Intelligent Mobile Crowdsensing

A special issue of Applied Sciences (ISSN 2076-3417).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 78

Special Issue Editors


E-Mail Website
Guest Editor
College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
Interests: multi-agent system optimization and decision-making

E-Mail Website
Guest Editor
College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
Interests: multi-agent system optimization and decision-making; smart Internet of Things; collaborative planning of drones/unmanned vehicles
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Special Issue Information

Dear Colleagues,

Mobile crowdsensing primarily leverages the limited sensing resources of smart devices, vehicles, UAVs, and other collectors to gather valuable environmental information, facilitating innovative applications such as smart transportation, public health, disaster response, environmental monitoring, and urban planning. Its advantages include a low cost, a high mobility, and a wide coverage, making it a powerful tool for comprehensive data collection. The integration of advanced artificial intelligence technology significantly enhances data collectors’ decision-making autonomy, behavioral intelligence, and distributed collaboration capabilities, leading to improved task execution efficiency, strengthened privacy protection, and more effective incentive mechanisms. By leveraging AI, intelligent mobile crowdsensing not only optimizes data collection but also ensures that the collected data are processed and utilized in the most efficient manner possible. Intelligent mobile crowdsensing thus offers a commendable framework for future information gathering, providing a scalable and adaptable solution for various data-driven applications. Its ability to harness the power of AI and mobile technology positions it as a pivotal tool in addressing modern-day challenges through innovative and efficient data collection and analysis strategies.

Dr. Wei Gong
Dr. Minghui Liwang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Intelligent mobile crowdsensing offers a commendable framework for future information gathering, providing a scalable and adaptable solution for various data-driven applications. Its ability to harness the power of AI and mobile technology positions it as a pivotal tool in addressing modern-day challenges through innovative and efficient data collection and analysis strategies. Studies in this special issue include:
  • intelligent data collection and processing
  • collaborative sensing systems
  • privacy and security protection
  • novel incentive mechanisms
  • application scenarios and case studies, distributed learning over mobile crowdsensing, etc.

Published Papers

This special issue is now open for submission.
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