Search results for "Sensor Networks"

showing 10 items of 174 documents

Quantification of cortical proprioceptive processing through a wireless and miniaturized EEG amplifier.

2022

Corticokinematic coherence (CKC) is computed between limb kinematics and cortical activity (e.g. MEG, EEG), and it can be used to detect, quantify and localize the cortical processing of proprioceptive afference arising from the body. EEG-based studies on CKC have been limited to lab environments due to bulky, non-portable instrumentations. We recently proposed a wireless and miniaturized EEG acquisition system aimed at enabling EEG studies outside the laboratory. The purpose of this work is to compare the EEG-based CKC values obtained with this device with a conventional wired-EEG acquisition system to validate its use in the quantification of cortical proprioceptive processing. Eleven hea…

AdultMaleMovementlangaton tekniikkaYoung AdultmittauslaitteetElectronicHumansEEGwireless sensor networkslaboratoriesrecordingAmplifiers ElectronicsensoriverkotMagnetoencephalographyElectroencephalographylaboratoriotwireless communicationProprioceptionAmplifiersperformance evaluationaivokuoriAdult; Amplifiers; Electronic; Electroencephalography; Female; Humans; Magnetoencephalography; Male; Movement; Proprioception; Young Adultharmonic analysisFemaleelectroencephalographyAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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A reliable CSMA protocol for high performance broadcast communications in a WSN

2014

Wireless Sensor Networks have been identified as a promising technology to efficiently perform distributed monitoring, tracking and control tasks. In order to accomplish them, since fast decisions are generally required, high values of throughput must be obtained. Additionally, a high packet reception rate is important to avoid wasting energy due to unsuccessful transmissions. These communication requirements are more easily satisfied by exploiting the broadcast nature of the wireless medium, which allows several simultaneous receptions through a unique node transmission. We propose a Medium Access Control protocol that ensures, simultaneously, high values of throughput and a high packet re…

Atomic broadcastKey distribution in wireless sensor networksbusiness.industryComputer scienceNode (networking)Media access controlWirelessThroughputBroadcastingbusinessBroadcast radiationWireless sensor networkComputer network2014 IEEE Global Communications Conference
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On the feasibility of personal audio systems over a network of distributed loudspeakers

2018

Los sistemas de reproducción de audio personal se ocupan de la creación de zonas sonoras personales dentro de una habitación sin necesidad de utilizar auriculares. Estos sistemas utilizan un conjunto de altavoces y diseñan los filtros necesarios en cada altavoz con el fin de que la señal de audio deseada llegue a cada persona en la sala lo más libre de interferencias posible. Existen propuestas muy interesantes en la literatura que hacen uso de arrays circulares o lineales, pero en este trabajo estudiamos el problema considerando una red de altavoces distribuidos controlados por un conjunto de nodos acústicos, que pueden intercambiar información a través de una red. Enunciamos el modelo de …

Audio signalbusiness.product_category:CIENCIAS TECNOLÓGICAS [UNESCO]MicrophoneComputer scienceAcoustics020206 networking & telecommunications02 engineering and technologypersonal audio systemsUNESCO::CIENCIAS TECNOLÓGICASGeneralLiterature_MISCELLANEOUSSignal-to-noise ratioSound reinforcement system0202 electrical engineering electronic engineering information engineeringElectronic engineering020201 artificial intelligence & image processingLoudspeakerDirectional soundwireless acoustic sensor networksbusinessHeadphones
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Multimode WSN: Improving Robustness, Fault Tolerance and Performance of Randomly Deployed Wireless Sensor Network

2010

This paper proposes an advanced, robust and flexible solution that applies the (revised) concept of Always Best Connected (ABC) Network, typical of multimode modern mobile devices, to Wireless Sensor Network. Hostile environments and unpredictable conditions (e.g. interferences) can negatively affect communication range, potentially increasing the number of unconnected nodes in random deployments. Multimode Wireless Sensor Network (MM-WSN) is provided with an adaptive mechanism for environmental condition evaluation and with the ability of self-configuring itself for optimal networking independence of detected conditions. Proposed solution is based on advanced smart nodes provided with mult…

Base stationKey distribution in wireless sensor networksWireless ad hoc networkRobustness (computer science)business.industryComputer scienceDistributed computingMobile wireless sensor networkWirelessNetwork performancebusinessWireless sensor networkComputer network2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks
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Predicting the Batteries' State of Health in Wireless Sensor Networks Applications

2018

[EN] The lifetime of wireless sensor networks deployments depends strongly on the nodes battery state of health (SoH). It is important to detect promptly those motes whose batteries are affected and degraded by ageing, environmental conditions, failures, etc. There are several parameters that can provide significant information of the battery SoH, such as the number of charge/discharge cycles, the internal resistance, voltage, drained current, temperature, etc. The combination of these parameters can be used to generate analytical models capable of predicting the battery SoH. The generation of these models needs a previous process to collect dense data traces with sampled values of the batt…

Battery (electricity)EnergyState of healthComputer science020209 energyProcess (computing)Battery02 engineering and technologyInternal resistanceWireless sensor networksReliability engineeringState of health (SoH)TECNOLOGIA ELECTRONICAMicrocontrollerHardware_GENERALControl and Systems EngineeringModels0202 electrical engineering electronic engineering information engineeringComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMSElectrical and Electronic EngineeringMicrocontrollersWireless sensor networkVoltage
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A method for modeling the battery state of charge in wireless sensor networks

2015

In this paper we propose a method for obtaining an analytic model of the battery State-of-Charge (SoC) in wireless sensor nodes. The objective is to find simple models that can be used to estimate accurately the real battery state and consequently the node lifetime. Running the model in the network nodes, we can provide the motes with the required information to implement applications that can be considered as battery-aware. The proposed methodology reduces the computational complexity of the model avoiding complicated electrochemical simulations and treating the battery as an unknown system with an output that can be predicted using simple mathematical models. At a first stage, during a se…

