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On crowdsensed data acquisition using multi-dimensional point processes

Saket Sathe, Timos Sellis, Karl Aberer
2015 2015 31st IEEE International Conference on Data Engineering Workshops  
In this paper we propose using multi-dimensional point processes (MDPPs), a mathematical modeling tool that can be effectively used for performing this data acquisition task.  ...  Unlike traditional sensor network data, crowdsensed data has a highly skewed spatio-temporal distribution caused largely due to the mobility of sensors [1].  ...  Before we define multi-dimensional point processes (MDPPs) and discuss how they can be used for acquiring crowdsensed streams, we present two running examples that will be used throughout the paper.  ... 
doi:10.1109/icdew.2015.7129562 dblp:conf/icde/SatheSA15 fatcat:ao4ne7k4tjhszmd3fhaukcnqeq

Detailed author index

2015 2015 31st IEEE International Conference on Data Engineering Workshops  
d On Crowdsensed Data Acquisition Using Multi-Dimensional Point Processes Schuh, Stefan 22 '!:!d AIR: Adaptive Index Replacement in Hadoop Sellis, Timos 124 '!:!  ...  d On Crowdsensed Data Acquisition Using Multi-Dimensional Point Processes She, Jieying 216 m On Bottleneck-Aware Arrangement for Event-Based Social Networks Shen, Zhitao 182 '!:!  ... 
doi:10.1109/icdew.2015.7129529 fatcat:4vkbzbkin5fvhmiibrbqxegjaq

A Survey on Social-Physical Sensing [article]

Md Tahmid Rashid, Na Wei, Dong Wang
2021 arXiv   pre-print
is contriving as a pervasive sensing paradigm that leverages the observations from human participants equipped with portable devices and ubiquitous Internet connectivity (i.e., through social media or crowdsensing  ...  Propelled by versatile data capture, communication, and computing technologies, physical sensing has revolutionized the avenue for spontaneously capturing and interpreting real-world phenomenon.  ...  Data Acquisition Platforms A crucial component of the sensing process in SPS is the data collection.  ... 
arXiv:2104.01360v1 fatcat:b6sag5objzhezcfhscb3ctf2ca

High-precision GPS measurement method without geographical restrictions using crowd-sensing technology

Yunxiang Zhang, Bin Wang, Lei Zhang
2021 Earth Sciences Research Journal  
The performance of the crowdsensing network was improved through a regular hexagon-based crowd-smart big data sensing network deployment mechanism.  ...  measurement method based on Google Earth, indicating that it has significant application value.  ...  The technologies involved include big data storage and processing, data quality management, and multi-modal data mining. (5) Resource optimization of crowd-sensing network.  ... 
doi:10.15446/esrj.v24n4.92151 fatcat:yzsymqazkzdpblyk75p77uxacm

Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives

Alessio Fascista
2022 Sensors  
sensor networks (WSNs), unmanned aerial vehicles (UAVs), and crowdsensing monitoring technologies.  ...  processing techniques, the major pillars at the basis of future integrated (air, land, and water) and large-scale environmental monitoring systems.  ...  Acknowledgments: The author would like to thank Angelo Coluccia for the insightful discussions on the topic and the extensive review of the paper.  ... 
doi:10.3390/s22051824 pmid:35270970 pmcid:PMC8914857 fatcat:xqcgx676mbckfpc2a6rurbfooq

Table of contents

2015 2015 31st IEEE International Conference on Data Engineering Workshops  
Safety Transportation by Means of Using Internet Survey (Masahiro Miyaji) On Crowdsensed Data Acquisition Using Multi-Dimensional Point Processes (Saket Sathe, Timos Sellis, Karl Aberer) Discovering  ...  Dutta) 101 m Farm Biosecurity Hot Spots Prediction Using Big Data Analytics Scalable and Efficient Spatial Data Management on Multi-Core CPU and GPU Clusters: A Preliminary Implementation Based on Impala  ... 
doi:10.1109/icdew.2015.7129527 fatcat:qx6n4vxvfbhqvmoudli5b26ufa

Credibility on Crowdsensing Data Acquisition

Manuel Neto, Danielo Gomes, José Soares
2019 Journal of Communication and Information Systems  
This paper focuses on the credibility of crowd sensed data. The ubiquity of crowdsensing platforms has enabled the capture of sensed information useful for several applications domains.  ...  The results show that the absence of standard models in the data capture process and the human factors such as individualism, inattention, and the possibility of errors (whether they are intentional or  ...  Danielo acknowledges the financial support of the CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico-Brasil, processes #432585/2016-8, #311878/2016-4).  ... 
doi:10.14209/jcis.2019.26 fatcat:o4cja467jbgenap4akpxmcu3ym

Sense-making from Distributed and Mobile Sensing Data

Santanu Sarma, Nalini Venkatasubramanian, Nikil Dutt
2014 Proceedings of the The 51st Annual Design Automation Conference on Design Automation Conference - DAC '14  
sensor data collection, tunable approximate processing, and mobile networking architecture, to create a compressive collaborative mobile crowdsensing platform called SenseDroid.  ...  The proposed framework is build using a multi-tired hierarchical architecture to sense spatial variations of a parameter of interest, perceive spatio-temporal fields, and enable energy efficient local  ...  of the two-dimensional map to transform into a vector where N is the total no of grid points and x[k] represent the sensor measurement at k-th grid point.  ... 
doi:10.1145/2593069.2596688 dblp:conf/dac/SarmaVD14 fatcat:lawbt2bnhvd5nbmv2izjzn6grq

