Task Assignment Scheme Designed for Online Urban Sensing Based on Sparse Mobile Crowdsensing

Sparse mobile crowdsensing (SMCS) achieves urban-scale environmental sensing by assigning tasks to workers in specific subareas and inferring global data from the collected information. However, the effectiveness of SMCS is often limited because many studies overlook workers' mobility and data...

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Vydáno v:	IEEE internet of things journal Ročník 12; číslo 11; s. 17791 - 17806
Hlavní autoři:	Zeng, Hongjian, Xiong, Yonghua, She, Jinhua, Yu, Anjun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 01.06.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithm optimization Automation Constraints Costs Crowdsensing Cycle time Data collection Data integrity Effectiveness Evolutionary algorithms Evolutionary computation Genetic algorithms Inference Inference algorithms Internet of Things Mobile computing Optimization Sensors sparse mobile crowdsensing (SMCS) subarea evaluation task assignment Time factors
ISSN:	2327-4662, 2327-4662
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