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Evidence of spatial embedding in the IPv4 router-level Internet network [article]

Joshua Parker, Arnold Boedihardjo
2014 arXiv   pre-print
We discuss these results in context of the recently proposed gravity models of the Internet, as well as the potential application to geolocation inferrence.  ...  In this work, we use node subgraph summary statistics to present evidence that the router-level (IPv4) network is spatially embedded, with the similarity (or dissimilarity) of a node from it's neighbor  ...  ACKNOWLEDGMENT The authors would like to thank Alexander Yale-Loehr, Sean Sovine, Harland Yu, Crystal Chen, Raimundo Dos Santos, and Nicole Wayant for their questions and comments during the process of  ... 
arXiv:1410.3340v1 fatcat:ljo7x5tmubbjldnsiojllfohoe

Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools [article]

Weiwei Jiang, Jiayun Luo
2021 arXiv   pre-print
Combined with this trend, this study presents an up-to-date survey of open data and big data tools used for traffic estimation and prediction.  ...  To further promote the use of big data for traffic estimation and prediction tasks, challenges and future directions are given for future studies.  ...  The volume stands for huge amount of data with unknown value coming from mobile devices, social media, the Internet of Things (IoT) and more.  ... 
arXiv:2103.11824v1 fatcat:tfupirrbavdgdgmqkzozvqnkpm

Multi-Modal Pedestrian Trajectory Prediction for Edge Agents Based on Spatial-Temporal Graph

Zou Xiangyu, Bin Sun, Zhao Duan, Zhu Zongwei, Jinjin Zhao, Yongxin He
2020 IEEE Access  
for common training, so as to generate reasonable pedestrian future trajectory distributions based on rich mixed features.  ...  Then, we capture the relative importance of global interactions on pedestrian trajectories through scaled dot product attention, and use recurrent sequence modeling and generative adversarial network architecture  ...  His current research interests include trajectory prediction, the Internet of Things, artificial intelligence, and edge computing.  ... 
doi:10.1109/access.2020.2991435 fatcat:6h64gmyyvvd2pbvzav3lqkdzzm

Grazing trajectory statistics and visualization platform based on cloud GIS

Dong Li, Chuanjian Wang, Qilei Wang, Tianying Yan, Wanlong Bing, Ju Wang
2020 Journal of Cloud Computing: Advances, Systems and Applications  
When users use the functions of spatial analysis (such as buffer analysis, finding hot pots analysis and interpolation point analysis), they can choose to analyze spatial data and related field information  ...  In particular, the trajectory processing service on the server was used to calculate walking speed, walking trajectory and feed intake of the herd in the platform.  ...  Acknowledgements We highly appreciate the Yang Yonglin of the Xinjiang Academy of Agricultural Reclamation and the pastoralists of Ziniquan farm, who participated in the GPS tra-jectory data collection  ... 
doi:10.1186/s13677-020-00184-9 fatcat:heiyzmpmqngmnhlmsph4yfgika

From earth observation to human observation: Geocomputation for social science

Deren Li, Wei Guo, Xiaomeng Chang, Xi Li
2020 Journal of Geographical Sciences  
Driven by the availability of spatially and temporally expansive big data, geocomputation for social science uses spatiotemporal statistical analyses to detect and analyze the interactions between human  ...  In this context, geography, with the human-nature relationship as its core, is undergoing a transition from strictly earth observations to the observation of human activities.  ...  It also promotes the leapfrog transformation of spatial analysis methods of modern geography from model-to data-driven.  ... 
doi:10.1007/s11442-020-1725-8 fatcat:es7yawfp6ja4zp4k7tju2oclyu

A Holistic Overview of Anticipatory Learning for the Internet of Moving Things: Research Challenges and Opportunities

Hung Cao, Monica Wachowicz
2020 ISPRS International Journal of Geo-Information  
The proliferation of Internet of Things (IoT) systems has received much attention from the research community, and it has brought many innovations to smart cities, particularly through the Internet of  ...  Moving Things (IoMT).  ...  Table 1 . 1 Overview of Internet of Moving Things (IoMT) research projects.  ... 
doi:10.3390/ijgi9040272 fatcat:l4guim65rjg3hpnzntqwmih3wq

Mobility-Aware Privacy-Preserving Mobile Crowdsourcing

Guoying Qiu, Yulong Shen, Ke Cheng, Lingtong Liu, Shuiguang Zeng
2021 Sensors  
Unfortunately, most of the existing techniques protect the participant's location-privacy according to actual trajectories.  ...  However, these mobile crowdsourcing applications suffer from various inferential attacks based on mobile behavioral factors, such as location semantic, spatiotemporal correlation, etc.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s21072474 pmid:33918353 fatcat:zafskjqzfjdonopwisqyptrmca

EDISON: An Edge-Native Method and Architecture for Distributed Interpolation

Lauri Lovén, Tero Lähderanta, Leena Ruha, Ella Peltonen, Ilkka Launonen, Mikko J. Sillanpää, Jukka Riekki, Susanna Pirttikangas
2021 Sensors  
To address the scaling problem, we propose EDISON: algorithms for distributed learning and inference, and an edge-native architecture for distributing spatio-temporal interpolation models, their computations  ...  This solution is not scalable, as when the spatial and temporal density of sensor data grows, the required transmission bandwidth and computational capacity become unfeasible.  ...  Abbreviations The following abbreviations are used in this manuscript: AP Access point EDISON Edge-native distributed interpolation ES Edge server GP Gaussian process MDPI Multidisciplinary Digital Publishing  ... 
doi:10.3390/s21072279 pmid:33805187 fatcat:osepjuvppbd27i2gsy2r5r7m3a