A Survey on Mobile Crowdsensing Systems: Challenges, Solutions and Opportunities

Andrea Capponi, Claudio Fiandrino, Burak Kantarci, Luca Foschini, Dzmitry Kliazovich, Pascal Bouvry
2019 IEEE Communications Surveys and Tutorials  
For data collection, MCS systems rely on contribution from mobile devices of a large number of participants or a crowd.  ...  Mobile crowdsensing (MCS) has gained significant attention in recent years and has become an appealing paradigm for urban sensing.  ...  Multi-dimensional. Typically, applications that require the use of different sensors or multimedia applications produce multidimensional data.  ... 
doi:10.1109/comst.2019.2914030 fatcat:psvt24nrjbcldpixw6b7stzm3a

Key Quality Indicators Prediction for Web Browsing with Embedded Filter Feature Selection

Su Xie, Ke Li, Mingming Xiao, Le Zhang, Wanlin Li
2020 Applied Sciences  
Based on the service perception data crowd-sensed from massive smartphones in the mobile network, we first investigated the application of multi-label ReliefF, a well-known method of feature selection,  ...  in determining the feature weights of the perception data and propose a unified multi-label ReliefF (UML-ReliefF) algorithm.  ...  The general process of the perceptional data acquisition are as follows.  ... 
doi:10.3390/app10062141 fatcat:nymh4437izhntpnuesawmi2n3q

Quality of Information in Mobile Crowdsensing

Francesco Restuccia, Nirnay Ghosh, Shameek Bhattacharjee, Sajal K. Das, Tommaso Melodia
2017 ACM transactions on sensor networks  
For a survey on mobile crowdsensing applications, we refer the reader to [92] .  ...  For example, the cameras on smartphones can be used as video and image sensors [29] , the microphone can be used as an acoustic sensor [39, 154, 206] , and the embedded global positioning system (GPS)  ...  ACKNOWLEDGEMENT We would like to thank the anonymous reviewers for their valuable comments, which helped us improve the quality of the paper.  ... 
doi:10.1145/3139256 fatcat:hgq6lcwmofhy3gpq4auqxuhggu

Space-Air-Ground Integrated Mobile Crowdsensing for Partially Observable Data Collection by Multi-Scale Convolutional Graph Reinforcement Learning

Yixiang Ren, Zhenhui Ye, Guanghua Song, Xiaohong Jiang
2022 Entropy  
Based on multi-source observations from embedded sensors and satellites, an aerial UAV swarm is required to carry out energy-efficient data collection and recharging tasks.  ...  Our ms-SDRGN approach incorporates a multi-scale convolutional encoder to process multi-source raw observations for better feature exploitation.  ...  Thirdly, case '-1GAT' disables one GAT layer and limits the ad-hoc communication to one-hop range, which decreases 0.08 points on CFE score and 530 points on reward.  ... 
doi:10.3390/e24050638 pmid:35626523 pmcid:PMC9140918 fatcat:ol64sxrv65cshaw3ucrtc23l64

Enabling Location-Based Services 2.0: Challenges and Opportunities

Saket Sathe, Roie Melamed, Peter Bak, Shivkumar Kalyanaraman
2014 2014 IEEE 15th International Conference on Mobile Data Management  
Future location-based applications/services will use the data generated by the new mobile devices for providing enhanced user experience. is paper presents a vision of such next-generation location-based  ...  We present the challenges and opportunities that LBS . will pose for mobile data management.  ...  In the future there will be a high demand for model-based data acquisition especially for the crowdsensing applications. III.  ... 
doi:10.1109/mdm.2014.45 dblp:conf/mdm/SatheMBK14 fatcat:23via46c2zb65ixrrb7lznqqrm

IEEE Access Special Section: Intelligent Data Sensing, Collection, and Dissemination in Mobile Computing

Xuxun Liu, Anfeng Liu, John Tadrous, Ligang He, Bo Ji, Zhongming Zheng
2020 IEEE Access  
The article ''Multi-step data prediction in wireless sensor networks based on one-dimensional CNN and bidirectional LSTM,'' by Cheng et al., proposes a new multi-step sensory data prediction model for  ...  The article ''Multi-sensor data fusion based on improved analytic hierarchy process,'' by Deng and Wang, uses multiple criteria factors to measure the degree of conflict between the evidence.  ... 
doi:10.1109/access.2020.3040051 fatcat:kgd4vkzh6bei5c6ckjdxmfygh4

Acting Selfish for the Good of All: Contextual Bandits for Resource-Efficient Transmission of Vehicular Sensor Data [article]

Benjamin Sliwa and Rick Adam and Christian Wietfeld
2020 arXiv   pre-print
as a novel client-based method for resource-efficient opportunistic transmission of delay-tolerant vehicular sensor data.  ...  BS-CB applies a hybrid approach which brings together all major machine learning disciplines - supervised, unsupervised, and reinforcement learning - in order to autonomously schedule vehicular sensor data  ...  Instead of using a multi-dimensional feature vector of raw context measurements for the autonomous decision making, we use an intermediate supervised learning step to forecast the currently achievable  ... 
arXiv:2007.09921v1 fatcat:j5to3mcplfb3fhvliear3uq44y
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