Spatio-temporal enabled urban decision-making process modeling and visualization under the cyber-physical environment

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• 作者：Wei Wang ; ChuanBo Hu ; NengCheng Chen ; ChangJiang Xiao…
• 关键词：decision ; making process ; meta ; model ; process chain ; SensorML ; emergency management ; 鍐崇瓥杩囩▼ ; 鍏冩ā鍨?/li> 杩囩▼閾?/li> 浼犳劅鍣ㄥ缓妯¤瑷€ ; 搴旀€ョ鐞?/li> 100105
• 刊名：SCIENCE CHINA Information Sciences
• 出版年：2015
• 出版时间：October 2015
• 年：2015
• 卷：58
• 期：10
• 页码：1-17
• 全文大小：2,340 KB
• 参考文献：1.Jankowski P. Integrating geographical information systems and multiple criteria decision-making methods. Int J Geogr Inf Syst, 1995, 9: 251鈥?73CrossRef
  2.Xu X H, Liang D, Zhou Y J, et al. A risk elimination coordination method for large group decision-making in natural disaster emergencies. Hum Ecol Risk Assessment, 2015, 21: 1314鈥?325CrossRef
  3.Br茅zillon P, Aroua A. A representation of real-time decision-making by contextual graphs based simulation. J Decision Syst, 2013, 22: 28鈥?2CrossRef
  4.Bouchart F J, Blackwood D J, Jowitt P W. Decision mapping: understanding decision-making processes. Civ Eng Environ Syst, 2002, 19: 187鈥?07CrossRef
  5.Cui L. Applying fuzzy comprehensive evaluation method to evaluate quality in crisis and emergency management. Commun Statist A-Theor Method, 2012, 41: 3942鈥?959CrossRef
  6.Zheng W, Fang B. Structure-independent disaster recovery: concept, architecture and implementations. Sci China Sers F-Inf Sci, 2009, 52: 813鈥?23MATH CrossRef
  7.Wei B, Jin Z, Zowghi D, et al. Implementation decision-making for internetware driven by quality requirements. Sci China Inf Sci, 2014, 57: 072104
  8.H氓kansson A, Hartung R. An infrastructure for individualised and intelligent decision-making and negotiation in cyber-physical systems. Procedia Comput Sci, 2014, 35: 822鈥?31CrossRef
  9.Chen N C, Xiao C J, Pu F L, et al. Cyber-physical geographical information service-enabled control of diverse in-situ sensors. Sensors, 2015, 15: 2565鈥?592CrossRef
  10.DelinK A, Jackson S P, Jackson D W, et al. Environmental studies with the sensor web: principles and practice. Sensors, 2005, 5: 103鈥?17CrossRef
  11.Luo Y T, Shen X J, Zhu Y M. Integrated optimization methods in multisensor decision and estimation fusion. Sci China Inf Sci, 2012, 55: 545鈥?50MATH MathSciNet CrossRef
  12.Hu C L, Guan Q F, Chen N C, et al. An observation capability metadata model for EO sensor discovery in sensor web enablement environments. Remot Sens, 2014, 6: 10546鈥?0570CrossRef
  13.Ren W, Ren Y, Zhang H. Secure, dependable and publicly verifiable distributed data storage in unattended wireless sensor networks. Sci China Inf Sci, 2010, 53: 964鈥?79CrossRef
  14.Vitoriano B, Rodr铆guez J T, Tirado G, et al. Intelligent decision-making models for disaster management. Hum Ecol Risk Assessment, 2015, 21: 1341鈥?360CrossRef
  15.Paolino L, Romano M, Sebilo M, et al. Supporting the on-site emergency management through a visualisation technique for mobile devices. J Locat Based Serv, 2010, 4: 222鈥?39CrossRef
  16.Lumpe M, Schneider J G. A form-based meta-model for software composition. Sci Comput Program, 2005, 56: 59鈥?8MATH MathSciNet CrossRef
  17.Chen N C, Hu C L, Chen Y, et al. Using SensorML to construct a geoprocessing e-Science workflow model under a sensor web environment. Comput Geosci, 2012, 47: 119鈥?29CrossRef
  18.Atkinson C, Kuhne T. Model-driven development: a metamodeling foundation. IEEE Softw, 2003 20: 3641
  19.Othman S H, Beydoun G, Sugumaran V. Development and validation of a Disaster Management Metamodel (DMM). Inf Process Manag, 2014, 50: 235鈥?71CrossRef
  20.Chen N C, Wang K, Xiao C J, et al. A heterogeneous sensor web node meta-model for the management of a flood monitoring system. Environ Modell Softw, 2014, 54: 222鈥?37CrossRef
  21.Chen N C, Di L P, Yu G N, et al. Use of ebRIM-based CSW with sensor observation services for registry and discovery of remote-sensing observations. Comput Geosci, 2009, 35: 360鈥?72CrossRef
  22.Chen N C, Di L P, Yu G N, et al. A flexible geospatial sensor observation service for diverse sensor data based on Web service. ISPRS J Photogramm Remote Sens, 2009, 64: 234鈥?42CrossRef
  23.Lee J, Jeong Y, Oh Y S, et al. An integrated approach to intelligent urban facilities management for real-time emergency response. Autom Constr, 2013, 30: 256鈥?64CrossRef
  
• 作者单位：Wei Wang (1) (2)
  ChuanBo Hu (1)
  NengCheng Chen (1) (2)
  ChangJiang Xiao (1)
  Chao Wang (1)
  ZeQiang Chen (2)
  
  1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China
  2. Collaborative Innovation Center of Geospatial Technology, Wuhan, 430079, China
  
• 刊物类别：Computer Science
• 刊物主题：Chinese Library of Science
  Information Systems and Communication Service
  
• 出版者：Science China Press, co-published with Springer
• ISSN：1869-1919

文摘

Urban management is increasingly dependent on the construction of cyber-physical systems, which have been widely deployed in multiple fields, including agriculture, transportation, and health care. Cyberphysical systems provide a large volume of big sensory data. Thus, the application of big data for urban emergency decision-making has become a challenge. Traditional decision-making models are unable to overcome several technical problems, including spatio-temporal information support and access to real-time service for disaster management and emergency response. In this paper, we propose a spatio-temporal enabled urban decision-making process modeling method in the cyber-physical environment and discuss the development off our basic metadata components, the definition of eleven-tuple information description structure. A prototype system is designed for modeling registering, management, visualization, and other functions. Decision-making processes are implemented as composite process chains through three phases, i.e., decision-making process modeling, instantiation of the decision-making process chain and execution of the decision-making process chain. For application to gas leak events, the decision-making process is executed to confirm the feasibility of the proposed decision-making process modeling method and the flexibility of the eleven-tuple information structure. Keywords decision-making process meta-model process chain SensorML emergency management