2024/01/06 by Wansen Wu, Wu, Wansen, Weiyi Yang +15 · 1 citation
Business, Management and Accounting · Computer Science · #Big Data and Business Intelligence #Computers and Society (cs.CY) #Data Visualization and Analytics #FOS: Computer and information sciences #Mobile Crowdsensing and Crowdsourcing
paper · pdf · doi:10.48550/arxiv.2401.03229
openalex publication_date 2024/01/06 · openalex created_date 2024/01/13 · openalex updated_date 2026/07/28
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 letter reports the outcomes of the latest DHW-CSI, focusing on Autonomous Crowdsensing (ACS) enabled by a range of 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.