lib.siu.edu/theses/396.

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High information quality is a paramount requirement for wireless sensor network monitoring applications. However, it is challenging to achieve a cost effective information quality solution due to unpredictable environment noise and events, unreliable wireless channel and network bandwidth, and resource and energy constraints. Specifically, the dynamic and unreliable nature of WSNs make it difficult to pre-determine optimum sensor rates and predict packet loss. To address this problem, we use information quality metrics presented by [26, 11] which characterize information quality based on the sampling frequency of sensor nodes and the packet loss rate during network transmission. These fundamental quality metrics are based on signal-to-noise ratio and are therefore application independent. Based on these metrics, a quality-aware scheduling system (QSS) is developed, which exploits cross-layer control of sensor nodes to effectively schedule data sensing and forwarding. Particularly, we develop and evaluate several QSS scheduling mechanisms: passive, reactive and perceptive. These mechanisms can adapt to environment noise, bandwidth variation and wireless channel collisions by dynamically controlling sensor rates and sensor phase. Our software and hardware experimental results indicate that our QSS is a novel and effective approach to improve information quality for WSNs.
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Nkwogu, Daniel Nnaemeka. "Quality of service optimization and adaptive learning in wireless sensor actuator networks for control applications." Thesis, University of Aberdeen, 2014. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=215699.

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Wireless sensor actuator networks (WSANs) are becoming a solution for the implementation of control applications. Sensors and actuators can be deployed forming a large or dense network to monitor and control physical parameters or systems. However, this comes with challenges. Reliable data transmission and real-time communication constraints are the most significant challenges in WSANs for control applications because wireless networks are characterised by harsh transmission conditions. The use of WSANs for critical control applications has not gained sufficient progress as wireless networks are perceived to be totally unreliable and hence unsuitable. This makes reliable data transmission a priority in this research. Control applications will have a number of quality of service (QoS) requirements, such as requiring a very low packet-loss rate (PLR), minimum delay and guaranteed packet delivery. The overall goal of this research is to develop a framework that ensures reliable and real-time communication within the sensor network. A totally reliable network design involves ensuring reliability in areas such as the medium access control, connectivity, scalability, lifetime, clustering and routing with trade-offs such as energy consumption, system throughput and computational complexity. In this thesis, we introduce a unique method of improving reliability and real-time communication for control applications using a link quality routing mechanism which is tied into the ZigBee addressing scheme. ZigBee routing protocols do not consider link quality when making routing decisions. The results based on common network test conditions give a clear indication of the impact on network performance for various path loss models. The proposed link quality aware routing (LQAR) showed a highly significant 20.5% improvement in network delays against the ZigBee hierarchical tree routing (HTR) protocol. There is also a 17% improvement in the PLR. We also investigate variable sampling to mitigate the effects of delay in WSANs using a neural network delay predictor and observer based control system model. Our focus on variable sampling is to determine the appropriate neural network topology for delay prediction and the impact of additional neural network inputs such as PLR and throughput. The major contribution of this work is the use of typical obtainable delay series for training the neural network. Most studies have used random generated numbers which are not a correct representation of delays actually experienced in a wireless network. In addition, results show that the use of network packet loss information improves the prediction accuracy of delay. Our results show that adequate prediction of the time-delay series using the observer based variable sampling model influences the performance of the control system model under the assumptions and stated conditions.
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Hughes, Jack Bryan. "Real-time link quality estimation and holistic transmission power control for wireless sensor networks." Thesis, University of Huddersfield, 2018. http://eprints.hud.ac.uk/id/eprint/34661/.

