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Autonomous and distributed recruitment and data collection framework for opportunistic sensing
2013
ACM SIGMOBILE Mobile Computing and Communications Review
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Opportunistic sensing is an approach that dynamically exploits the sensing resources offered by smart phones in order to collect data about a certain area. ...
Participants are not expected to change their behavior in order to provide data to the sensing activity, and may contribute to the sensing only for a short fractions of time. ...
Numerous approaches have been proposed to support people-centric sensing recruitment, however, most of them rely on registries that collect possible candidates for the sensing activities and therefore ...
doi:10.1145/2436196.2436219
fatcat:lthmyxkpqzgnjm2qgulobtt5im
The OPPORTUNITY Framework and Data Processing Ecosystem for Opportunistic Activity and Context Recognition
2012
International Journal of Sensors Wireless Communications and Control
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We present the OPPORTUNITY Framework and Data Processing Ecosystem to recognize human activities or contexts in such opportunistic sensor configurations. ...
We demonstrate OPPORTUNITY on a large-scale dataset collected to exhibit the sensor richness and related characteristics, typical of opportunistic sensing systems. ...
ACKNOWLEDGEMENTS The project OPPORTUNITY acknowledges the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission ...
doi:10.2174/2210327911101020102
fatcat:jb7upf4jkrez7bdhrzgjojpdwu
Mobile crowdsensing with mobile agents
2015
Autonomous Agents and Multi-Agent Systems
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Human mobility patterns, everyday actions and willingness to participate opportunistically extends the data collection and sensing coverage with possibly large numbers of devices [1, 4, 5, 18, 26, 36] ...
Participant devices are then programmed for manual or automatic and context-aware data collection. ...
The participant devices are aware of the sensing context and opportunistic store-carryand-forward method in used data collection: (1) the devices store the collected raw data until a mobile agent migrates ...
doi:10.1007/s10458-015-9311-7
fatcat:mbm4w4hs75h6lfssizcol6tgea
The OPPORTUNITY Framework and Data Processing Ecosystem for Opportunistic Activity and Context Recognition
2012
International Journal of Sensors Wireless Communications and Control
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We present the OPPORTUNITY Framework and Data Processing Ecosystem to recognize human activities or contexts in such opportunistic sensor configurations. ...
We demonstrate OPPORTUNITY on a large-scale dataset collected to exhibit the sensor richness and related characteristics, typical of opportunistic sensing systems. ...
ACKNOWLEDGEMENTS The project OPPORTUNITY acknowledges the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission ...
doi:10.2174/2210328711101020102
fatcat:hrq7dfhi2vbbfd2ejg2m2ejq6e
Cheating-Resilient Incentive Scheme for Mobile Crowdsensing Systems
[article]
2017
arXiv
pre-print
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Therefore, a mechanism is required for the system server to recruit well-behaving users for credible sensing, and to stimulate and reward more contributive users based on sensing truth discovery to further ...
Mobile Crowdsensing is a promising paradigm for ubiquitous sensing, which explores the tremendous data collected by mobile smart devices with prominent spatial-temporal coverage. ...
After receiving an announcement, a user who possessed data collected within ±60 seconds autonomously applied for the task, and then uploaded corresponding report if it was recruited. ...
arXiv:1701.01928v1
fatcat:e45uc2ihdfautaimplcnfp4rfq
Developing Agent-Based Smart Objects for IoT Edge Computing: Mobile Crowdsensing Use Case
[chapter]
2018
Lecture Notes in Computer Science
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This scheme introduces challenges in handling dynamic opportunistic resource availability, due to mobility and unpredicted actions of the participants. ...
Software agents have been exploited to handle the inherent dynamicity in the Internet of Things (IoT) systems, as agents are capable of autonomous, reactive and proactive operation in response to changes ...
This work has been carried out under the framework of INTER-IoT, Research and Innovation action -Horizon 2020 European Project, Grant Agreement #687283, financed by the European Union. ...
doi:10.1007/978-3-030-02738-4_20
fatcat:ai5q4vpnmvfepoodk4avlpe5nu
A Self-Adaptive Behavior-Aware Recruitment Scheme for Participatory Sensing
2015
Sensors
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The scheme is proposed to model the tempo-spatial behavior and data quality rating to select participants for participatory sensing campaign. ...
In the paper, we propose a self-adaptive behavior-aware recruitment scheme for participatory sensing. ...
He is responsible for part of the theoretical analysis and paper check.
Conflicts of Interest The authors declare no conflict of interest. ...
doi:10.3390/s150923361
pmid:26389910
pmcid:PMC4610571
fatcat:sm6hd5v7grfnporvdzuteabrm4
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions and Opportunities
2019
IEEE Communications Surveys and Tutorials
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For data collection, MCS systems rely on contribution from mobile devices of a large number of participants or a crowd. ...
