Search results for "Crowdsensing"

showing 4 items of 4 documents

FIRST

2018

Thanks to the collective action of participating smartphone users, mobile crowdsensing allows data collection at a scale and pace that was once impossible. The biggest challenge to overcome in mobile crowdsensing is that participants may exhibit malicious or unreliable behavior, thus compromising the accuracy of the data collection process. Therefore, it becomes imperative to design algorithms to accurately classify between reliable and unreliable sensing reports. To address this crucial issue, we propose a novel Framework for optimizing Information Reliability in Smartphone-based participaTory sensing (FIRST) that leverages mobile trusted participants (MTPs) to securely assess the reliabil…

FOS: Computer and information sciencesComputer Networks and CommunicationsComputer scienceDistributed computingFrameworkCrowdsensing02 engineering and technologyTrustMobileComputer Science - Networking and Internet ArchitectureThe National MapInformation020204 information systems0202 electrical engineering electronic engineering information engineeringAndroid (operating system)ReputationPaceSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniNetworking and Internet Architecture (cs.NI)Data collectionParticipatory sensingInformation quality020206 networking & telecommunicationsQualitySoftware deploymentWireless sensor networkACM Transactions on Sensor Networks
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IncentMe: Effective Mechanism Design to Stimulate Crowdsensing Participants with Uncertain Mobility

2018

Mobile crowdsensing harnesses the sensing power of modern smartphones to collect and analyze data beyond the scale of what was previously possible with traditional sensor networks. Given the participatory nature of mobile crowdsensing, it is imperative to incentivize mobile users to provide sensing services in a timely and reliable manner. Most importantly, given sensed information is often valid for a limited period of time, the capability of smartphone users to execute sensing tasks largely depends on their mobility pattern, which is often uncertain. For this reason, in this paper, we propose IncentMe, a framework that solves this core issue by leveraging game-theoretical reverse auction …

FOS: Computer and information sciencesOptimizationMonitoringComputer Networks and CommunicationsComputer scienceDistributed computingMobile computingCrowdsensing02 engineering and technologyComputer Science - Networking and Internet ArchitectureReverse auctionSmart phoneCrowdsensingGame Theory0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringSensorNetworking and Internet Architecture (cs.NI)Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMechanism designMobile computing020206 networking & telecommunicationsAuctionNavigationCore (game theory)RoadComputer Networks and CommunicationSensingTask analysisTask analysiParticipatoryState (computer science)MechanismSmartphoneWireless sensor networkIncentiveSoftware
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A Fog-Based Application for Human Activity Recognition Using Personal Smart Devices

2019

The diffusion of heterogeneous smart devices capable of capturing and analysing data about users, and/or the environment, has encouraged the growth of novel sensing methodologies. One of the most attractive scenarios in which such devices, such as smartphones, tablet computers, or activity trackers, can be exploited to infer relevant information is human activity recognition (HAR). Even though some simple HAR techniques can be directly implemented on mobile devices, in some cases, such as when complex activities need to be analysed timely, users’ smart devices can operate as part of a more complex architecture. In this article, we propose a multi-device HAR framework that exploits the fog c…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniExploitComputer Networks and CommunicationsComputer sciencebusiness.industryBandwidth (signal processing)Activity tracker020206 networking & telecommunicationsCloud computing02 engineering and technologyActivity recognitionHuman–computer interactionHuman activity recognition mobile crowdsensing fog computing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSmart environmentbusinessMobile deviceWearable technologyACM Transactions on Internet Technology
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SMCP: a Secure Mobile Crowdsensing Protocol for fog-based applications

2020

Abstract The possibility of performing complex data analysis through sets of cooperating personal smart devices has recently encouraged the definition of new distributed computing paradigms. The general idea behind these approaches is to move early analysis towards the edge of the network, while relying on other intermediate (fog) or remote (cloud) devices for computations of increasing complexity. Unfortunately, because both of their distributed nature and high degree of modularity, edge-fog-cloud computing systems are particularly prone to cyber security attacks that can be performed against every element of the infrastructure. In order to address this issue, in this paper we present SMCP…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniModularity (networks)General Computer ScienceExploitEdge devicebusiness.industryComputer scienceDistributed computingHuman Activity RecognitionCyber SecurityCloud computingCryptographic protocolEncryptionlcsh:Q350-390lcsh:QA75.5-76.95Artificial Intelligencelcsh:Information theoryMobile Crowdsensinglcsh:Electronic computers. Computer scienceEnhanced Data Rates for GSM EvolutionbusinessProtocol (object-oriented programming)
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