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Wireless sensor networks (WSNs) are becoming widely adopted across multiple industries to implement sensor and non-critical control applications. These networks of smart sensors and actuators require energy efficient and reliable operation to meet application requirements. Regulatory body restrictions, hardware resource constraints and an increasingly crowded network space makes realising these requirements a significant challenge. Transmission power control (TPC) protocols are poised for wide spread adoption in WSNs to address energy constraints and prolong the lifetime of the networked devices. The complex and dynamic nature of the transmission medium; the processing and memory hardware resource constraints and the low channel throughput makes identifying the optimum transmission power a significant challenge. TPC protocols for WSNs are not well developed and previously published works suffer from a number of common deficiencies such as; having poor tuning agility, not being practical to implement on the resource constrained hardware and not accounting for the energy consumed by packet retransmissions. This has resulted in several WSN standards featuring support for TPC but no formal definition being given for its implementation. Addressing the deficiencies associated with current works is required to increase the adoption of TPC protocols in WSNs. In this thesis a novel holistic TPC protocol with the primary objective of increasing the energy efficiency of communication activities in WSNs is proposed, implemented and evaluated. Firstly, the opportunities for TPC protocols in WSN applications were evaluated through developing a mathematical model that compares transmission power against communication reliability and energy consumption. Applying this model to state-of-the-art (SoA) radio hardware and parameter values from current WSN standards, the maximum energy savings were quantified at up to 80% for links that belong to the connected region and up to 66% for links that belong to the transitional and disconnected regions. Applying the results from this study, previous assumptions that protocols and mechanisms, such as TPC, not being able to achieve significant energy savings at short communications distances are contested. This study showed that the greatest energy savings are achieved at short communication distances and under ideal channel conditions. An empirical characterisation of wireless link quality in typical WSN environments was conducted to identify and quantify the spatial and temporal factors which affect radio and link dynamics. The study found that wireless link quality exhibits complex, unique and dynamic tendencies which cannot be captured by simplistic theoretical models. Link quality must therefore be estimated online, in real-time, using resources internal to the network. An empirical characterisation of raw link quality metrics for evaluating channel quality, packet delivery and channel stability properties of a communication link was conducted. Using the recommendations from this study, a novel holistic TPC protocol (HTPC) which operates on a per-packet basis and features a dynamic algorithm is proposed. The optimal TP is estimated through combining channel quality and packet delivery properties to provide a real-time estimation of the minimum channel gain, and using the channel stability properties to implement an adaptive fade margin. Practical evaluations show that HTPC is adaptive to link quality changes and outperforms current TPC protocols by achieving higher energy efficiency without detrimentally affecting the communication reliability. When subjected to several common temporal variations, links implemented with HTPC consumed 38% less than the current practise of using a fixed maximum TP and between 18-39% less than current SoA TPC protocols. Through offline computations, HTPC was found to closely match the performance of the optimal link performance, with links implemented with HTPC only consuming 7.8% more energy than when the optimal TP is considered. On top of this, real-world implementations of HTPC show that it is practical to implement on the resource constrained hardware as a result of implementing simplistic metric evaluation techniques and requiring minimal numbers of samples. Comparing the performance and characteristics of HTPC against previous works, HTPC addresses the common deficiencies associated with current solutions and therefore presents an incremental improvement on SoA TPC protocols.
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Dargie, Waltenegus. "Impact of Random Deployment on Operation and Data Quality of Sensor Networks." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2010. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-32911.

