邀请函 | 中国深圳创新创业大赛第六届国际赛英国分站赛决赛

项目概要：

核心团队来自英国南安普顿大学与英国约克大学。Extend Robotics创建了一个基于虚拟现实的游戏化人机界面软件系统AMAS。它具有世界上最好的 3D 图形和流媒体引擎，目前已受理申请专利。它为普通用户提供了一种进入远程工作空间的直观方法，可以使用经济实惠的消费类 VR 设备，作为标准化界面来控制各种不同类型的第三方商用机械臂。它通过具有精确 3D 几何形状和灵活视角的沉浸式可视化，用户可以使用自然的手势控制和编程机器人，轻易地完成实时交互且长时间使用不会眩晕。

Project Summary: 

The core team members are from University of Southampton and University of York. The creation of AMAS, a virtual reality-based gamified human-machine interface software system featuring the world's best 3D graphics and streaming engine, currently the subject of a patent application. It provides an intuitive way for the average user to access remote workspaces, using affordable consumer VR devices, as a standardised interface to control different types of third party commercial robotic arms. Through immersive visualisation with precise 3D geometry and flexible viewing angles, users can control and program robots using natural gestures, easily interacting in real time and without dizziness over long periods of time.

项目概要：

CityMaaS是一家屡获殊荣的伦敦包容型科技型企业。CityMaaS旨在满足围绕残疾人群和老化人群的辅助性需求，同时协助公共和私营部门实现包容性需求。CityMaaS协助本地企业打开2740亿英国本地市场和8万亿美元全球市场，把握这些市场的消费能力和增长机会。CityMaaS在在移动地图平台、AssistMe插件和AWARE的数据上结合机械学习，协助目标人群独立生活。目前CityMaaS均有获得公共和私营部门的资助和支持，并已开始服务潜在和现有客户，包括HSBC, Moody’s, Motability, Oxford County Council, Valpi bus in Portugal, and PWC等机构。

Project Summary: 

CityMaaS is an award-winning inclusive technology company with patents based in London, established to address the needs of disabled people and ageing population, their friends, and families globally, whilst assisting the public and private sector, especially local businesses to be inclusive and to tap into the  274bn (UK) and $8trn (Globally) spending power and growth opportunity. We use machine learning and data on Mobility Map Platform, Assist Me plugin, and AWARE to enable independent living offline and online. CityMaaS is funded and supported by the public and private sectors. We have helped prospective and existing clients such as HSBC, Moody’s, Motability, Oxford County Council, Valpi bus in Portugal, and PWC.

项目概要：

Binumi国际有限公司为全球的企业提供视频技术和解决方案。该公司服务于许多行业的客户，包括教育、媒体、建筑、采矿和技术。 Binumi实现了视频创作和规模化，使企业能够以传统视频制作团队无法竞争的价格获得大量高质量的视频。 该业务通过其核心技术平台、视频故事专家和战略支持的结合来实现。这种组合使企业能够通过规模化的再利用（如地点、语言和分发渠道，如社交媒体）有效地利用所有内容。

Project Summary: 

Binumi International Limited provides video technology and solutions to businesses across the globe. The business services clients across many industries, including education, media, construction, mining and technology. Binumi’s enables video creation and scale, enabling businesses to access high quality video at high volumes at price points traditional video production teams cannot compete with. The business achieves through a combination of its core technology platform, expert video storytellers and strategic support. This combination enables businesses to make efficient use of all content by re-purposing at scale (e.g. locations, languages and distribution channels such as social media).

项目概要：

项目核心团队成员主要来自于英国阿伯丁大学和英国赫瑞瓦特大学。项目旨在打造国内首款以7-16岁青少年群体为目标用户，集在线编程，授课教学，代码开源，社交互动等一体的开放式激励性平台。平台同时支持PC H5端和移动端app（iOS/Android）。移动端突出社交性和便携性，主要以社交的方式，呈现学生使用不同编程语言设计的游戏作品（目前以Scratch编程为主，更加直观，互动性更强。）PC H5端提供丰富的功能，在线课程根据游戏开发流程的模式进行爬藤设计。平台内置了积分系统，学生可以根据不同的活动、行为、成就来获得积分，用积分换取相应的课程或者素材资源，借此保证学生在学习中获得的成就感，激发学习兴趣与动力。同时，为了方便学校或家庭对未成年人进行管理和监督，我们为不同的用户赋予具有不同权限的身份，例如老师，家长，学生和游客等。

