智能选址大数据(大数据城市化与机器人建造)
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DigitalFUTURES 2020
大数据城市化与
机器人建造
Big Data Urbanism and Robotic Fabrication
DigitalFUTURES2020
大数据城市化与机器人建造
(欧洲-中东-非洲时区)
01指导教师及简介 Instructors and Bios
Areti Markopoulou, 希腊建筑师、研究者、城市问题技术专家,致力于研究建筑与数字技术的融合。Areti是巴塞罗那IAAC的学术主任,并领导着前沿建筑小组探索设计和科学对现在和未来人类建造空间、行为和交互的正面影响。她的研究和实践力图将建筑重新定义为具有表现力的“身体”,超越了传统的静态材料、近似数据或标准化制造的概念。
Aldo Sollazzo, 是一位建筑师和研究者,也是一位计算性设计和数字建造的专家。曾于2007年完成建筑设计硕士学位,在IAAC于2012年获得高等建筑硕士学位,在巴塞罗那Fab Lab于2014年完成Fab Academy学业,Aldo目前正在参与多个同时进行的项目。自2011年起,Aldo担任了数据支持的设计公司Noumena的主管,并致力于以实践和实验的方式探究建筑、机械和建造中设计战略和新数字模式的边界。
Alexandre Dubor, 是一位以新科技改善城市建设和生活的建筑师和研究者。他拥有法国EAVT & ENPC的建筑与工程硕士学位和西班牙IAAC的高等建筑硕士学位,主修机械建造和大型增材制造(FabBot 3.0)。
Alex Mademochoritis,是一位希腊-法国城市问题技术专家、研究者和教育家。他在IAAC担任城市和技术硕士项目的主管。他的研究与学术方向包括城市技术和大数据的开发与应用,及它们将城市环境转变为交互式、以人为本、生态和智能城市方面的潜力。
02相关作品Related Works
世界第一座3D打印桥梁,西班牙,2016
TerraPerforma, 3D Printed Performative Wall
WASTEARN, IAAC COURSE
03课程介绍及教学日程Description and Agenda
在运用机器人进行建造时,城市数据能如何指导城市公共空间的设计?本次工作营将由两个部分组成,并教授有关城市设计、数据科学和建造中机器人建造的理论和技术知识。IAAC的前沿建筑小组是一个研究城市、建筑和公共空间设计转换中的信息、交互和建造新科技的综合性小组,将主持工作营。
目前越来越多的可用数据不但为观察和管理城市提供了新的机会,也同时在改变人们描述、理解和设计城市的方式,不断挑战在设计、规划和建造相关行业中的基本定式。定量和定性数据的交叉让人们能够以一种原始的视角体验和分析城市环境;在一个连续的互动关系中进行信息的输入和输出;在一个严格控制的区域内的数据和计量提供设定可持续性标准的可靠依据;还可以在检视人口过于密集的城市与区域时作为极具说服力的证据。
04预期目标Envisioned Outcome
通过对城市分析,大数据可视化和城市动态制图的介绍,学员在工作营的第一部分将会了解到城市设计中大数据的背景,并使用QGIS去绘制有关城市,游客行为和基础设施信息的图表。通过理解城市中热门景点对基础设施的需要(从娱乐到公共设施到商业),工作营学员将能够定位这些需要大量资源并产出大量废料的游客集中区。在将这些区域定位后,工作营的第二部分将着重于使用游客设施产生的废料,通过3D打印再利用制造新的城市设施以服务这些地区的公共空间。
这些机器人3D打印演算设计的循环性建造原则将帮助学员完成一系列为城市中高密度游客及公共区域的新设施类解决办法。工作营将以一次聚焦进阶城市化,数字建造和机器人的圆桌讨论作结。导师,学生和其他参与者将会有机会充分讨论交流有关城市化未来的建造工程的话题。
Big Data Urbanism and Robotic Fabrication
Instructors and Bios: Areti Markopoulou is a Greek architect, researcher, and urban technologist working at the intersection between architecture and digital technologies. She is the Academic Director at IAAC in Barcelona, where she also leads the Advanced Architecture Group, a multidisciplinary research group exploring how design and science can positively impact and transform the present and future of our built spaces, the way we live and interact. Her research and practice seek to redefine architecture as a performative “body” beyond traditional notions of static materiality, approximate data, or standardized manufacturing.
Aldo Sollazzo is an architect and researcher, an expert in computational design and digital fabrication. Master in Architectonic Design in 2007, Master in Advanced Architecture at IAAC in 2012, Fab Academy diploma in 2014 in the Fab Lab Barcelona, Aldo is currently involved in several projects running in parallel. Since 2011, he is the manager of Noumena, a firm embracing data-driven design, investigating between the boundaries of new digital paradigms and design strategies applied to architecture, robotics and fabrication, through a hands-on and experimental approach.
Alex Mademochoritis is Greek-French urban technologist, researcher and educator. He is the coordinator of the Master in City & Technology program at the Institute for Advanced Architecture of Catalonia (IAAC). His research and academic interests include the development and application of urban technologies and big data, in relation to their potentials in transforming urban environments into responsive, human-centered, ecological, and intelligent cities.
Description:How can urban data inform strategies for the design of public space using circular robotic construction methods? This workshop is divided into 2 parts and offers theoretical and technical knowledge in the topics of Urban Design and Data Science and Robotic Fabrication in Construction. It is led by the IAAC’s Advanced Architecture Group (AAG) an interdisciplinary research group investigating emerging technologies of information, interaction and manufacturing for the design and transformation of the cities, buildings and public spaces.