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Several applications have been proposed for wireless sensor networks, including habitat monitoring, structural health monitoring, pipeline monitoring, and precision agriculture. Among the desirable features of wireless sensor networks, one is the ease of deployment. Since the nodes are capable of self-organization, they can be placed easily in areas that are otherwise inaccessible to or impractical for other types of sensing systems. In fact, some have proposed the deployment of wireless sensor networks by dropping nodes from a plane, delivering them in an artillery shell, or launching them via a catapult from onboard a ship. There are also reports of actual aerial deployments, for example the one carried out using an unmanned aerial vehicle (UAV) at a Marine Corps combat centre in California -- the nodes were able to establish a time-synchronized, multi-hop communication network for tracking vehicles that passed along a dirt road. While this has a practical relevance for some civil applications (such as rescue operations), a more realistic deployment involves the careful planning and placement of sensors. Even then, nodes may not be placed optimally to ensure that the network is fully connected and high-quality data pertaining to the phenomena being monitored can be extracted from the network. This work aims to address the problem of random deployment through two complementary approaches: The first approach aims to address the problem of random deployment from a communication perspective. It begins by establishing a comprehensive mathematical model to quantify the energy cost of various concerns of a fully operational wireless sensor network. Based on the analytic model, an energy-efficient topology control protocol is developed. The protocol sets eligibility metric to establish and maintain a multi-hop communication path and to ensure that all nodes exhaust their energy in a uniform manner. The second approach focuses on addressing the problem of imperfect sensing from a signal processing perspective. It investigates the impact of deployment errors (calibration, placement, and orientation errors) on the quality of the sensed data and attempts to identify robust and error-agnostic features. If random placement is unavoidable and dense deployment cannot be supported, robust and error-agnostic features enable one to recognize interesting events from erroneous or imperfect data.
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Stucki, Eric Thomas. "Medium Access Control and Networking Protocols for the Intra-Body Network." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1182.pdf.

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Speer, Ngoc Anh Phan. "Design and Analysis of Adaptive Fault Tolerant QoS Control Algorithms for Query Processing in Wireless Sensor Networks." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/27221.

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Data sensing and retrieval in WSNs have a great applicability in military, environmental, medical, home and commercial applications. In query-based WSNs, a user would issue a query with QoS requirements in terms of reliability and timeliness, and expect a correct response to be returned within the deadline. Satisfying these QoS requirements requires that fault tolerance mechanisms through redundancy be used, which may cause the energy of the system to deplete quickly. This dissertation presents the design and validation of adaptive fault tolerant QoS control algorithms with the objective to achieve the desired quality of service (QoS) requirements and maximize the system lifetime in query-based WSNs. We analyze the effect of redundancy on the mean time to failure (MTTF) of query-based cluster-structured WSNs and show that an optimal redundancy level exists such that the MTTF of the system is maximized. We develop a hop-by-hop data delivery (HHDD) mechanism and an Adaptive Fault Tolerant Quality of Service Control (AFTQC) algorithm in which we utilize "source" and "path" redundancy with the goal to satisfy application QoS requirements while maximizing the lifetime of WSNs. To deal with network dynamics, we investigate proactive and reactive methods to dynamically collect channel and delay conditions to determine the optimal redundancy level at runtime. AFTQC can adapt to network dynamics that cause changes to the node density, residual energy, sensor failure probability, and radio range due to energy consumption, node failures, and change of node connectivity. Further, AFTQC can deal with software faults, concurrent query processing with distinct QoS requirements, and data aggregation. We compare our design with a baseline design without redundancy based on acknowledgement for data transmission and geographical routing for relaying packets to demonstrate the feasibility. We validate analytical results with extensive simulation studies. When given QoS requirements of queries in terms of reliability and timeliness, our AFTQC design allows optimal â sourceâ and â pathâ redundancies to be identified and applied dynamically in response to network dynamics such that not only query QoS requirements are satisfied, as long as adequate resources are available, but also the lifetime of the system is prolonged.
Ph. D.
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Boubrima, Ahmed. "Deployment and scheduling of wireless sensor networks for air pollution monitoring." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI018.