Project Summary: 

The core team members of the project are mainly from the University of Aberdeen and Heriot-Watt University in the UK. The project aims to create the first open and inspiring platform in China that targets young people aged 7-16 and integrates online programming, teaching, open source code and social interaction. The platform supports both PC H5 and mobile apps (iOS/Android). The mobile end highlights social and portability, mainly in a social way, presenting students' game creations designed in different programming languages (currently, the main focus is on Scratch programming, which is more intuitive and interactive.) The PC H5 end offers a wealth of features and the online course is designed to climb the vine based on the model of the game development process. The platform has a built-in points system, where students can earn points based on different activities, behaviours and achievements, and exchange them for corresponding courses or material resources, thereby ensuring that students gain a sense of achievement in their learning and stimulating their interest and motivation. At the same time, in order to facilitate the management and supervision of minors by schools or families, different users are given different identities with different rights, such as teachers, parents, students and visitors.

项目概要：

核心团队由伦敦国王大学和利兹大学的毕业生组成。Ohbot和Picoh机器人被设计为学习的工具。这些机器人没有内置编程行为，使用团队开发的块状编程软件或儿童起草的Python代码来开发程序，使机器人实现 "动"、"说"、"看 "和 "听"等一系列功能。一个全面的学习活动计划提供了从简单的单一动作到包括自然语言处理、生成、生物模拟运动和机器学习的程序的进展。电路结构已经最终确定，团队有功能齐全的原型打印件。控制板的驱动软件已经开发完毕，并与主机应用程序集成。主机应用程序已被修改以适应编程。团队已经完成计算了将设计从原型转向生产版本所需的工作成本，并计划进一步量产。

Project Summary: 

The core team consists of graduates from King's University London and the University of Leeds.Ohbot and Picoh robots are designed as tools for learning. The robots come without programmed behaviour, instead using block programming software that we have developed or Python code children draft to iteratively develop programs that make the robots 'move', 'speak', 'see' and 'hear'. A comprehensive scheme of learning activities offers progression from simple single movements to programs that can include natural language processing, generation, biomimetic movement, and machine learning.We have partially completed the development of Picoh AI. The circuit architecture has been finalised and we have fully functional prototype prints. The control board driver software has been developed and integrated with the host application. The host application has been modified to accommodate programming. We have costed the work needed to move the design from prototype to production version and are confident that it is achievable.   

项目概要：

核心团队来自英国林肯大学助理教授、博导、GAI 实验室主任及德国慕尼黑工业大学计算机学院机器人、人工智能与实时系统研究所博士组成。项目基于团队研发最先进人工智能算法，计算机视觉技术及实时控制技术，针对解决精细农业中定点除草技术难题。所开发的系统可以在田间复杂环境下自主式行驶导航，并精准识别杂草/作物，然后通过视觉伺服控制算法管理末端执行喷头阀门精准对靶处理杂草，从而达到精准除草，保障作物高产高质。使用该系统不仅大量减少农药(节省>80%药量)投入的花费，还降低了化学药剂对地下及地表水源污染，保障自然/人类/动物/食品的安全。

Project Summary: 

The core team members are from Assistant Professor, PhD, Director of GAI Lab, University of Lincoln, UK and PhD from Institute of Robotics, Artificial Intelligence and Real-Time Systems, Institute of Computer Science, Technical University of Munich, Germany. The project is based on the team's development of state-of-the-art artificial intelligence algorithms, computer vision technology and real-time control technology, and is aimed at solving the technical problems of spot weeding in fine agriculture. The developed system can navigate autonomously in the complex environment of the field, and accurately identify weeds/crops, and then manage the end-effector valves to precisely target weeds through vision servo control algorithms, thus achieving precise weeding and ensuring high crop yield and quality. The use of the system not only greatly reduce the cost of pesticide (save > 80% of the amount of medicine) inputs, but also reduce the chemical pollution of underground and surface water sources, to protect the safety of nature / human / animal / food.

