Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018WR024447 |
Reward-Based Participant Management for Crowdsourcing Rainfall Monitoring: An Agent-Based Model Simulation | |
Yang, Pan1,2,4; Ng, Tze Ling2,3; Cai, Ximing1,4 | |
2019-10-16 | |
发表期刊 | WATER RESOURCES RESEARCH
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ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
文章类型 | Article;Early Access |
语种 | 英语 |
国家 | USA; Peoples R China; Australia |
英文摘要 | Crowdsourcing incorporates common citizens as rich sources of data and is promising for environmental monitoring. In this paper, we propose and test the idea of incorporating incentives to crowdsourcing management for rainfall monitoring. Specifically, we model the allocation of incentives (quantitatively measurable and limited rewards) among crowdsourcing participants for a theoretical rainfall monitoring case. For this purpose, we develop an integrated model comprising a reward allocation component to represent the decision-making process of a central manager, an agent-based model to simulate the interactions between the manager and participants, and a rainfall simulation model to evaluate the effectiveness of various reward allocation policies. We simulate six reward allocation policies of varying levels of administrative cost, and consideration of participant and rainfall spatial heterogeneities. The results suggest the performance of each policy to improve with the reward budget and their spatial uniformity. Among the six policies tested, we find that the participant density weighted maximum participation policy yields the most accurate estimation of rainfall intensity due to its more explicit consideration of the spatial distribution of participants; however, this policy associates with a high administrative cost. This highlights the trade-off between performance and cost in designing effective reward allocation policies. This paper provides a physical and behavior simulation modeling tool to study the feasibility and complexity of reward-based participant management for crowdsourcing rainfall monitoring. The proposed crowdsourcing method is beneficial for a wide range of applications that require rainfall data with fine resolution, such as storm water management and water availability and biomass assessment for food and energy crops. |
英文关键词 | crowdsourcing rainfall monitoring agent-based model reward allocation participant management |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000491049700001 |
WOS关键词 | GLOBAL SENSITIVITY-ANALYSIS ; CITIZEN SCIENCE ; RESPONSE RATES ; SOCIAL MEDIA ; GAUGE ; INCENTIVES ; NETWORK ; DESIGN ; QUALITY ; RADAR |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/187690 |
专题 | 资源环境科学 |
作者单位 | 1.Univ Illinois, Dept Civil & Environm Engn, Urbana, IL 61820 USA; 2.Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R China; 3.CSIRO Land & Water, Clayton, Vic, Australia; 4.Univ Illinois, DOE Ctr Adv Bioenergy & Bioprod Innovat, Urbana, IL 61820 USA |
推荐引用方式 GB/T 7714 | Yang, Pan,Ng, Tze Ling,Cai, Ximing. Reward-Based Participant Management for Crowdsourcing Rainfall Monitoring: An Agent-Based Model Simulation[J]. WATER RESOURCES RESEARCH,2019. |
APA | Yang, Pan,Ng, Tze Ling,&Cai, Ximing.(2019).Reward-Based Participant Management for Crowdsourcing Rainfall Monitoring: An Agent-Based Model Simulation.WATER RESOURCES RESEARCH. |
MLA | Yang, Pan,et al."Reward-Based Participant Management for Crowdsourcing Rainfall Monitoring: An Agent-Based Model Simulation".WATER RESOURCES RESEARCH (2019). |
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