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Les réseaux de capteurs sans fil (RCSF) sont largement utilisés dans les applications environnementales où l’objectif est de détecter un phénomène physique tel que la température, l’humidité, la pollution de l’air, etc. Dans ce contexte d’application, l’utilisation de RCSF permet de comprendre les variations du phénomène et donc être en mesure de prendre des décisions appropriées concernant son impact. En raison des limitations de ses méthodes de suivi traditionnelles et de sa grande variabilité spatiale et temporelle, la pollution de l'air est considérée comme l'un des principaux phénomènes physiques qui restent à étudier et à caractériser. Dans cette thèse, nous considérons trois applications concernant l’utilisation de RCSF pour le suivi de la pollution de l’air : la cartographie en temps réel de la qualité de l’air, la détection de dépassements de seuils des polluants et la correction de modèles physiques qui simulent le phénomène de dispersion de la pollution. Toutes ces applications nécessitent de déployer et d’ordonnancer minutieusement les capteurs afin de mieux comprendre la pollution atmosphérique tout en garantissant un coût de déploiement minimal et en maximisant la durée de vie du réseau. Notre objectif est de résoudre les problèmes de déploiement et d'ordonnancement tout en tenant compte des caractéristiques spécifiques du phénomène de la pollution de l’air. Nous proposons pour chaque cas d'application une approche efficace pour le déploiement de noeuds capteurs et puits. Nous proposons également une approche d’ordonnancement adaptée au cas de la correction de modèles physiques. Nos approches d'optimisation prennent en compte la nature physique de la pollution atmosphérique et intègrent les données réelles fournies par les plateformes existantes de suivi de la qualité de l’air. Dans chacune de nos approches d’optimisation, nous utilisons la programmation linéaire en nombres entiers pour concevoir des modèles d’optimisation adaptés à la résolution de petites et moyennes instances. Pour traiter les grandes instances, nous proposons des heuristiques en utilisant des techniques de relaxation linéaire. Outre nos travaux théoriques sur le suivi de la pollution atmosphérique, nous avons conçu et déployé dans la ville de Lyon un réseau de capteurs de pollution économe en énergie. Sur la base des caractéristiques de notre système et des jeux de données de la pollution atmosphérique, nous avons évalué l’efficacité de nos approches de déploiement et d’ordonnancement. Nous présentons et discutons dans cette thèse les résultats d'évaluation de performances ainsi que des lignes directrices pour la conception de systèmes de suivi de la pollution de l’air. Parmi nos principales conclusions, nous soulignons le fait que la taille optimale du réseau de capteurs dépend du degré de variation des concentrations de pollution dans la région de déploiement
Wireless sensor networks (WSN) are widely used in environmental applications where the aim is to sense a physical phenomenon such as temperature, humidity, air pollution, etc. In this context of application, the use of WSN allows to understand the variations of the phenomenon over the monitoring region and therefore be able to take adequate decisions regarding the impact of the phenomenon. Due to the limitations of its traditional costly monitoring methods in addition to its high spatial and temporal variability, air pollution is considered as one of the main physical phenomena that still need to be studied and characterized. In this thesis, we consider three main applications regarding the use of WSN for air pollution monitoring: 1) the construction of real time air quality maps using sensor measurements; 2) the detection of pollution threshold crossings; and 3) the correction of physical models that simulate the pollution dispersion phenomenon. All these applications need careful deployment and scheduling of sensors in order to get a better knowledge of air pollution while ensuring a minimal deployment cost and a maximal lifetime of the deployed sensor network. Our aim is to tackle the problems of WSN deployment and scheduling while considering the specific characteristics of the air pollution phenomenon. We propose for each application case a new efficient approach for the deployment of sensor and sink nodes. We also propose a WSN scheduling approach that is adapted to the case of physical models’ correction. Our optimization approaches take into account the physical nature of air pollution dispersion and incorporate real data provided by the existing pollution sensing platforms. As part of each approach, we use integer linear programming to derive optimization models that are well adapted to solving small and medium instances. To deal with large instances, we propose heuristic algorithms while using linear relaxation techniques. Besides our theoretical works on air pollution monitoring, we design from scratch and deploy in the Lyon city a cost-effective energy-efficient air pollution sensor network. Based on the characteristics of our monitoring system in addition to real world air pollution datasets, we evaluate the effectiveness of our deployment and scheduling approaches and provide engineering insights for the design of WSN-based air pollution monitoring systems. Among our conclusions, we highlight the fact that the size of the optimal sensor network depends on the degree of the variations of pollution concentrations within the monitoring region
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Ouyang, Wenbin. "On-Loom Fabric Defect Inspection Using Contact Image Sensors and Activation Layer Embedded Convolutional Neural Network." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404537/.

