Retraction Notice: Autonomous Crowdsensing: Operating and Organizing Crowdsensing for Sensing Automation

The precise characterization and modeling of Cyber-Physical-Social Systems (CPSS) requires more comprehensive and accurate data, which imposes heightened demands on intelligent sensing capabilities. To address this issue, Crowdsensing Intelligence (CSI) has been proposed to collect data from CPSS by harnessing the collective intelligence of a diverse workforce. Our first and second Distributed/Decentralized Hybrid Workshop on Crowdsensing Intelligence (DHW-CSI) have focused on principles and high-level processes of organizing and operating CSI, as well as the participants, methods, and stages involved in CSI. This perspective reports the outcomes of the latest DHW-CSI, focusing on Autonomous Crowdsensing (ACS) enabled by foundation intelligence and its associated technologies such as decentralized autonomous organizations and operations, large language models, and human-oriented operating systems. Specifically, we explain what ACS is and explore its distinctive features in comparison to traditional crowdsensing. Moreover, we present the “6A-goal” of ACS and propose potential avenues for future research.

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Publication Details

Journal
IEEE Transactions on Intelligent Vehicles
Published
2024-11-20
DOI
https://doi.org/10.1109/tiv.2024.3502554
Primary Topic
Mobile Crowdsensing and Crowdsourcing
Type
article
Field-Weighted Citation Impact
0.00
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article

Retraction Notice: Autonomous Crowdsensing: Operating and Organizing Crowdsensing for Sensing Automation

Weiyi Yang, Wansen Wu, Zhengqiu Zhu, Yong Peng et al.
IEEE Transactions on Intelligent Vehicles
Mobile Crowdsensing and Crowdsourcing
article

Retraction Notice: Autonomous Crowdsensing: Operating and Organizing Crowdsensing for Sensing Automation

Weiyi Yang, Wansen Wu, Zhengqiu Zhu, Yong Peng, Juanjuan Li, Yong Zhao, Sihang Qiu, Bin Chen, Fei‐Yue Wang
article en

Abstract

The precise characterization and modeling of Cyber-Physical-Social Systems (CPSS) requires more comprehensive and accurate data, which imposes heightened demands on intelligent sensing capabilities. To address this issue, Crowdsensing Intelligence (CSI) has been proposed to collect data from CPSS by harnessing the collective intelligence of a diverse workforce. Our first and second Distributed/Decentralized Hybrid Workshop on Crowdsensing Intelligence (DHW-CSI) have focused on principles and high-level processes of organizing and operating CSI, as well as the participants, methods, and stages involved in CSI. This perspective reports the outcomes of the latest DHW-CSI, focusing on Autonomous Crowdsensing (ACS) enabled by foundation intelligence and its associated technologies such as decentralized autonomous organizations and operations, large language models, and human-oriented operating systems. Specifically, we explain what ACS is and explore its distinctive features in comparison to traditional crowdsensing. Moreover, we present the “6A-goal” of ACS and propose potential avenues for future research.

IEEE Transactions on Intelligent Vehicles
National University of Defense Technology (CN), Chinese Academy of Sciences (CN), Institute of Automation (CN)
Reduced inequalities
Openalex Percentile: Top 78%
Mobile Crowdsensing and Crowdsourcing
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