22 citations · 28 across the 13 of their papers we have counts for
4 papers · 1 filter
A Data-driven Crowd Simulation Framework Integrating Physics-informed Machine Learning with Navigation Potential Fields
Runkang Guo, Bin Chen, Qi Zhang +3
Traditional rule-based physical models are limited by their reliance on singular physical formulas and parameters, making it difficult to effectively tackle the intricate tasks ass…
Heterogeneous Graph Reinforcement Learning for Dependency-aware Multi-task Allocation in Spatial Crowdsourcing
Yong Zhao, Zhengqiu Zhu, Chen Gao +3
Spatial Crowdsourcing (SC) is gaining traction in both academia and industry, with tasks on SC platforms becoming increasingly complex and requiring collaboration among workers wit…
Conversational Crowdsensing: A Parallel Intelligence Powered Novel Sensing Approach
Zhengqiu Zhu, Yong Zhao, Bin Chen +6
The transition from CPS-based Industry 4.0 to CPSS-based Industry 5.0 brings new requirements and opportunities to current sensing approaches, especially in light of recent progres…
Autonomous Crowdsensing: Operating and Organizing Crowdsensing for Sensing Automation
Wansen Wu, Weiyi Yang, Juanjuan Li +6
The precise characterization and modeling of Cyber-Physical-Social Systems (CPSS) requires more comprehensive and accurate data, which imposes heightened demands on intelligent sen…