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Malfunctions on loom machines are the main causes of faulty fabric production. An on-loom fabric inspection system is a real-time monitoring device that enables immediate defect detection for human intervention. This dissertation presented a solution for the on-loom fabric defect inspection, including the new hardware design—the configurable contact image sensor (CIS) module—for on-loom fabric scanning and the defect detection algorithms. The main contributions of this work include (1) creating a configurable CIS module adaptable to a loom width, which brings CIS unique features, such as sub-millimeter resolution, compact size, short working distance and low cost, to the fabric defect inspection system, (2) designing a two-level hardware architecture that can be efficiently deployed in a weaving factory with hundreds of looms, (3) developing a two-level inspecting scheme, with which the initial defect screening is performed on the Raspberry Pi and the intensive defect verification is processed on the cloud server, (4) introducing the novel pairwise-potential activation layer to a convolutional neural network that leads to high accuracies of defect segmentation on fabrics with fine and imbalanced structures, (5) achieving a real-time defect detection that allows a possible defect to be examined multiple times, and (6) implementing a new color segmentation technique suitable for processing multi-color fabric defects. The novel CIS-based on-loom scanning system offered real-time and high-resolution fabric images, which was able to deliver the information of single thread on a fabric. The algorithm evaluation on the fabric defect datasets showed a non-miss-detection rate on defect-free fabrics. The average precision of defect existed images reached above 90% at the pixel level. The detected defect pixels' integrity—the recall scored around 70%. Possible defect regions overestimated on ground truth images and the morphologies of fine defects similar to regular fabric pattern were the two major reasons that caused the imperfection in defect pixel locating. The experiments showed the defect areas on multi-color fabrics could be precisely located under the proposed color segmentation algorithm.
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Souil, Marion. "Contribution à la qualité de service dans les réseaux de capteurs sans fil." Phd thesis, Université de Technologie de Compiègne, 2013. http://tel.archives-ouvertes.fr/tel-00919777.

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L'apparition récente de petits capteurs peu couteux fonctionnant sur batteries, capables de traiter les données acquises et de les transmettre par ondes radio ont le potentiel de révolutionner les applications de surveillance traditionnelles. Les réseaux sans fils composés de nœuds capteurs autonomes proches de la cible à surveiller permettent des tâches de surveillance précises allant du contrôle de la température dans des bâtiments jusqu'a la détection de feux de forêt. Récemment, de nouvelles applications de réseaux de capteurs sans fil telles que des applications multimédia ou dans le domaine de la santé ont émergé. Les réseaux sous-jacents déployés pour ces applications sont souvent compos'es de nœuds hétérogènes comportant différents capteurs et doivent fournir un niveau de service conforme aux exigences des différents types de trafic en s'adaptant à la charge variable. Cependant, concevoir des protocoles efficaces adaptés à ces applications tout en s'accommodant des ressources limitées des réseaux de capteurs est une tâche difficile. Dans cette thèse, nous nous focalisons sur le support de la qualité de service au niveau de la couche MAC, car cette couche conditionne et détermine largement les performances du réseau étant donné qu'elle est responsable de l'organisation de l'accès au canal. Dans un premier temps, nous étudions les contraintes spécifiques des applications ayant des exigences fortes ainsi que des applications hétérogènes et nous examinons les travaux proposés dans la littérature. Etant donné l'inadéquation des solutions existantes en présence d'un trafic important, nous proposons AMPH, un protocole MAC adaptatif avec qualité de service pour les réseaux de capteurs sans fil hétérogènes. Notre solution consiste en une méthode d'accès au canal hybride basée sur le multiplexage temporel, dans laquelle tous les nœuds peuvent accéder au canal à chaque division de temps en utilisant un nouveau mécanisme de compétition qui favorise le trafic prioritaire. Grâce à ces techniques, AMPH utilise efficacement le canal quelque soit la charge de trafic et assure une latence faible au trafic temps réel. Nous vérifions les performances d'AMPH à l'aide de simulations et d'un modèle mathématique.
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Books on the topic "Sensor networks – Quality control"

