EMIA - Epi-terrestrial Multi-modal Input Assimilation

极端天气是一个日益严重的城市问题，而成百上千的屏幕显示交通拥堵，行人川流不息。智慧城市系统能否灵活应对每一个独特的人群，并应对即将到来的城市山洪暴发？缺少的关键是(i)了解屏幕之间的每条道路上发生了什么，（ii）如何使所有这些数据与人类城市活动、栖息地和气候变化相关，以及（iii）同步数据，就像成千上万的交通协调员在每条道路上协调一致一样，在雨天，阳光下甚至洪水泛滥。EMIA项目就是为此而设计的。它是AI预测城市洪水的延伸，居住在一个革命性的超级建筑（AIMU）中。AIMU吸收了数字孪生，使其对人工智能可读，同时保持地理拓扑的准确性和相关性。与交通监控系统中的传统机器学习算法不同，EMIA提出了一种重新实施道路安全标准的方法，即从现有的交通监控系统中提取以人为中心的参数，并通过整合和分析来自频繁道路使用者的注册行车记录仪传输的视频片段来扩展信息的范围。视频的来源将被匿名化，任何不合适的视频将在传输前被自动删除。在开发期间，参与者将受到创新奖励制度的鼓励。此外，EMIA还提出将新加坡现有的LIDAR点云数据和Virtual Singapore转换为AIMU内可与人类和AI交互的高清结构。这种新方法可以更快地转换和更容易地自动同化和计算城市基础设施、海岸侵蚀、交通改道和洪水灾害中疏散的变化，特别是在易受气候变化影响的城市。最后，EMIA将在AIMU超结构中对交通大数据进行网格化，以实现同步和数据交互，从而使这种新形式的城市人工智能能够用于优化交通的半监督计算。这些努力实现了17项联合国可持续发展目标中的6项。拟议的项目为期2.5年，其最终产品可以立即添加到我们现有客户的产品列表中，或者通过其独特的普适性和可持续性成为一个独立的商业化实体。拟议中的项目由Citymatrix私人有限公司（新加坡）和Interactive Coventry有限公司（英国）共同努力，双方进行研发，相互技术转让和能力建设。

Extreme weather is an escalating urban issue while hundreds to thousands of screens showing traffic congestion with streams of pedestrians sprawling across. Can a smart city system flexibly react to every unique population and deal with impending urban flash floods?The missing keys are (i) knowing what happens on every road between the screens, (ii) how to make all these data relevant to human urban activity, habitat and climate change, and (iii) synchronize the data as intrinsically as hundreds of thousands of traffic coordinators coordinating in unison on every road, under rain sunshine or even flooding.The EMIA project is designed to do that. It is an extension from an AI forecasting urban flooding residing within a revolutionary superconstruct (AIMU). AIMU assimilates digital twin and makes it legible to AI, while staying geo-topologically accurate and relevant.Unlike conventional machine learning algorithms in traffic CCTV, EMIA proposes a refocus of implementing road safety standards by extracting human centric parameters from existing traffic CCTV, as well as extending the reach of information by incorporating and analyzing video footage transmitted from enrolled dashcams among frequent road users. The source of the footage will be anonymized, and any unsuitable footage will be automatically deleted prior to transmission. The participants will be encouraged by an innovative reward system during the development period.In addition, EMIA proposes AI-powered conversion of existing LIDAR points cloud data of Singapore and Virtual Singapore into a High-Definition structure that can be interactive with humans and AI within the AIMU. This new approach enables faster conversion and easier automatic assimilation and computation of change in urban infrastructure, coastal erosion, traffic diversion and evacuation in a flooding disaster especially in cities susceptible to climate change.Finally, EMIA will mesh the traffic Big Data in the AIMU superconstruct for synchronization and data interaction so that this new form of city AI will be useful for semi-supervised computation for optimized traffic. These efforts fulfil 6 of 17 United Nation Sustainable Development Goals.The proposed project is 2.5 years and its end product can be immediately added to our product offering to existing list of clients, or an independent entity commercializable by its unique universality and sustainability. The proposed project is a joint effort under the collaboration of Citymatrix Pte Ltd (Singapore) and Interactive Coventry Ltd (UK) with research and development conducted by both parties, mutual technology transfer and capacity building.