项目概要：

核心团队来自伦敦国王学院博士组成。团队拥有源自于国际首个研发成功的基于光学原理的扭矩传感技术的技术优势。该技术首次实现了应用非激光光源对微米级别材料形变的测量，实现了旋转扭矩的精确测量。该传感原理融入了针对性开发的特殊传感结构，在保证各项物理参数的同时降低了整体结构限制；使用了特制光学芯片，确保了传感单元的稳定性并降低了系统误差。因而，使用该原理的传感器，可以具备精度高，成本低，可靠性高等特征。同时传感器的结构在理论上也可以极小，极薄。基于该原理的旋转扭矩传感器将打破现有技术在精度，结构大小及测量范围上的极限。团队瞄准要求较低但需求量较大的助力自行车市场，拟解决助力自行车旋转扭矩传感器的成本及稳定性问题；其次将业务扩展至电动汽车领域，选择一两家电动汽车头部企业，针对几款高端车型定制化开发车轮实际扭矩监控传感器，然后扩大生产规模，降低成本，下放至中低端车型；最后将业务扩展至工业及协作机器人领域，为机器人关节提供动态扭矩传感，提升机器人可靠性与柔性。

Project Summary:

The core team consists of PhDs from King's College London. The team has technological strengths derived from the first successful international development of a torque sensing technology based on the optical principle. For the first time, this technology enables the measurement of material deformation at the micron level using a non-laser light source, enabling the precise measurement of rotational torque. The sensing principle incorporates a specially developed sensing structure that reduces the overall structural limitations while maintaining all physical parameters, and the use of special optical chips ensures the stability of the sensing unit and reduces system errors. The use of special optical chips ensures the stability of the sensing unit and reduces system errors. As a result, sensors using this principle can be characterised by high accuracy, low cost and high reliability. The sensor structure can also be theoretically extremely small and thin. A rotary torque sensor based on this principle will break the limits of existing technology in terms of accuracy, structure size and measuring range. The team aims to solve the cost and stability problems of rotational torque sensors for bicycles, which have low requirements but high demand. Finally, we will expand our business to industrial and collaborative robots, providing dynamic torque sensing for robot joints to improve robot reliability and flexibility.

项目概要：

核心团队负责人毕业于伦敦大学学院，现任英国伦敦玛丽女王大学化学系讲师、博士生导师。在大力发展光伏产业的政策背景下，面对传统的清洗方式难以适应光伏运维的发展的痛点，本项目提供了一种无氟、高透光度、高机械强度、固态超滑表面涂层的自洁净方案。产品形式主要为高性能固态超滑表面抗污涂层，主要用于光伏玻璃表面自清洁等技术领域。具体使用方法：可通过浸渍、刷涂、喷涂等常规技术，将涂料涂覆在光伏玻璃表面，再经过热固化，形成高性能光伏玻璃自清洁涂层。项目已完成实验室研发和测试，处于产品开发阶段。

Project Summary:

The core team leader graduated from University College London and is currently a lecturer and PhD supervisor in the Department of Chemistry at Queen Mary University of London, UK. Under the policy background of vigorous development of the photovoltaic industry in China, facing the pain point that traditional cleaning methods are difficult to adapt to the development of photovoltaic operation and maintenance, this project provides a fluorine-free, high permeability, high mechanical strength, solid-state super-slick surface coating for self-cleaning solutions. The product is mainly in the form of a high-performance solid-state super-slip surface anti-fouling coating, mainly used in the technical field of self-cleaning of photovoltaic glass surfaces. Specific use: the coating can be applied to the PV glass surface through conventional techniques such as dipping, brushing and spraying, and then heat cured to form a high performance PV glass self-cleaning coating. The project has completed laboratory development and testing, and is in the product development stage.

项目概要：

核心团队成员来自新加坡国立大学、英国牛津布鲁克斯学院、加州大学伯克利分校、清华大学。项目采用自主研发的在纳米孔隙下通过改变温度及湿度的条件下进行可逆化碳捕捉技术与自主研发的MS-019碳捕集分离膜材料，为工业及能源类碳排放企业提供碳减排、碳达峰等技术解决方案。经过规模化成本核算每吨捕集成本在40-45元人民币区间，远低于国际上的醇胺溶液处理技术，并方便可以进行液态或固态化封存处理。目前公司相关产品与技术已应用到中石化南京研究院、中国神华包头煤化工项目、华润海丰电力项目中。

Project Summary: 

The core team members are from the National University of Singapore, Oxford Brookes College, University of California, Berkeley and Tsinghua University. The project adopts self-developed reversible carbon capture technology by changing the temperature and humidity under nano-pore conditions and self-developed MS-019 carbon capture and separation membrane material to provide carbon emission reduction and carbon peaking technology solutions for industrial and energy companies. The cost per tonne of capture is RMB 40-45 per tonne, which is much lower than the international alcohol-amine solution treatment technology, and can be conveniently processed in liquid or solid state. The company's products and technologies have been applied to Sinopec Nanjing Research Institute, China Shenhua Baotou Coal Chemical Project and China Resources Haifeng Power Project.