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Consorzio Nazionale Interuniversitario per le Telecomunicazioni, IEEE South and Central Italy Section, IEEE Communications Society, and Tirrenia International Workshop on Digital Communications (18th : 2007 : University of Padova, Italy), eds. Wireless Communications: 2007 CNIT Thyrrenian Symposium. New York: Springer Science + Business Media, 2008.

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Wang, Bang. Coverage control in sensor networks. London: Springer, 2010.

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Wang, Bang. Coverage Control in Sensor Networks. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-059-5.

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1979-, Gschwender Adam, ed. ZigBee wireless sensor and control network. Upper Saddle River, NJ: Prentice Hall, 2010.

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Santi, Paolo. Topology Control in Wireless Ad Hoc and Sensor Networks. Chichester, UK: John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470094559.

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Topology control in wireless ad hoc and sensor networks. Chichester, UK: John Wiley & Sons, 2004.

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Santi, Paolo. Topology Control in Wireless Ad Hoc and Sensor Networks. New York: John Wiley & Sons, Ltd., 2005.

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Elahi, Ata. ZigBee wireless sensor and control network. Upper Saddle River, NJ: Prentice Hall, 2010.

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Elahi, Ata. ZigBee wireless sensor and control network. Upper Saddle River, NJ: Prentice Hall, 2010.

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Patan, Maciej. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Book chapters on the topic "Sensor networks – Quality control"

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Izadi, Davood, Jemal Abawajy, and Sara Ghanavati. "Quality Control of Sensor Network Data." In Lecture Notes in Electrical Engineering, 467–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25553-3_58.

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Seelam, Koteswararao, Kathala Krishna Chaitanya Rao, Komal Vyas, and Thanuku Aishwarya. "A Novel Contention Resolution Protocol for Wireless Sensor Networks." In ICICCT 2019 – System Reliability, Quality Control, Safety, Maintenance and Management, 449–56. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8461-5_50.

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Anil Kumar, Kakelli, Addepalli V. N. Krishna, and K. Shahu Chatrapati. "Congestion Control in Heterogeneous Wireless Sensor Networks for High-Quality Data Transmission." In Proceedings of the International Congress on Information and Communication Technology, 429–37. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0755-2_46.

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Spyrou, Evangelos D., and Dimitrios K. Mitrakos. "Optimising Wireless Sensor Network Link Quality Through Power Control with Non-convex Utilities Using Game Theory." In Ad-hoc, Mobile, and Wireless Networks, 255–61. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67910-5_21.

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Penhaker, Marek, Monika Darebnikova, and Martin Cerny. "Sensor Network for Measurement and Analysis on Medical Devices Quality Control." In Communications in Computer and Information Science, 182–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22729-5_16.

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Dudin, Alexander, Chesoong Kim, and Sergey Dudin. "Optimal Control by the Queue with Rate and Quality of Service Depending on the Amount of Harvested Energy as a Model of the Node of Wireless Sensor Network." In Distributed Computer and Communication Networks, 165–78. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36614-8_13.

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Priyadarshini, Sushree Bibhuprada B. "Concentric Quadrivial Scalar Premier Selection Scheme Based on Sensing Region Segregation (CQSPS-SRS): An Innovative Marching Towards Optimum Camera Actuation and Enhanced Event Coverage in Wireless Multimedia Sensor Networks." In ICICCT 2019 – System Reliability, Quality Control, Safety, Maintenance and Management, 494–501. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8461-5_56.

