大数据在我国城市供水全过程监管领域的应用展望
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摘要
我国城市供水行业现存海量数据信息,但整体利用程度偏低,信息壁垒和数据孤岛现象突出。与传统数据管理相比,大数据具有规模海量、分析预测和辅助决策等特点,能够更好地帮助政府部门实现城市供水全过程智慧化监管。基于供水行业数据特点,从供水数据的采集、存储、整合、共享及挖掘等技术实现的角度,构建了城市供水政府监管大数据研究需求框架,同时分析了大数据在城市供水全过程监管领域的应用前景及未来发展趋势,为有效提升政府对城市供水全过程监管能力和供水应急保障能力提出相关建议。
Large amounts of data and information exits in urban water supply industry in China with inefficient utilization,information barriers and the problem of data island.Compared with traditional data management,big data can be used to support intelligent supervision of the whole process of urban water supply with analytical prediction and assistant decision-making function.Based on the data characteristics in government regulation of urban water supply,the domain demand framework for big data research is constructed.Requirement analysis on data collection,storage,integration and sharing,as well as analysis and mining are studied.Application prospect and future trends on big data are discussed.At last,recommendations to enhance the government regulatory capacity and emergency support capability in water supply industry are conducted.
Large amounts of data and information exits in urban water supply industry in China with inefficient utilization,information barriers and the problem of data island.Compared with traditional data management,big data can be used to support intelligent supervision of the whole process of urban water supply with analytical prediction and assistant decision-making function.Based on the data characteristics in government regulation of urban water supply,the domain demand framework for big data research is constructed.Requirement analysis on data collection,storage,integration and sharing,as well as analysis and mining are studied.Application prospect and future trends on big data are discussed.At last,recommendations to enhance the government regulatory capacity and emergency support capability in water supply industry are conducted.
引文
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[35]刘伟,吴庆梅,邓力,等.美国饮用水预警监测技术述评[J].农业灾害研究,2018,8(1):43-44.
[36]Storey M V,Van B D G,Burns B P.Advances in on-line drinking water quality monitoring and early warning systems[J].Water research,2011,45(2):741-747.
[37]周煜申,康望星,沈存,等.大数据在水环境综合评价预警中的应用研究[J].江苏科技信息,2017,(35):52-54.
[38]王书伟.大数据时代政府部门间信息资源共享策略研究[D].长春:吉林大学,2013.
[39]邵益生,宋兰合,李琳,等.城市饮用水水质督察技术体系构建及应用示范[J].建设科技,2015,(10):37-38,41.
[40]谢治菊.大数据优化政府决策的机理,风险及规避[J].行政论坛,2018,(1):60-66.
[41]郑石明,刘佳俊.基于大数据的空气污染治理与政府决策[J].华南师范大学学报:社会科学版,2017,(4):105-111.
[2]孙国庆.智慧水务关键技术研究及应用[J].水利信息化,2018,2(1):46-49.
[3]关庆珍.大数据驱动政府管理创新策略研究[J].成都行政学院学报,2017,38(5):17-19.
[4]Kim G H,Trimi S,Chung J H.Big-data applications in the government sector[J].Communications of the ACM,2014,57(3):78-85.
[5]Faghmous J H,Kumar V.A big data guide to understanding climate change:The case for theory-guided data science[J].Big data,2014,2(3):155-163.
[6]Manzoor A.Emerging role of big data in public sector[M]//Big Data:Concepts,Methodologies,Tools,and Applications.IGI Global,2016:2458-2478.
[7]Jin X,Wah B W,Cheng X,et al.Significance and challenges of big data research[J].Big Data Research,2015,2(2):59-64.
[8]郭建锦,郭建平.大数据背景下的国家治理能力建设研究[J].中国行政管理,2015,6:73-76.
[9]罗梓超,吕志坚.韩国大数据发展及应用分析[J].全球科技经济瞭望,2014,29(3):22-26.
[10]Calder K E.Singapore:Smart city,smart state[M].Brookings Institution Press,2016.
[11]杨柳忠,黄健,边际,等.城市供水水质监测预警系统技术平台研究概述[J].建设科技,2012,(5):74-76.
[12]边际,牛晗,耿艳妍,等.三级水质监控网络构建关键技术研究与示范[J].给水排水,2013,39(6):13-17.