项目概要：

核心团队负责人来自英国帝国理工学院。Synced利用自行开发的Synced仪表盘，致力于服务关注环境和社会问题的人群并提高公众的环保意识，公众可以使用仪表盘进行查询地理环境相关情况，比如该地区适合进行的户外活动、地区历史或者对即将搬去的新城市环境。Synced的用户还可以用其他创意性的方式来定制化属于自己的地图。仪表板上的数据是通过向现有Synced应用程序的用户发布基于加密货币的奖励来收集资料的。用户添加合格的数据，标记地图后会得到相应奖励.目前Synced正在扩展完善奖励系统，以拓展收集其他类型的数据，包括航空图像和物联网（IoT）数据。为此，Synced正在创建并提供开源硬件，如污染传感器和其他测量设备，以实现数据的自动上传。

Project Summary: 

The core team members are from Imperial College London.Synced builds tools for people to crowdfund & crowdsource geospatial data for the places they care about. Our dashboards will be used to highlight environmental and social matters like pollution, broken infrastructure, crime & safety and open waste dumping. Individuals will also use dashboards for research - for outdoor hobbies, local history or to get a feel for a place they’re looking to move to. They can also be used in all sorts of other creative ways to make updating maps of the things that interest you. Data on a dashboard is crowdsourced by issuing cryptocurrency-based bounties to users of the existing Synced apps, who then mark things matching the bounty. Qualifying marks are added to the dashboard, and the marker is paid a share of the bounty. The team will extend the bounty system to provide more types of data including aerial imagery and Internet of Things (IoT) data. To do this, the team will be creating and offering open-source hardware such as pollution sensors and other measurement devices that will be able to automatically upload data to dashboards.

项目概要：

核心团队负责人为伦敦大学学院博士。项目主营业务为微波催化降解PET塑料至BHET单体产物。团队预计3个月左右申请国际专利技术，并在接下来的六个月内消化在英国开发的国际专利技术，初步在国内形成大批量降解回收PET塑料的能力，在12个月内将将废弃PET塑料的处理能力提升至十吨到百吨级，回收的BHET单体产量提升至十吨到百吨级。5年内在化学法回收降解PET塑料并生产再生PET塑料领域占有1％左右的市场份额（全球到2025年的PET塑料产值预计超过200亿美元），直接产值超过1亿美元（6.5亿人民币）。

Project Summary:

The core team leader is a PhD from University College London. The main business of the project is microwave catalysed degradation of PET plastics to BHET monomer products. The team expects to apply for the international patent technology in about 3 months and to digest the international patent technology developed in the UK within the next 6 months, to initially develop the capacity to degrade and recycle PET plastics in large quantities in China, and to increase the processing capacity of waste PET plastics to 10 to 100 tons and the production of recycled BHET monomer to 10 to 100 tons within 12 months. Within 5 years, the company will have a market share of about 1% in the field of chemically recovered degraded PET plastics and produce recycled PET plastics (the global output value of PET plastics is expected to exceed US$20 billion by 2025), with a direct output value of over US$100 million (RMB650 million).

项目概要：

核心团队负责人为英国布里斯托大学博士。HUD结构预期增加光伏面板3％-5％发电量，基于成熟上下游制备工艺，成本可控。技术对标太阳光谱，不受产品技术路线换代影响，兼容性强。项目的切入点放在一种光伏表面制绒工艺，但后续可用于多种表面结构制备领域的应用。项目符合国家十四五规划与碳中和目标。

Project Summary:

The core team leader is a PhD from University Bristol.The HUD structure is expected to increase the power generation of photovoltaic panels by 3-5% and is based on a mature upstream and downstream production process with controllable costs. The technology is aligned to the solar spectrum and is not affected by product technology line changes and is highly compatible. The project's entry point is placed in a photovoltaic surface fleece making process, but subsequently can be used for a variety of applications in the field of surface structure preparation. The project is in line with the national 14th Five-Year Plan and carbon neutrality targets.

