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Urban Computing and Smart Cities:Opportunities and Challenges in Modelling Large-Scale Aggregated Human Behavior

机译:城市计算和智慧城市:大型综合人类行为建模的机遇与挑战

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City-wide urban infrastructures are increasingly reliant on networked technology to improve and expand their services. As a side effect of this digitalization, large amounts of data -digital footprints-can be sensed and analyzed to uncover patterns of human urban behavior and to augment the city experience of its citizens. In my talk, I will introduce the main concepts, opportunities and challenges in the emerging area of urban computing/smart cities, which focuses on improving the quality of life of an urban environment by understanding the city dynamics through the data provided by ubiquitous technologies. This is a human-centric, data-rich area that spans multiple disciplines, including sociology, computer science and urban planning. From a computer science perspective, there are challenges in a variety of domains, including data visualization, storage, security, privacy, machine learning, data mining and pattern recognition. Some of the applications of smart cities include traffic forecasting, modeling of the spread of biological viruses, urban and transportation design and location-based services.
机译:全市范围的城市基础设施越来越依赖网络技术来改善和扩展其服务。作为这种数字化的副作用,可以检测和分析大量数据(数字足迹),以发现人类城市行为的模式并增强其公民的城市体验。在我的演讲中,我将介绍新兴的城市计算/智能城市领域的主要概念,机遇和挑战,其重点是通过利用普适技术提供的数据来了解城市动态,从而改善城市环境的生活质量。这是一个以人为中心,数据丰富的领域,涵盖了社会学,计算机科学和城市规划等多个学科。从计算机科学的角度来看,在各个领域都存在挑战,包括数据可视化,存储,安全性,隐私,机器学习,数据挖掘和模式识别。智慧城市的一些应用包括交通预测,生物病毒传播建模,城市和交通设计以及基于位置的服务。

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