Results 81 to 90 of about 5,841 (261)

Federated Learning Meets Urban Opportunistic Crowdsensing in 6G Networks: Opportunities, Challenges, and Optimization Potentials

IEEE Network
6G networks are envisioned to enable the Internet of Things (IoTs) and foster ubiquitous sensing. Urban opportunistic crowdsensing, which leverages participants carrying mobile sensing units (MSUs) in their daily activities to collect data, enables low ...
Wenjun Zhang, Xiaoli Liu, Chao Zhu, Samu Varjonen, Fangxin Wang, Sasu Tarkoma   +5 more
semanticscholar   +1 more source

Multibridge Inference Structural Health Monitoring (MISHM): A Drive‐By Crowdsensing Approach at the Network Level

Structural Control and Health Monitoring, Volume 2025, Issue 1, 2025.
As aging bridge infrastructure poses increasing safety risks, there is a critical need for reliable and scalable Structural Health Monitoring (SHM) systems. Traditional SHM methods, which rely on fixed sensor networks and assessments of individual bridges, face significant challenges in scalability, cost, and efficiency—particularly in complex urban ...
Jiangyu Zeng, Qipei Mei, Mustafa Gül, Suparno Mukhopadhyay   +3 more
wiley   +1 more source

Mobile Crowdsensing in Software Defined Opportunistic Networks

, 2017
application/pdfMobile crowdsensing is a new paradigm that sharing sensing data collected by mobile devices such as smartphones and tablets. As mobile devices are usually connected by an opportunistic network for data transferring, it is hard to ...
リ, ホ, GUO, Minyi, 李, 鶴, 董, 冕雄, LI, He, オオタ, カオル, DONG, Mianxiong, OTA, Kaoru, 太田, 香, トウ, メンユウ   +9 more
core   +1 more source

Towards System Implementation and Data Analysis for Crowdsensing Based Outdoor RSS Maps

IEEE Access, 2018
With the explosive usage of smart mobile devices, sustainable access to wireless networks (e.g., Wi-Fi) has become a pervasive demand. Most mobile users expect seamless network connection with low cost.
Xiaochen Fan, Xiangjian He, Chaocan Xiang, Deepak Puthal, Liangyi Gong, Priyadarsi Nanda, Gengfa Fang   +6 more
doaj   +1 more source

Blockchain‐based incentive mechanism for environmental, social, and governance disclosure: A principal‐agent perspective

Corporate Social Responsibility and Environmental Management, Volume 31, Issue 6, Page 6318-6334, November 2024.
Abstract Environmental, social, and governance (ESG) disclosure has drawn much attention from listed companies, investors, and regulators. In response to the increasing demand of investors and regulators for non‐financial information, listed companies have paid attention to publishing ESG reports consisting of environmental, social, and governance ...
Yuxiang Niu, Yelin Fu, Xinlai Liu, Arjun Rachana Harish, Ming Li, George Q. Huang   +5 more
wiley   +1 more source

Generative AI for Secure and Privacy-Preserving Mobile Crowdsensing [PDF]

IEEE wireless communications
Recently, generative AI has attracted much attention from both academic and industrial fields, due to its potential especially in data generation and synthesis aspects.
Yaoqi Yang, Bangning Zhang, D. Guo, Hongyang Du, Zehui Xiong, D. Niyato, Zhu Han   +6 more
semanticscholar   +1 more source

Efficient Algorithms for Flexible Sweep Coverage in Crowdsensing

IEEE Access, 2018
Sweep coverage is an important covering technique in mobile crowdsensing, in which users or participants are employed to periodically monitor a set of points of interest (POIs) each with a weight indicating the value of its information to be collected ...
Peihuang Huang, Wenxing Zhu, Kewen Liao, Timos Sellis, Zhiyong Yu, Longkun Guo   +5 more
doaj   +1 more source

Advancements in Q‐learning meta‐heuristic optimization algorithms: A survey

WIREs Data Mining and Knowledge Discovery, Volume 14, Issue 6, November/December 2024.
Future research directions include exploring diverse meta—heuristic integrations, investigating transfer learning strategies, and advancing techniques for state space reduction. Abstract This paper reviews the integration of Q‐learning with meta‐heuristic algorithms (QLMA) over the last 20 years, highlighting its success in solving complex optimization
Yang Yang, Yuchao Gao, Zhe Ding, Jinran Wu, Shaotong Zhang, Feifei Han, Xuelan Qiu, Shangce Gao, You‐Gan Wang   +8 more
wiley   +1 more source

Online Change Detection for Energy-Efficient Mobile Crowdsensing [PDF]

, 2014
Mobile crowdsensing is power hungry since it requires continuously and simultaneously sensing, processing and uploading fused data from various sensor types including motion sensors and environment sensors.
Le Viet Duc, Duc Viet, Havinga, Paul J.M., Scholten, Johan   +2 more
core   +1 more source

Forecasting Public Transit Use by Crowdsensing and Semantic Trajectory Mining: Case Studies

ISPRS International Journal of Geo-Information, 2016
With the growing development of smart cities, public transit forecasting has begun to attract significant attention. In this paper, we propose an approach for forecasting passenger boarding choices and public transit passenger flow.
Ningyu Zhang, Huajun Chen, Xi Chen, Jiaoyan Chen   +3 more
doaj   +1 more source