TY - JOUR
T1 - CrowdManager
T2 - An Ontology-Based Interaction and Management Middleware for Heterogeneous Mobile Crowd Sensing
AU - Liu, Yimeng
AU - Yu, Zhiwen
AU - Wang, Jiangtao
AU - Guo, Bin
AU - Su, Jiangbin
AU - Liao, Jiahao
N1 - Publisher Copyright:
© 2002-2012 IEEE.
PY - 2023/11/1
Y1 - 2023/11/1
N2 - With the enrichment of types and numbers of sensing terminals, more and more devices such as mobile phones, smart wearables, mobile robots, drones have appeared in our life, enabling the development of Mobile Crowd Sensing (MCS) technology. MCS systems has gradually changed from isomorphic sensing to heterogeneous collaborative sensing, and finally evolved into a heterogeneous multi-source sensing mode of the fusion of humans, machines and objects (things). However, state-of-the-art systems/frameworks do not well support efficient interactions and Heterogeneous Crowd Agents (HCA) management in Heterogeneous MCS (H-MCS) systems. With this in mind, this article aims at two major gaps: Efficient interaction and collaboration of HCA, automated modeling and flexible management of HCA. To deal with the challenges, we design an ontology-based interaction and management middleware (CrowdManager). Three core modules that constitute the middleware: HCA Information Extraction and Representation (HER), Ontology-based HCA Construction & Management (OCM), and Communication and Interaction Module (CIM) are well demonstrated. Extensive comparative evalution suggests that our approach not only brings rich and efficient HCA management and interactive functions to H-MCS systems, but also reduces communication time and various resource occupancy rates by more than 50%.
AB - With the enrichment of types and numbers of sensing terminals, more and more devices such as mobile phones, smart wearables, mobile robots, drones have appeared in our life, enabling the development of Mobile Crowd Sensing (MCS) technology. MCS systems has gradually changed from isomorphic sensing to heterogeneous collaborative sensing, and finally evolved into a heterogeneous multi-source sensing mode of the fusion of humans, machines and objects (things). However, state-of-the-art systems/frameworks do not well support efficient interactions and Heterogeneous Crowd Agents (HCA) management in Heterogeneous MCS (H-MCS) systems. With this in mind, this article aims at two major gaps: Efficient interaction and collaboration of HCA, automated modeling and flexible management of HCA. To deal with the challenges, we design an ontology-based interaction and management middleware (CrowdManager). Three core modules that constitute the middleware: HCA Information Extraction and Representation (HER), Ontology-based HCA Construction & Management (OCM), and Communication and Interaction Module (CIM) are well demonstrated. Extensive comparative evalution suggests that our approach not only brings rich and efficient HCA management and interactive functions to H-MCS systems, but also reduces communication time and various resource occupancy rates by more than 50%.
KW - Heterogeneous mobile crowd sensing
KW - collaboration
KW - human-machine-things
KW - interaction
KW - ontology management
UR - http://www.scopus.com/inward/record.url?scp=85136888589&partnerID=8YFLogxK
U2 - 10.1109/TMC.2022.3199787
DO - 10.1109/TMC.2022.3199787
M3 - 文章
AN - SCOPUS:85136888589
SN - 1536-1233
VL - 22
SP - 6358
EP - 6376
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 11
ER -