Inferring Geographical Partitions by Exploiting User Mobility in Urban Area

Feng XIANG, Benxiong HUANG, Lai TU, Duan HU
2014 IEICE transactions on information and systems  
Ubiquitous cell phones can be such a sensor to analyze the social connection and boundaries of geographical regions.  ...  Second, another generative model which is widely used in linguistic context is adopted to explore the functions of regions.  ...  While the traditional IoT (Internet of Things) technology such as wearable sensors, PAN (Personal area network), can be used for sensing human mobility, they are usually limited to small scale applications  ... 
doi:10.1587/transinf.2013thp0013 fatcat:ntijjlusnjehzo6dzh4zsztqty

We hear your activities through Wi-Fi signals

Fang-Jing Wu, Gurkan Solmaz
2016 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT)  
We propose a method which infers mobility behaviors in two stages: from Wi-Fi signals to trajectories and from trajectories to the mobility behaviors.  ...  We evaluate the applicability of the proposed approach using the StudentLife dataset which contains Wi-Fi, GPS, and accelerometer measurements collected from smartphones of 49 students within a three-month  ...  The speed of each person is computed over all the GPS trajectories to be able to analyze their correlations with the Wi-Fi signal strengths.  ... 
doi:10.1109/wf-iot.2016.7845478 dblp:conf/wf-iot/WuS16 fatcat:thv2qwuhqndcvfh36sbhq6yd64

LocWeb 2010

Erik Wilde, Susanne Boll, Johannes Schöning
2010 Proceedings of the 3rd International Workshop on Location and the Web - LocWeb '10  
The rapid rise of multi-sensory mobile devices and Internet-enabled "things" equipped with sensors and ubiquitous connectivity opens new possibilities and provides the foundations to capture, share and  ...  The Third International Workshop on Location and the Web (LocWeb 2010) focuses on research and development that targets the intersection of Internet-enabled location-aware and/or located devices, and services  ...  awareness, location as context, connecting with and relating to things based on spatial information. • Sensing and applying user location for ubiquitous applications. • Beyond location -models for user  ... 
doi:10.1145/1899662.1899663 dblp:conf/locweb/WildeBS10 fatcat:xk23sx4ysnfy5h3rj27hytiap4

Real-time Deep Learning at the Edge for Scalable Reliability Modeling of Si-MOSFET Power Electronics Converters

Mohammadreza Baharani, Mehrdad Biglarbegian, Babak Parkhideh, Hamed Tabkhi
2019 IEEE Internet of Things Journal  
This article presents a transformative approach, named Deep Learning Reliability Awareness of Converters at the Edge (Deep RACE), for real-time reliability modeling and prediction of high-frequency MOSFET  ...  The proposed Deep RACE solution has been prototyped and implemented through learning from MOSFET data set provided by NASA.  ...  Acknowledgment The authors would like to thank Energy Production and Infrastructure Center (EPIC), and ECE Department at the University of North Carolina at Charlotte.  ... 
doi:10.1109/jiot.2019.2896174 fatcat:7uszxbl5wre5dnyfnx6h5izlbi

Living with Internet of Things: The Emergence of Embedded Intelligence

Bin Guo, Daqing Zhang, Zhu Wang
2011 2011 International Conference on Internet of Things and 4th International Conference on Cyber, Physical and Social Computing  
With the development of sensing, wireless communication, and Internet technologies, we are now living in a world that is filled with various smart thingsthe Internet of Things.  ...  by mining the digital traces left by people while interacting with Internet of Smart Things.  ...  the collective effect of networked smart things − the Internet of Things.  ... 
doi:10.1109/ithings/cpscom.2011.11 dblp:conf/ithings/GuoZW11 fatcat:fdgg26mbenci7hls7awyprt5ba

Semantic data provisioning and reasoning for the Internet of Things

Altti Ilari Maarala, Xiang Su, Jukka Riekki
2014 2014 International Conference on the Internet of Things (IOT)  
Semantic technologies could facilitate realizing features like interoperability and reasoning for Internet of Things (IoT).  ...  In this paper, we study approaches for delivering semantic data from IoT nodes to distributed reasoning engines and reasoning over such data.  ...  ACKNOWLEDGMENT This work was partly supported by TEKES as part of the Internet of Things program of DIGILE (Finnish Strategic Center for Science, Technology and Innovation in the field of ICT and digital  ... 
doi:10.1109/iot.2014.7030117 dblp:conf/iot/MaaralaSR14 fatcat:fbteetinnfgylaeri72r6sfduq

CT-Mapper: Mapping Sparse Multimodal Cellular Trajectories using a Multilayer Transportation Network [article]

Fereshteh Asgari and Alexis Sultan and Haoyi Xiong and Vincent Gauthier and Mounim El-Yacoubi
2016 arXiv   pre-print
The HMM is unsupervised as the transition and emission probabilities are inferred using respectively the physical transportation properties and the information on the spatial coverage of antenna base stations  ...  One of the main strengths of CT-Mapper is its capability to map noisy sparse cellular multimodal trajectories over a multilayer transportation network where the layers have different physical properties  ...  Transition probability and emission score were modeled based on topological properties of the transportation network and the spatial distribution of antenna base stations.  ... 
arXiv:1604.06577v1 fatcat:6epd2pihlzadpefo72kbbvimui
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