Search results for "Sensor node"

showing 10 items of 33 documents

Reliable diagnostics using wireless sensor networks

2019

International audience; Monitoring activities in industry may require the use of wireless sensor networks, for instance due to difficult access or hostile environment. But it is well known that this type of networks has various limitations like the amount of disposable energy. Indeed, once a sensor node exhausts its resources, it will be dropped from the network, stopping so to forward information about maybe relevant features towards the sink. This will result in broken links and data loss which impacts the diagnostic accuracy at the sink level. It is therefore important to keep the network's monitoring service as long as possible by preserving the energy held by the nodes. As packet trans…

0209 industrial biotechnologyGeneral Computer ScienceComputer science[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]02 engineering and technologyData loss[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]Network topology[SPI.AUTO]Engineering Sciences [physics]/Automatic[INFO.INFO-IU]Computer Science [cs]/Ubiquitous ComputingPrognostics and health management[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringAdaBoostElectroniquebusiness.industryNetwork packetGeneral Engineering[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationWireless sensor networksRandom forest[SPI.TRON]Engineering Sciences [physics]/Electronics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Sensor node020201 artificial intelligence & image processing[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Gradient boosting[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessWireless sensor networkComputer networkComputers in Industry
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Subjective Logic-Based In-Network Data Processing for Trust Management in Collocated and Distributed Wireless Sensor Networks

2018

While analyzing an explosive amount of data collected in today’s wireless sensor networks (WSNs), the redundant information in the sensed data needs to be handled. In-network data processing is a technique which can eliminate or reduce such redundancy, leading to minimized resource consumption. On the other hand, trust management techniques establish trust relationships among nodes and detect unreliable nodes. In this paper, we propose two novel in-network data processing schemes for trust management in static WSNs. The first scheme targets at networks, where sensor nodes are closely collocated to report the same event. Considering both spatial and temporal correlations, this scheme generat…

021110 strategic defence & security studiesComputer scienceNode (networking)Reliability (computer networking)Distributed computing0211 other engineering and technologies020206 networking & telecommunications02 engineering and technologyEnergy consumptionSensor node0202 electrical engineering electronic engineering information engineeringRedundancy (engineering)Trust management (information system)Electrical and Electronic EngineeringSubjective logicInstrumentationWireless sensor networkIEEE Sensors Journal
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Sensor Mining for User Behavior Profiling in Intelligent Environments

2011

The proposed system exploits sensor mining methodologies to profile user behaviors patterns in an intelligent workplace. The work is based in the assumption that users’ habit profiles are implicitly described by sensory data, which explicitly show the consequences of users’ actions over the environment state. Sensor data are analyzed in order to infer relationships of interest between environmental variables and the user, detecting in this way behavior profiles. The system is designed for a workplace equipped in the context of Sensor9k, a project carried out at the Department of Computer Science of Palermo University.

Ambient intelligenceExploitAmbient IntelligenceComputer scienceSensor nodeProfiling (information science)Sensor Data MiningData miningcomputer.software_genrecomputer
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Sensor Node Network for Remote Moisture Measurement in Timber Based on Bluetooth Low Energy and Web-Based Monitoring System

2021

This paper proposes an IoT system based on wireless BLE connectivity to monitor the moisture content of wood, using a compact and low-cost moisture device that relies on a resistance measurement method valid for an ultra-wide range of resistance values. This device is digitally controlled with a BLE-incorporated micro-controller characterized by its small size and low power consumption, providing long-life battery. The proposed system consists of two main parts: first, the BLE moisture device including the moisture content measurement and wireless capability (BLE)

Battery (electricity)IoTComputer scienceReal-time computingCloud computingwood moisture sensorcloud server02 engineering and technologylcsh:Chemical technologyBiochemistryArticleAnalytical ChemistryMoisture measurement0202 electrical engineering electronic engineering information engineeringWirelessWeb applicationlcsh:TP1-1185Electrical and Electronic EngineeringWood industryInstrumentationWater contentInternetMoisturebusiness.industry020206 networking & telecommunicationsXarxes locals sense fil Wi-Fiweb applicationmoisture estimationAtomic and Molecular Physics and OpticsVisualizationIoT networkSensor nodeBLE020201 artificial intelligence & image processingSoCbusiness
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Self-Powered IoT Device for Indoor Applications

2018

This paper presents a proof of concept for selfpowered Internet of Things (IoT) device, which is maintenance free and completely self-sustainable through energy harvesting. These IoT devices can be deployed in large scale and placed anywhere as long as they are in range of a gateway, and as long as there is sufficient light levels for the solar panel, such as indoor lights. A complete IoT device is designed, prototyped and tested. The IoT device can potentially last for more than 5 months (transmission interval of 30 seconds) on the coin cell battery (capacity of 120mAh) without any energy harvesting, sufficiently long for the dark seasons of the year. The sensor node contains ultra-low pow…