Battery (electricity)EngineeringEnergyMathematical modelbusiness.industryNode (networking)Real-time computingWireless sensor networksTECNOLOGIA ELECTRONICAKey distribution in wireless sensor networksMultilayer perceptronComputer Science::Networking and Internet ArchitectureElectronic engineeringMobile wireless sensor networkBatteries State-of-ChargeWirelessBatteries modelingElectrical and Electronic EngineeringbusinessInstrumentationWireless sensor network
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An over-the-distance wireless battery charger based on RF energy harvesting

2017

An RF powered receiver silicon IC (integrated circuit) for RF energy harvesting is presented as wireless battery charger. This includes an RF-to-DC energy converter specifically designed with a sensitivity of -18.8 dBm and an energy conversion efficiency of ∼45% at 900 MHz with a transmitting power of 0.5 W in free space. Experimental results concerned with remotely battery charging using a complete prototype working in realistic scenarios will be shown.

Battery (electricity)EngineeringInternet of Things02 engineering and technologyIntegrated circuitInternet of Things; Litium Ion Battery; Radio Frequency Harvesting; Wireless Battery Charger; Wireless Sensor Networks; Hardware and Architecture; Electrical and Electronic Engineering; Modeling and SimulationSettore ING-INF/01 - ElettronicaRadio Frequency Harvestinglaw.inventionBattery chargerlawWireless Battery ChargerHardware_INTEGRATEDCIRCUITS0202 electrical engineering electronic engineering information engineeringElectronic engineeringElectrical and Electronic Engineeringbusiness.industry020208 electrical & electronic engineeringEnergy conversion efficiencyElectrical engineering020206 networking & telecommunicationsHardware and ArchitectureModeling and SimulationLitium Ion BatteryRadio frequencyInternet of ThingWireless Sensor NetworksbusinessEnergy harvestingSensitivity (electronics)Wireless sensor networkWireless Sensor Network2017 14th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD)
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Practical Considerations in the Implementation of Collaborative Beamforming on Wireless Sensor Networks

2017

Wireless Sensor Networks (WSNs) are composed of spatially distributed autonomous sensor devices, named motes. These motes have their own power supply, processing unit, sensors and wireless communications However with many constraints, such as limited energy, bandwidth and computational capabilities. In these networks, at least one mote called a sink, acts as a gateway to connect with other networks. These sensor networks run monitoring applications and then the data gathered by these motes needs to be retrieved by the sink. When this sink is located in the far field, there have been many proposals in the literature based on Collaborative Beamforming (CB), also known as Distributed or Cooper…

BeamformingEngineering02 engineering and technologylcsh:Chemical technologyBiochemistryArticleAnalytical ChemistryDefault gateway0202 electrical engineering electronic engineering information engineeringWirelesslcsh:TP1-1185ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMSElectrical and Electronic Engineeringwireless sensor networksInstrumentationbusiness.industryBandwidth (signal processing)ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKScollaborative beamforming020206 networking & telecommunicationsAtomic and Molecular Physics and OpticsPower (physics)cooperative beamforming020201 artificial intelligence & image processingSink (computing)businessWireless sensor networkdistributed beamformingEnergy (signal processing)Computer networkSensors
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Design and validation of a wireless Body Sensor Network for integrated EEG and HD-sEMG acquisitions

2022

Sensorimotor integration is the process through which the human brain plans the motor program execution according to external sources. Within this context, corticomuscular and corticokinematic coherence analyses are common methods to investigate the mechanism underlying the central control of muscle activation. This requires the synchronous acquisition of several physiological signals, including EEG and sEMG. Nevertheless, physical constraints of the current, mostly wired, technologies limit their application in dynamic and naturalistic contexts. In fact, although many efforts were made in the development of biomedical instrumentation for EEG and High Density-surface EMG (HD-sEMG) signal ac…

Biomedical Engineeringevoked potentialsWireless communicationSynchronizationReceiversBody sensor networkswireless body sensor networkmittauslaitteetInternal MedicineHumansEEGsensorimotor integrationBiopotential acquisition systemsHD-sEMGElectromyographyGeneral NeuroscienceRehabilitationsensoriverkotBrainSignal Processing Computer-AssistedElectroencephalographyelektromyografiahermo-lihastoimintaBiopotential acquisition systems; Body sensor networks; EEG; Electroencephalography; Electromyography; evoked potentials; HD-sEMG; Instruments; Receivers; sensorimotor integration; Synchronization; wireless body sensor network; Wireless communicationInstrumentsWireless Technologylangattomat verkot
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Detecting faulty wireless sensor nodes through Stochastic classification

2011

In many distributed systems, the possibility to adapt the behavior of the involved resources in response to unforeseen failures is an important requirement in order to significantly reduce the costs of management. Autonomous detection of faulty entities, however, is often a challenging task, especially when no direct human intervention is possible, as is the case for many scenarios involving Wireless Sensor Networks (WSNs), which usually operate in inaccessible and hostile environments. This paper presents an unsupervised approach for identifying faulty sensor nodes within a WSN. The proposed algorithm uses a probabilistic approach based on Markov Random Fields, requiring exclusively an ana…

Brooks–Iyengar algorithmComputer scienceDistributed computingReal-time computingProbabilistic logicMarkov processMarkov Random Fieldsymbols.namesakeKey distribution in wireless sensor networksWireless Sensor Networks.Autonomic ComputingSensor nodesymbolsOverhead (computing)Algorithm designWireless sensor network2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)
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