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Urraca, Ruben, Javier Antonanzas, Andres Sanz-Garcia, Alvaro Aldama, and Francisco Javier Martinez-de-Pison. "An Algorithm Based on Satellite Observations to Quality Control Ground Solar Sensors: Analysis of Spanish Meteorological Networks." In Lecture Notes in Computer Science, 609–21. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92639-1_51.

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Selmic, Rastko R., Vir V. Phoha, and Abdul Serwadda. "Quality of Service." In Wireless Sensor Networks, 179–96. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46769-6_7.

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Challen, Geoffrey, and Matt Welsh. "Volcano Monitoring: Addressing Data Quality Through Iterative Deployment." In Wireless Sensor Networks, 71–113. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-5834-1_4.

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Conference papers on the topic "Sensor networks – Quality control"

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"Enabling Quality Control of Sensor Web Observations." In International Conference on Sensor Networks. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004707200170027.

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Saab, Christine, Isam Shahrour, and Fadi Hage Chehade. "Smart technology for water quality control: Feedback about use of water quality sensors." In 2017 Sensors Networks Smart and Emerging Technologies (SENSET). IEEE, 2017. http://dx.doi.org/10.1109/senset.2017.8125060.

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Huang, Vincent, Richard Carlsson, Qiang Li, and Evan Liu. "System and interfaces for water quality monitoring and control in aquaculture." In 2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP). IEEE, 2011. http://dx.doi.org/10.1109/issnip.2011.6146579.

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Benavoli, Alessio, and Luigi Chisci. "Towards optimal energy-quality tradeoff in tracking via sensor networks." In European Control Conference 2007 (ECC). IEEE, 2007. http://dx.doi.org/10.23919/ecc.2007.7068371.

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Onur, E., C. Ersoy, and H. Delic. "On the quality of deployment in wireless sensor networks." In 2005 Proceedings of the 8th International Conference on Telecommunications. IEEE, 2005. http://dx.doi.org/10.1109/contel.2005.185950.

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Biao Song, Wendong Xiao, and Zhaohui Zhang. "Quality of estimation guaranteed energy efficient sensor selection in wireless sensor networks." In 2014 11th World Congress on Intelligent Control and Automation (WCICA). IEEE, 2014. http://dx.doi.org/10.1109/wcica.2014.7052962.

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Xu, Hongli, Liusheng Huang, Junmin Wu, Gang Wang, and Wang Liu. "Delay-Constraint Topology Control in Wireless Sensor Networks Format." In 5th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness. ICST, 2008. http://dx.doi.org/10.4108/icst.qshine2008.3815.

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He, Liang, Boyang Yu, and Jingdong Xu. "LQATC: Link Quality Assured Topology Control Algorithm in Sensor Networks." In 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2010. http://dx.doi.org/10.1109/wicom.2010.5601387.

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Prathiba, B., K. Jaya Sankar, and V. Sumalatha. "Enhancing the data quality in wireless sensor networks — A review." In 2016 International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT). IEEE, 2016. http://dx.doi.org/10.1109/icacdot.2016.7877626.

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Lei Chen, Boleslaw K. Szymanski, and Joel W. Branch. "Quality-driven congestion control for target tracking in wireless sensor networks." In 2008 5th IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS). IEEE, 2008. http://dx.doi.org/10.1109/mahss.2008.4660115.

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Reports on the topic "Sensor networks – Quality control"

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Kanna, Rajgopal. Enhancing the Quality of Routing (QOR) in DataCentric Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, October 2004. http://dx.doi.org/10.21236/ada427474.

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Aman Behal, Sunil Kumar, and Goodarz Ahmadi. Intelligent Control via Wireless Sensor Networks for Advanced Coal Combustion Systems. Office of Scientific and Technical Information (OSTI), August 2007. http://dx.doi.org/10.2172/934579.

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Magana-Zook, S. A. Dynamic Networks Experiment FY18 - Quality Control Focus Area Efforts. Office of Scientific and Technical Information (OSTI), July 2018. http://dx.doi.org/10.2172/1465301.

