Results 81 to 90 of about 12,378 (273)

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

open access: yesISPRS 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   +3 more
doaj   +1 more source

Crowdsensing for Characterizing Mobility and Its Impact on the Subjective Wellbeing in an Underdeveloped Region

open access: yesApplied Sciences, 2020
Living in an underdeveloped region implies a higher cost of living: access to services, such as school, work, medical care, and groceries, becomes more costly than those who live in regions with better infrastructure.
A. G. Ramos   +2 more
doaj   +1 more source

Urban Mobility: Mobile Crowdsensing Applications

open access: yes, 2018
Mobility has become one of the most difficult challenges that cities must face. More than half of world’s population resides in urban areas and with the continuously growing population it is imperative that cities use their resources more efficiently.
Simões, João   +3 more
openaire   +2 more sources

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

open access: yesStructural 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   +3 more
wiley   +1 more source

Differentially Private Mobile Crowd Sensing Considering Sensing Errors

open access: yesSensors, 2020
An increasingly popular class of software known as participatory sensing, or mobile crowdsensing, is a means of collecting people’s surrounding information via mobile sensing devices. To avoid potential undesired side effects of this data analysis method,
Yuichi Sei, Akihiko Ohsuga
doaj   +1 more source

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

open access: yesCorporate 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   +5 more
wiley   +1 more source

A model for implementing vibration and sound heatmaps in smart cities based on crowdsensing data

open access: yesSmart Cities and Regional Development Journal, 2023
This paper aims to establish a model that can utilize vibration and sound heatmaps in smart traffic using Internet of things, mobile and web technologies.
Boban DAVIDOVIC   +2 more
doaj  

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

open access: yesIEEE Communications Surveys and Tutorials, 2019
Mobile crowdsensing (MCS) has gained significant attention in recent years and has become an appealing paradigm for urban sensing. For data collection, MCS systems rely on contribution from mobile devices of a large number of participants or a crowd ...
Andrea Capponi   +5 more
semanticscholar   +1 more source

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

open access: yesWIREs 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   +8 more
wiley   +1 more source

Optimizing Wirelessly Powered Crowd Sensing: Trading energy for data

open access: yes, 2017
To overcome the limited coverage in traditional wireless sensor networks, \emph{mobile crowd sensing} (MCS) has emerged as a new sensing paradigm. To achieve longer battery lives of user devices and incentive human involvement, this paper presents a ...
Andreev, Sergey   +4 more
core   +1 more source

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