大数据驱动下智慧城市建设的若干思考

doi:10.3981/j.issn.1000-7857.2017.21.016

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摘要在当前的智慧城市建设中，随着互联网、物联网、通信网及大规模智能化应用服务的深入发展，产生了海量、异构、多源的城市时空大数据。在大数据时代，智慧城市的建设值得人们更深层次的思考。如何应对这些大规模、复杂的城市数据，尤其是对数据的感知、采集、存储、管理、分析、挖掘、计算、可视化及高效的服务应用都面临着巨大挑战。本文主要从技术、立法、管理3个视角重点阐述了大数据对智慧城市发展驱动作用。在技术上从纵向和横向两个视角分析城市时空大数据的特征及应用；从数据资产的角度强调了立法在智慧城市中的作用；从政策管理、奖惩与市场机制等方面分析了管理在智慧城市建设中的重要性；从综合视角思考大数据驱动下智慧城市建设中的若干问题。

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	马新强
	刘勇
	范婧
	黄羿
	吴茂念
	张明义

关键词 ：智慧城市, 大数据, 城市计算, 数据挖掘, 可视化分析

Abstract：In the construction of smart city, the depth development of Internet, Internet of things, communication networks and large-scale intelligent services will result in massive, heterogeneous, multi-source big spatio-temporal urban data. In the era of big data, we should think deeply about the construction of smart city. How to deal with these large-scale and complicated urban data is facing enormous challenges, including data collection, sensing, storage, management, mining, visualization and efficient services. In this paper we mainly discuss the driving effects of big data on smart city in the views of technology, legislation and management. We analyze the features and applications of big spatio-temporal urban data in two directions, point out the importance of legislation from the perspective of data assets, and summarize the management of smart city in terms of policy management, rewards and punishments, and market mechanisms. Finally, we put forward some thoughts on the construction of smart city driven by big data.

Key words： smart city big data urban computing data mining visual analysis

收稿日期: 2017-03-23

基金资助:国家自然科学基金项目（61562011）；浙江大学工业控制技术国家重点实验室开放课题（ICT170330）；浙江省自然科学基金项目（LY16F020015）；重庆市基础科学与前沿技术研究项目（cstc2016jcyjA0568，cstc2015jcyjA40026）

通讯作者: 刘勇(通信作者),教授,研究方向为机器学习、机器人,电子信箱:yongliu@iipc.zju.edu.cn E-mail: yongliu@iipc.zju.edu.cn

作者简介: 马新强,副教授,研究方向为城市计算、健康医疗大数据,电子信箱:xinqma@163.com

引用本文:

马新强, 刘勇, 范婧, 黄羿, 吴茂念, 张明义. 大数据驱动下智慧城市建设的若干思考[J]. 科技导报, 2017, 35(21): 131-137.
MA Xinqiang, LIU Yong, FAN Jing, HUANG Yi, WU Maonian, ZHANG Mingyi. Big data-driven smart city:Some thoughts. Science & Technology Review, 2017, 35(21): 131-137.

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http://www.kjdb.org/CN/10.3981/j.issn.1000-7857.2017.21.016 或 http://www.kjdb.org/CN/Y2017/V35/I21/131

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