[13]黄健,黄金桃,张晓亮,等.水质信息管理系统及可视化平台关键技术研发与示范[J].给水排水,2013,39(6):18-22.
[14]张宏建,张光新,侯迪波,等.水质安全评价及预警关键技术研发与应用示范[J].给水排水,2013,39(6):23-27.
[15]贾瑞宝,邵益生,宋兰合,等.济南市城市供水水质监测预警系统技术平台[J].建设科技,2014,(Z1):84-85.
[16]CJ/T 474-2015城镇供水管理信息系统供水水质指标分类与编码[S].
[17]韩晶,王健全.大数据标准化现状及展望[J].信息通信技术,2014,(6):38-42.
[18]程学旗,靳小龙,王元卓,等.大数据系统和分析技术综述[J].软件学报,2014,25(9):1889-1908.
[19]Joseph R C,Johnson N A.Big data and transformational government[J].IT Professional,2013,15(6):43-48.
[20]马广惠,安小米,宋懿.业务驱动的政府大数据平台数据治理[J].情报资料工作,2018,39(1):21-27.
[21]陈军飞,邓梦华,王慧敏.水利大数据研究综述[J].水科学进展,2017,28(4):622-631.
[22]Allen M,Preis A,Iqbal M,et al.Case study:a smart water grid in Singapore[J].Water Practice and Technology,2012,7(4):wpt2012089.
[23]史澜.基于移动互联技术理念探析大数据在供水管网管理的运用及展望[J].电子世界,2016,(20):10,12.
[24]游珊.基于数据挖掘技术的火灾事故分析[J].信息系统工程,2018,(1):22.
[25]陈松.浅析供水调度大数据挖掘与应用[J].求知导刊,2018,4(2):30-31.
[26]闫成印.物联网带动大数据发展[J].互联网天地,2012,(11):29-31.
[27]TongKe F.Smart agriculture based on cloud computing and IOT[J].Journal of Convergence Information Technology,2013,8(2):1.
[28]Lazarescu M T.Design of a WSN platform for long-term environmental monitoring for IoT applications[J].IEEE Journal on emerging and selected topics in circuits and systems,2013,3(1):45-54.
[29]沈一凡,魏冠雄,侯迪波,等.供水管网水质监测传感器网络布局优化[J].自动化仪表,2017,38(6):51-55.
[30]束慧.基于物联网技术的污水处理过程动态监控系统[J].计算机测量与控制,2014,22(8):2441-2443.
[31]Hart W E,Murray R.Review of sensor placement strategies for contamination warning systems in drinking water distribution systems[J].Journal of Water Resources Planning and Management,2010,136(6):611-619.
[32]李云生,刘伟江,吴悦颖,等.美国水质模型研究进展综述[J].水利水电技术,2006,(2):68-73.
[33]Chapra S C,Pelletier G J,Tao H.QUAL2K:A modeling framework for simulating river and stream water quality:Documentation and users manual[Z].Civil and Environmental Engineering Dept.,Tufts University,Medford,MA,2003.
[34]Tong S T Y,Chen W.Modeling the relationship between land use and surface water quality[J].Journal of environmental management,2002,66(4):377-393.
[35]刘伟,吴庆梅,邓力,等.美国饮用水预警监测技术述评[J].农业灾害研究,2018,8(1):43-44.
[36]Storey M V,Van B D G,Burns B P.Advances in on-line drinking water quality monitoring and early warning systems[J].Water research,2011,45(2):741-747.
[37]周煜申,康望星,沈存,等.大数据在水环境综合评价预警中的应用研究[J].江苏科技信息,2017,(35):52-54.
[38]王书伟.大数据时代政府部门间信息资源共享策略研究[D].长春:吉林大学,2013.
[39]邵益生,宋兰合,李琳,等.城市饮用水水质督察技术体系构建及应用示范[J].建设科技,2015,(10):37-38,41.
[40]谢治菊.大数据优化政府决策的机理,风险及规避[J].行政论坛,2018,(1):60-66.
[41]郑石明,刘佳俊.基于大数据的空气污染治理与政府决策[J].华南师范大学学报:社会科学版,2017,(4):105-111.