Battery (electricity)business.industryComputer science020209 energy020208 electrical & electronic engineeringElectrical engineering02 engineering and technologyTransmission (telecommunications)Proof of conceptSensor nodeDefault gateway0202 electrical engineering electronic engineering information engineeringWirelessbusinessWireless sensor networkEnergy harvesting2018 31st International Conference on VLSI Design and 2018 17th International Conference on Embedded Systems (VLSID)
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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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A Battery-Free Smart Sensor Powered with RF Energy

2018

The development of Internet of Things (IoT) infrastructure and applications is stimulating advanced and innovative ideas and solutions, some of which are pushing the limits of state-of-the-art technology. The increasing demand for Wireless Sensor Network (WSN) that must be capable of collecting and sharing data wirelessly while often positioned in places hard to reach and service, motivates engineers to look for innovative energy harvesting and wireless power transfer solutions to implement battery-free sensor nodes. Due to the pervasiveness of RF (Radio Frequency) energy, RF harvesting that can reach out-of-sight places could be a key technology to wirelessly power IoT sensor devices, whic…

Computer Networks and CommunicationsComputer scienceInternet of ThingsEnergy Engineering and Power TechnologyRadio Frequency HarvestingIndustrial and Manufacturing EngineeringArtificial IntelligenceWireless Battery ChargerWirelessRenewable EnergyWireless power transferInstrumentationSustainability and the Environmentbusiness.industryRF power amplifierTransmitterElectrical engineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionInternet of Things; Litium Ion Battery; Radio Frequency Harvesting; Wireless Battery Charger; Wireless Power Transfer; Wireless Sensor Networks; Artificial Intelligence; Computer Networks and Communications; Computer Science Applications1707 Computer Vision and Pattern Recognition; Energy Engineering and Power Technology; Renewable Energy Sustainability and the Environment; Industrial and Manufacturing Engineering; InstrumentationSensor nodeLitium Ion BatteryWireless Power TransferRadio frequencyInternet of ThingWireless Sensor NetworksbusinessEnergy harvestingWireless sensor network2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI)
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A new autonomous data transmission reduction method for wireless sensors networks

2018

International audience; The inherent limitation in energy resources and computational power for sensor nodes in a Wireless Sensor Network, poses the challenge of extending the lifetime of these networks. Since radio communication is the dominant energy consuming activity, most presented approaches focused on reducing the number of data transmitted to the central workstation. This can be achieved by deploying both on the workstation and the sensor node a synchronized prediction model capable of forecasting future values. Thus, enabling the sensor node to transmit only the values that surpasses a predefined error threshold. This mechanism offers a decrease in the cost of transmission energy f…

Computer sciencebusiness.industryReal-time computing020206 networking & telecommunications[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technology[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation7. Clean energy[INFO.INFO-IU]Computer Science [cs]/Ubiquitous ComputingReduction (complexity)[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]Transmission (telecommunications)[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]020204 information systemsSensor node0202 electrical engineering electronic engineering information engineeringWireless[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessWireless sensor networkEnergy (signal processing)Data transmissionData reduction2018 IEEE Middle East and North Africa Communications Conference (MENACOMM)
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LoRa-Based Sensor Node Energy Consumption with Data Compression

2021

In this paper simple temporal compression algorithms' efficiency to reduce LoRa-based sensor node energy consumption has been evaluated and measured. It is known that radio transmission is the most energy consuming operation in a wireless sensor node. In this paper three lightweight compression algorithms are implemented in an embedded LoRa platform to compress sensor data in on-line mode and the overall energy consumption is measured. Energy consumption is compared to the situation without implementing any compression algorithm. The results show that a simple compression algorithm is an effective method to improve the battery powered sensor node lifetime. Despite the radio transmission's h…

Consumption (economics)Battery (electricity)Computer sciencebusiness.industrySensor nodeReal-time computingWirelessEnergy consumptionbusinessComputer Science::Operating SystemsWireless sensor networkEnergy (signal processing)Data compression2021 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT)
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Knowledge Extraction from Environmental Data Through a Cognitive Architecture

2008

Wireless Sensor Networks represent a novel technology which is expected to experience a dramatic diffusion thanks to the promise to be a pervasive sensory means; however, one of the issues limiting their potential growth relies in the difficulty of managing and interpreting huge amounts of collected data. This paper proposes a cognitive architecture for the extraction of high-level knowledge from raw data through the representation of processed data in opportune conceptual spaces. The presented framework interposes a conceptual layer between the subsymbolic one, devoted to sensory data processing, and the symbolic one, aimed at describing the environment by means of a high level language. T…

Data processingKnowledge extractionComputer scienceSensor nodeknowledge extraction cognitive architectureCognitive architectureCognitive networkRaw dataWireless sensor networkData scienceEnvironmental data
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