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Hansen, Jeffrey, Scott Hissam, B. C. Meyers, Ed Morris, Daniel Plakosh, Soumya Simanta, and Lutz Wrage. Adaptive Flow Control for Enabling Quality of Service in Tactical Ad Hoc Wireless Networks. Fort Belvoir, VA: Defense Technical Information Center, December 2010. http://dx.doi.org/10.21236/ada536719.

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Steigerwalt, Ryan. Quality Control Methodologies for Advanced EMI Sensor Data Acquisition and Anomaly Classification - Former Southwestern Proving Ground, Arkansas. Fort Belvoir, VA: Defense Technical Information Center, July 2015. http://dx.doi.org/10.21236/ada626409.

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Lanzara, Giulia, Lunwei Zhang, and Fu-Kuo Chang. Design of CNT Embedded Adhesive Film for Sensing, Control, and Reinforcement of PZT Actuator/Sensor Networks in Multifunctional Composites During Cure. Fort Belvoir, VA: Defense Technical Information Center, December 2010. http://dx.doi.org/10.21236/ada563591.

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Kyllönen, Katriina, Karri Saarnio, Ulla Makkonen, and Heidi Hellén. Verification of the validity of air quality measurements related to the Directive 2004/107/EC in 2019-2020 (DIRME2019). Finnish Meteorological Institute, 2020. http://dx.doi.org/10.35614/isbn.9789523361256.

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This project summarizes the results from 2000–2020and evaluates the trueness andthequality control (QC) procedures of the ongoing polycyclic aromatic hydrocarbon (PAH)and trace element measurements in Finlandrelating to Air Quality (AQ) Directive 2004/107/EC. The evaluation was focused on benzo(a)pyrene and other PAH compounds as well as arsenic, cadmium and nickel in PM10and deposition. Additionally, it included lead and other metals in PM10and deposition, gaseous mercury and mercury deposition, andbriefly other specificAQ measurements such as volatile organic compounds (VOC)and PM2.5chemical composition. This project was conducted by the National Reference Laboratory on air quality and thiswas the first time these measurements were assessed. A major part of the project was field and laboratory audits of the ongoing PAH and metal measurements. Other measurements were briefly evaluated through interviews and available literature. In addition, the national AQ database, the expertise of local measurement networks and related publications were utilised. In total, all theseven measurement networks performing PAH and metal measurements in 2019–2020took part in the audits. Eleven stations were audited while these measurements are performed at 22 AQ stations in Finland. For the large networks, one station was chosen to represent the performance of the network. The audits included also six laboratories performing the analysis of the collected samples. The audits revealed the compliance of the measurements with the AQ Decree 113/2017, Directive 2004/107/EC and Standards of the European Committee for Standardization(CEN). In addition, general information of the measurements, instruments and quality control procedures were gained. The results of the laboratory audits were confidential,but this report includes general findings, and the measurement networks were informed on the audit results with the permission of the participating laboratories. As a conclusion, the measurementmethodsusedwere mainly reference methods. Currently, all sampling methods were reference methods; however, before 2018 three networks used other methods that may have underestimated concentrations. Regarding these measurements, it should be noted the results are notcomparable with the reference method. Laboratory methods were reference methods excluding two cases, where the first was considered an acceptable equivalent method. For the other, a change to a reference method was strongly recommended and this realized in 2020. For some new measurements, the ongoing QC procedures were not yet fully established, and advice were given. Some networks used consultant for calibration and maintenance, and thus theywere not fully aware of the QC procedures. EN Standards were mostly followed. Main concerns were related to the checks of flow and calculation of measurement uncertainty, and suggestions for improvement were given. When the measurement networks implement the recommendations given inthe audits, it can be concluded that the EN Standards are adequately followed in the networks. In the ongoing sampling, clear factors risking the trueness of the result were not found. This applies also for the laboratory analyses in 2020. One network had concentrations above the target value, and theindicative measurementsshould be updated to fixed measurements.
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