For this reason, MCS frameworks are specifically designed to include incentive mechanisms and address privacy concerns. ...
[7] "opportunistic sensing" is defined as "On the other hand, opportunistic sensing is where the sensing is more autonomous and user involvement is minimal (e.g. continuous location sampling)". ...
doi:10.1109/comst.2019.2914030
fatcat:psvt24nrjbcldpixw6b7stzm3a
Quality-aware user recruitment based on federated learning in mobile crowd sensing
2021
Tsinghua Science and Technology
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However, large-scale data collection may reduce the quality of sensed data. Thus, quality control is a key problem in MCS. ...
of sensed data by 23.5% and 38.8%, respectively. ...
Prediction model for sensing data quality In internet of things networks, wearable devices, autonomous vehicles, or smart homes may contain numerous sensors that allow them to collect large amounts of ...
doi:10.26599/tst.2020.9010046
fatcat:uwanci6pz5avdnyb7stg2tn7jm
Simulation Of Trust-Based Mechanism For Enhancing User Confidence In Mobile Crowdsensing Systems
2020
IEEE Access
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This paper illustrates the establishment of user confidence during recruitment in MCS as it is very critical for the success of MCS systems and proposes a simulation trust-based mechanism (SiTBaM) approach ...
The trust-based scheme of MCS is studied to predict the damage level, the scores of quality-of-service (QoS), and the levels of qualityof-data (QoD) of MCS systems. ...
OPPORTUNISTIC TECHNIQUE In the case of an opportunistic MCS system, the sensor data is acquired autonomously and reported to the cloud periodically without the user involvement [19] . ...
doi:10.1109/access.2020.2968797
fatcat:kegfiusr2bcudifqh2vze4bbd4
Mobile Devices as an Infrastructure: A Survey of Opportunistic Sensing Technology
2015
Journal of Information Processing
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., smartphones), employing powerful capability of such commercial mobile products has become a promising approach for large-scale environmental and human-behavioral sensing. ...
Such a new paradigm of scalable context monitoring is known as opportunistic sensing, and has been successfully applied to a broad range of applications. ...
As with opportunistic sensing, this approach also incurs privacy concern and requires incentive/quality control mechanisms for data collection. ...
doi:10.2197/ipsjjip.23.94
fatcat:rnkekppyjvckvbe7cq5als4suu
A Review of Mobile Crowdsourcing Architectures and Challenges: Toward Crowd-Empowered Internet-of-Things
2019
IEEE Access
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The problems that can be tackled include the use of geographically distributed tasks, and mobile sensing using the collective wisdom of the crowd. ...
However, the implementation of mobile crowdsourcing applications has been found to be challenging to users due to the nature of dynamic sensing, crowd engagement with data distribution, and a process of ...
form selforganized opportunistic networks for data distributing and sharing [37] . ...
doi:10.1109/access.2018.2885353
fatcat:vtfbb7ydjre2rfkulrjm6ypyma
Reputation-Based Incentives for Data Dissemination in Mobile Participatory Sensing Networks
2015
International Journal of Distributed Sensor Networks
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The results show that RIDD remarkably increases the winning probability of participants who disseminate accurate data and reduces the cost for retaining sufficient number of reliable participants. ...
Due to uncertainty of connection, mobile nodes sometimes need encounter opportunities to accomplish data communication and transmission. ...
networking, environmental detection, and traffic monitoring by integrating ubiquitous sensing, large-scale data collection, and cloud computing. ...
doi:10.1155/2015/172130
fatcat:4uoy2575nzdodke6eho4oalqte
Trustworthy opportunistic sensing: A Social Computing Paradigm
2011
2011 IEEE International Conference on Information Reuse & Integration
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We refer to this new era as the Social Computing Paradigm, and we argue that it could be particularly useful in conjunction with opportunistic sensing. ...
Thus, it is possible to create largescale opportunistic networks by integrating sensors, applications and social networks and this development could also promote innovative collaborative cyber security ...
Figure 2 shows the different layers for the envisioned socially aware opportunistic sensing framework. ...
doi:10.1109/iri.2011.6009608
dblp:conf/iri/JohnsonLOW11
fatcat:6ltaztftobb7na272ucrttwu2y
Data Trustworthiness Evaluation in Mobile Crowdsensing Systems with Users' Trust Dispositions' Consideration
2019
Sensors
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Mobile crowdsensing is a powerful paradigm that exploits the advanced sensing capabilities and ubiquity of smartphones in order to collect and analyze data on a scale that is impossible with fixed sensor ...
subjective data besides the raw sensing data generated by their smart devices. ...
Discussion and Use Cases The proposed framework assumes that an application uses both opportunistic and participatory sensing approaches for collecting data. ...
doi:10.3390/s19061326
fatcat:327qhd23mzbnzofihma4ghviiq
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