The increasing availability of data creates new opportunities not only for the monitoring and management of cities but also for changing the way we describe, understand and design them, challenging many basic assumptions of design, planning and construction-related professions. The overlapping of quantitative and qualitative data enables us to experience and analyze the urban environment in a completely original way, giving and receiving information in a continuous loop of interactions. Moreover, data and measurements in controlled enclosures, on the one hand, offer trustworthy mediums on how to develop sustainability criteria, and on the other, they have become pervasive and persistent in challenging the settlement of overpopulated and dense cities.
Agenda:
Envisioned Outcome:
Through an introduction to urban analytics, big data visualization and urban dynamic cartographies, during the first part of the workshop attendees will be able to understand the context of big data in urban design as well as use QGIS to map data related to cities, touristic activities and urban infrastructure. Understanding that dense touristic areas require heavy infrastructure (from leisure to urban furniture and commerce), we are able to map high touristic areas that require big amounts of resources as well as produce big amounts of waste. After identifying these areas in the city, the second part of the workshop will focus on using the waste produced by touristic infrastructure in order to robotically produce 3d printed urban elements for the public space surrounding these areas.
Through circular construction principles to computational design for robotic 3d Printing, the attendees will develop a series of urban furniture solutions for the dense touristic areas and public space.The workshop will conclude with a final round table discussion on Advanced Urbanism, Digital Fabrication and Robotics where tutors, students and other participants will have the opportunity to engage and interact in a discussion about the future of urbanism and the construction sector.
更多工作营精彩预告正在路上,敬请期待:
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Urban Design Data Viz | Tang Ge, MetroDataTech/City Data Group
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Architecture Intelligence | Hao Zheng, Upenn
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Interaction Design | Brad Cantrell, UVA Xun Liu, UVA Waishan Qiu, Cornell
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Computational Design | Alyisa Andrasek, RMIT
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Computational Design | Biao Li, Li Li, Southeast University
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Computational Design | Mark Burry, Swinburne
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Architecture Intelligence | Matias del Campo Sandra Manninger, UMichigan
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Robotic Fabircation | Philip Yuan, CAUP / Achim Menges, ICD
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Structural Design | Mike Xie Nic Bao, RMIT
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Computational Design | Roland Snooks, RMIT
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Neuro Design | Kris Mun, Sensory Architectures Georgios Christopolous , NTU Singapore Ying Wu
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Architecture Intelligence | Wanyu He, XKool
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Robotic Fabircation | Gilles Retsin, Bartlett UCL
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Robotic Fabircation | Yunsheng Su, Tongji University
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Structural Design | Philippe Block, ETH
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Robotic Fabircation | Areti Markopoulou, IaaC
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Robotic Fabircation | Mette Thomsen, CITA
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AR/VR | Biayna Bogosian, FIU
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Theory | Antoine Picon GSD
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Theory | Neil& Yanchao
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Computational Design | Shajay Bhooshan, ZHA Code
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Computational Design | Daniel Bolojan Emmanouil Vermisso Shermeen Yousif, FAU
……(列表更新中,精彩待续)
亚洲-泛太平洋时区
欧洲-中东-非洲时区
南北美洲时区
申请报名
以下所有时间均指格林威治中央区时(GMT)时间
第一轮申请窗口开放时间: 延期至,2020年6月6日中午12:00至6月10日中午12:00
***请申请者提前准备一张jpeg或png作品文件,图片尺寸和版式不限,文件大小不超过7MB(受腾讯报名系统限制)
申请时间节点: ·工作营具体教学信息和招生要求将于6月6日中午12:00之前在Fab-Union公众号和官方网站上陆续公布。· 线上申请表将在6月6日中午12:00准时通过腾讯问卷和Google Doc问卷发布,报名链接可在Fab-Union公众号和官方网站上获取。
申请流程
以下所有时间均指格林威治中央区时(GMT)时间
亚太区申请者: 1.关注Fab-Union公众号、digitalfutures.tongji.edu.cn或www.digitalfutures.world网站,获取各组工作营的教学信息,以及各组工作营关于软件技能、软件设备、硬件设备的不同招生要求。
2. 在6月6日中午12:00至6月10日中午12:00之间登陆腾讯报名系统,在报名表中用英文填写:
· 联系邮箱、姓名、教育或工作履历、获奖情况
· 上传一张jpeg或png作品文件,图片尺寸和版式不限,文件大小不超过7MB· 选择一个工作营报名志愿,并对照网站中该组招生要求,如实填写申请者已满足/拥有的软件技能、软件设备、硬件设备· 选择申请意向为:“正式学员(Active Student)”或“旁听学员(Auditing Student)”· 提交报名表***“正式学员(Active Student)”意味着学员会全程亲身参与到工作营学习中,与导师互动,完成教学成果,并最终获得结业证书。“旁听学员(Auditing Student)”意味着学员可以全程旁听工作营教学,但是无法与导师互动,也不会被授予结业证书。
3.组委会收到申请者报名信息后,会提交给各组工作营导师进行审核。
4.该志愿录取结果将于6月13日中午12:00之前以邮件形式发送给申请者。成功入选的申请人可以根据邮件信息加入指定微信群。
5.对于未入选者,仍可在6月13日中午12:00之后关注网站,届时如有仍未满员的工作营,可通过组委会提供的渠道在6月15日中午12:00之前完成第二志愿报名,录取结果将于6月17日中午12:00之前以邮件形式发送给申请者。
***网站中将分别列出每组工作营的“正式学员满员”和“旁听学员满员”两种状态,申请者可根据显示的状态选取未满员工作营作为第二志愿。例如,某工作营只显示“正式学员满员”,申请者仍可以“旁听学员”的意向申请该工作营。
6.此过程将以两天为一个申请反馈周期持续进行,直到所有工作营满员。
请申请者加入官方微信群组以获取实时信息更新
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