Results 171 to 180 of about 5,841 (261)

Enhanced YOLOv8 for efficient road damage detection with spatial-channel reconstruction and multi-scale attention. [PDF]

Sci Rep
Tang Z, Wang H, Chamchong R.
europepmc   +1 more source

E-commerce recommender system design based on web information extraction and sentiment analysis. [PDF]

PLoS One
Feng J.
europepmc   +1 more source

HyAR-PPO: Hybrid Action Representation Learning for Incentive-Driven Task Offloading in Vehicular Edge Computing. [PDF]

Sensors (Basel)
Wang W, Li M, Wu H.
europepmc   +1 more source

Jump-start crowdsensing: A three-layer incentive framework for mobile crowdsensing

2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS), 2017
In the past decade, with the rapid development of wireless communication and sensor technology, ubiquitous smartphones equipped with increasingly rich sensors have more powerful computing and sensing abilities. Thus, mobile crowdsensing has received extensive attentions from both industry and academia.
Yatong Chen 0001, Huangxun Chen, Shuo Yang 0001, Xiaofeng Gao 0001, Fan Wu 0006   +4 more
openaire   +2 more sources

A Survey of Mobile Crowdsensing Techniques

ACM Transactions on Cyber-Physical Systems, 2018
Mobile crowdsensing serves as a critical building block for emerging Internet of Things (IoT) applications. However, the sensing devices continuously generate a large amount of data, which consumes much resources (e.g., bandwidth, energy, and storage ...
Jinwei Liu, Haiying Shen, Husnu S Narman   +2 more
exaly   +2 more sources

Deep Reinforcement Scheduling for Mobile Crowdsensing in Fog Computing

ACM Transactions on Internet Technology, 2019
application/pdfMobile crowdsensing becomes a promising technology for the emerging Internet of Things (IoT) applications in smart environments. Fog computing is enabling a new breed of IoT services, which is also a new opportunity for mobile crowdsensing.
He Li, Kaoru Ota, Mianxiong Dong
exaly   +3 more sources

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When Crowdsensing Meets Smart Cities: A Comprehensive Survey and New Perspectives

IEEE Communications Surveys and Tutorials
Crowdsensing has received widespread attention in recent years. It is extensively employed in smart cities and intelligent transportation systems. This paper comprehensively surveys the latest research advancements in crowdsensing for smart cities from a
VÍCTOR C M Leung, Daxin Tian, Yuan Zhuang   +2 more
exaly   +2 more sources

Mobile Crowdsensing with Imagery Tasks

IEEE/WIC/ACM International Conference on Web Intelligence, 2021
The amount of gadgets connected to the internet has grown rapidly in the recent years. These human owned devices can potentially be used to gather sensor data without active involvement of their owners.
Justas Dautaras, Mihhail Matskin
openaire   +2 more sources

An Ordered Submodularity-Based Budget-Feasible Mechanism for Opportunistic Mobile Crowdsensing Task Allocation and Pricing

IEEE Transactions on Mobile Computing
Mobile crowdsensing services are divided into two categories: opportunistic and participatory. In opportunistic mobile crowdsensing services, users do not need to specify the crowdsensing tasks to be completed.
Jixian Zhang, Hao Wu, Weidong Li
exaly   +2 more sources

A blockchain-based location privacy-preserving crowdsensing system

Future Generation Computer Systems, 2019
© 2018 Elsevier B.V. With the support of portable electronic devices and crowdsensing, a new class of mobile applications based on the Internet of Things (IoT) application is emerging.
Mengmeng Yang, Tianqing Zhu, Kaitai Liang   +2 more
exaly   +4 more sources