Filters








1,909 Hits in 6.7 sec

An energy-saving framework for mobile devices based on crowdsourcing intelligences

Guangtai Liang, Shaochun Li
2015 Proceedings of the 3rd International Workshop on Mobile Development Lifecycle - MobileDeLi 2015  
To guarantee good experiences of mobile users, we propose an energy-saving framework for mobile devices, which uses a set of coarse-grained and general-purpose energy-waste heuristics as a starting point  ...  and then smartly takes advantages of crowdsourcing intelligence to refine energywaste related knowledge to help detect/resolve energy wastes in mobile devices.  ...  To address this problem, we propose a general-purpose energy-saving framework for mobile devices based on crowdsourcing intelligence.  ... 
doi:10.1145/2846661.2846665 dblp:conf/oopsla/LiangL15 fatcat:qun2lc4eofaiffdqaeicvdd6fu

Towards Crowdsourcing Internet of Things (Crowd-IoT): Architectures, Security and Applications

Kenneth Li Minn Ang, Jasmine Kah Phooi Seng, Ericmoore Ngharamike
2022 Future Internet  
Crowdsourcing can play an important role in the Internet of Things (IoT) applications for information sensing and gathering where the participants are equipped with geolocated devices.  ...  Mobile crowdsourcing can be seen as a new paradigm contributing to the development of the IoT.  ...  The authors presented AnonySense, a general architecture focusing on privacy-aware mobile crowdsourcing.  ... 
doi:10.3390/fi14020049 fatcat:o62tjaayyvfnjc75irzkpzu5vy

A Review of Mobile Crowdsourcing Architectures and Challenges: Toward Crowd-Empowered Internet-of-Things

Jurairat Phuttharak, Seng W. Loke
2019 IEEE Access  
We present a taxonomy based on the key issues in mobile crowdsourcing and discuss the different approaches applied to these issues.  ...  Crowdsourcing using mobile devices, known as mobile crowdsourcing, is a powerful approach incorporating human wisdom into mobile computations to solve problems while exploiting the advantages of mobility  ...  It contains various sensing devices based on the power of user devices including mobile phones, wearable devices, smart vehicles and so on.  ... 
doi:10.1109/access.2018.2885353 fatcat:vtfbb7ydjre2rfkulrjm6ypyma

Crowdsourcing with Smartphones

Georgios Chatzimilioudis, Andreas Konstantinidis, Christos Laoudias, Demetrios Zeinalipour-Yazti
2012 IEEE Internet Computing  
interaction by ef ciently calculating the k nearest neighbors for each user at all times; (iii) SmartP2P optimizes energy, time and recall of search in a mobile social community for objects generated  ...  We show how these applications can be deployed on SmartLab, a novel cloud of 40+ Android devices deployed at University of Cyprus, providing an open testbed that facilitates research and development of  ...  The Crowdcast framework [10] is proposed to answer such CAkNN queries ef ciently based on the crowdsourcing of user locations (see Figure 3 ).  ... 
doi:10.1109/mic.2012.70 fatcat:glqmkflnhvhibgyh6sbvqbsraq

Mobile Crowd Sensing and Computing

Bin Guo, Zhu Wang, Zhiwen Yu, Yu Wang, Neil Y. Yen, Runhe Huang, Xingshe Zhou
2015 ACM Computing Surveys  
This article characterizes the unique features and novel application areas of MCSC and proposes a reference framework for building human-in-the-loop MCSC systems.  ...  MCSC extends the vision of participatory sensing by leveraging both participatory sensory data from mobile devices (offline) and user-contributed data from mobile social networking services (online).  ...  ACKNOWLEDGMENTS The authors would like to thank all the colleagues for their discussion and suggestions.  ... 
doi:10.1145/2794400 fatcat:lol35ouj75eplapvdod5kyy2me

Special Issue on Artificial-Intelligence-Powered Edge Computing for Internet of Things

Lei Yang, Xu Chen, Samir M. Perlaza, Junshan Zhang
2020 IEEE Internet of Things Journal  
of edge devices for crowdsourced mobile-edge caching and sharing.  ...  a random forest-based method and an edge-PLCs selection method to save the deployment cost.  ... 
doi:10.1109/jiot.2020.3019948 fatcat:mogalqnhnnaqpbxb7zivzdhvry

Deep Learning for Mobile Crowdsourcing Techniques, Methods, and Challenges: A Survey

Bingchen Liu, Weiyi Zhong, Jushi Xie, Lingzhen Kong, Yihong Yang, Chuang Lin, Hao Wang
2021 Mobile Information Systems  
In view of this, we review the current research status of deep learning for mobile crowdsourcing from the perspectives of techniques, methods, and challenges.  ...  However, the complexity of a mobile crowdsourcing task makes it hard to pursue an optimal resolution with limited computing resources, as well as various task constraints.  ...  It involves crowdsourcing activities on smart phones or other mobile devices.  ... 
doi:10.1155/2021/6673094 doaj:526bd22b22354287b58ac08179088be1 fatcat:gotbqx6tmvglxmciyhmxezlvfq

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 ''Mobile intelligent computing in Internet of Things: An optimized data gathering method based on compressive sensing,'' by Sun et al., proposes a mobile intelligent computing based on compressive  ...  The article ''An energy-efficient multi-ring-based routing scheme for WSNs,'' by He et al., proposes a novel scheme named Energy-efficient Routing Scheme, based on Multi-Ring (ERSMR).  ... 
doi:10.1109/access.2020.3040051 fatcat:kgd4vkzh6bei5c6ckjdxmfygh4

Guest editors' introduction: IT in Smart Cities

Robert R. Harmon, Bin Guo, Maria R. Lee
2016 IT Professional Magazine  
4 Crowdsensing seeks to improve sensing quality on mobile devices by promoting user participation and validation of collected data.  ...  Geo-conquesting is often used when a new brand is trying to compete with an established one. The study presented has important implications for digital advertising in smart cities.  ... 
doi:10.1109/mitp.2016.63 fatcat:nv7vfunzj5cxtoz32cfzd2lpqy

Leveraging Intelligent Transportation Systems and Smart Vehicles Using Crowdsourcing: An Overview

Michael C. Lucic, Xiangpeng Wan, Hakim Ghazzai, Yehia Massoud
2020 Smart Cities  
techniques and technologies on specific crowdsourcing-based ITS systems.  ...  Intelligent Transportation Systems (ITS) and Vehicular Social Networks (VSN) can be leveraged by mobile, spatial, and passive sensing crowdsourcing techniques due to improved connectivity, higher throughput  ...  The authors of [37] developed an automated assignment system for mobile crowdsourcing frameworks based on relationship metrics, and network service parameters.  ... 
doi:10.3390/smartcities3020018 fatcat:dg57ehkvurbpdahp6wvuabk6xm

Crowd Intelligence for Sustainable Futuristic Intelligent Transportation System: A Review

Rathin Shit
2020 IET Intelligent Transport Systems  
The crowd-intelligence-based mobility, traffic control, traffic prediction, parking solutions have been discussed in this survey.  ...  In this study, a survey is conducted considering crowd-intelligence techniques for the transportation system.  ...  [122] proposed a framework based on the crowd-sensing model to overcome this challenge. The authors used crowdsource-based violation report for traffic regulation.  ... 
doi:10.1049/iet-its.2019.0321 fatcat:2krdzlefdndbxfx3uhlzexhps4

Cloud-based crowd sensing: a framework for location-based crowd analyzer and advisor

K C Aishwarya, A Nambi, S Hudson, R K Nadesh
2017 IOP Conference Series: Materials Science and Engineering  
Mobile Cloud Computing is the inheritance of this concept towards mobile handheld devices.  ...  Crowdsensing, or to be precise, Mobile Crowdsensing is the process of sharing resources from an available group of mobile handheld devices that support sharing of different resources such as data, memory  ...  A requester is the client and the crowdsource is the server. The framework also uses human intelligence as a support to the mobile devices. Zhang, Xinglin, et al.  ... 
doi:10.1088/1757-899x/263/4/042076 fatcat:bvmyj6flmndmjhbkz3kvqccr54

Blockchain-Based Crowdsourcing Makes Training Dataset of Machine Learning No Longer Be in Short Supply

Haitao Xu, Wei Wei, Yong Qi, Saiyu Qi, Alireza Souri
2022 Wireless Communications and Mobile Computing  
Crowdsourcing systems based on mobile computing seem to address the bottlenecks faced by machine learning due to their unique advantages; i.e., crowdsourcing can make professional and nonprofessional participate  ...  In this paper, we review studies applying mobile crowdsourcing to training dataset collection and annotation.  ...  In addition, crowdsourcing in mobile computing domain is named mobile crowdsourcing (MCS). In particular, MCS systems dedicate to collecting data with sensors embedded on mobile devices.  ... 
doi:10.1155/2022/7033626 fatcat:6xc6wsi7ynaxnfhk2popfhxsma

Harnessing the Power of the General Public for Crowdsourced Business Intelligence: A Survey

Bin Guo, Yan Liu, Yi Ouyang, Vincent W. Zheng, Daqing Zhang, Zhiwen Yu
2019 IEEE Access  
This paper first characterizes the concept model and unique features and presents a generic framework for CrowdBI.  ...  Compared with the traditional business intelligence that is based on the firm-owned data and survey data, CrowdBI faces numerous unique issues, such as customer behavior analysis, brand tracking, and product  ...  [91] aim to use infrastructure sensors, and wearable/mobile devices to detect customers' in-store behaviors in an energy-efficient manner.  ... 
doi:10.1109/access.2019.2901027 fatcat:a5vz6vl7urckpdsreplkvjalea

Enhancing Mobile App User Understanding and Marketing with Heterogeneous Crowdsourced Data: A Review

Bin Guo, Yi Ouyang, Tong Guo, Longbing Cao, Zhiwen Yu
2019 IEEE Access  
Finally, an evolvable app ecosystem architecture based on heterogeneous crowdsourced data is presented.  ...  This paper reviews CrowdApp, a research field that leverages heterogeneous crowdsourced data for mobile app user understanding and marketing.  ...  To save the energy consumption for the task of predicting app usage, Liao et al. [68] propose a temporal-based app predictor to dynamically predict the apps that are most likely to be used.  ... 
doi:10.1109/access.2019.2918325 fatcat:de763kc4qbdy5ijo55jxyhzgt4
« Previous Showing results 1 — 15 out of 1,909 results