项目概要：

核心团队负责人来自皇家艺术学院的软系统纺织专业。lokaReboon是一种由回收的天然橡胶气球制成的可持续和生态友好的创新未来材料。团队使用回收的彩色乳胶气球作为原材料，在保留气球本身丰富色彩的同时，兼具出色的材料强度和耐磨性，使用寿命极长。此外，在lokaReboon的制作过程中不需要二次染色，不产生二次工业废水。

Project Summary:

The core team leader is from the Royal College of Art, majoring in Textiles-Soft Systems. lokaReboon is an innovative, sustainable and eco-friendly future material made from recycled natural rubber balloons. The team uses recycled coloured latex balloons as the raw material, which retains the richness of the balloons' colours while providing excellent material strength and abrasion resistance for a long life. In addition, no secondary dyeing is required in the production of lokaReboon and no secondary industrial waste water is generated.

项目概要：

与基因及蛋白组学类似，细胞力是一大类全新的组学，更是一片未开发的巨大蓝海。Cell4D是全球首款基于细胞力组学的单细胞辨识及分选平台，堪称细胞的"人脸识别"。细胞是生命的基础，更是破解每一种疾病的钥匙。作为一款平台型技术，Cell4D与国际药企巨头合作，将细胞力组学应用于精准医疗，药物发现及细胞疗法，每个领域的成功都将开拓百亿美元的市场蓝海。例如我们的生物芯片可将肿瘤诊断分型的精度提高两个数量级的同时降低九成以上的时间及成本，更能在数分钟内辨识耐药细胞以助力精准医疗。此外基于细胞力组学无创无标记的特点，可实时监控细胞状态及分化，为细胞疗法（如CAR-T等）赋能。作为全球首款实时，高通量，低成本的细胞力学芯片，Cell4D可针对每一种疾病，高效采集细胞力指纹特征数据库，人类细胞力指纹库的意义和重要性不亚于人类基因组数据库，结合人工智能，将驱动生命科学的数字革新。项目Top 12入选默克加速器，Top 1%入选奇绩创坛（前YC中国），作为唯二两家中国企业之一入选全球最大的生命科学加速器MedTech Innovator APAC并斩获2022 Beyond生命科学大奖。核心团队成员来自瑞士苏黎世联邦理工大学、苏黎世大学，巴塞尔大学及荷兰乌得勒支大学。

Project Summary:

Cell4D is the world's first single cell identification and sorting platform based on cellular forceomics, which is the "face recognition" of cells. Cells are the foundation of life and the key to deciphering every disease. As a platform technology, Cell4D has partnered with international pharmaceutical giants to apply cellular forceomics to precision medicine, drug discovery and cellular therapies, with success in each of these areas opening up a $10 billion market. For example, our biochips can increase the accuracy of tumour diagnostic typing by two orders of magnitude while reducing time and cost by over 90%, and can identify drug-resistant cells within minutes to facilitate precision medicine. In addition, based on the non-invasive and label-free nature of cellular forceomics, cell status and differentiation can be monitored in real time, enabling cellular therapies such as CAR-T. As the world's first real-time, high-throughput, low-cost cellular mechanics chip, Cell4D can efficiently collect cellular force fingerprinting database for each disease, which is as significant and important as the human genome database and will drive digital innovation in life sciences when combined with artificial intelligence. The project was selected as one of the top 12 companies in the Merck Accelerator, one of the top 1% in the Qiji Venture Forum (formerly YC China), and one of only two Chinese companies to be selected for the MedTech Innovator APAC, the world's largest life science accelerator and winner of the 2022 Beyond Life Science Award. The core team members are from ETH Zurich, University of Zurich, University of Basel and Utrecht University in the Netherlands.

项目概要：

核心团队来自剑桥大学。Senzo成功开发了全球独创的ALF + MAP体外诊断快速检测系统平台。ALF用于快速低价定性检测，MAP用于临床定量检测。两者既可以单独使用，也可以结合使用，形成一个完整的系统，进行精确的定量检测。它们也可以根据所使用的环境独立使用。Senzo的存在是为了以一种新颖、经济的形式给世界带来更好的医疗点和家庭检测解决方案。

Project Summary:

The core team members are from University of Cambridge. Senzo has successfully developed the world’s original ALF plus MAP in vitro diagnostic rapid test system platforms. ALF is used for qualitative detection and MAP is used for quantitative detection. The two can be used in combination to form a complete system that allows accurate quantitative detection; they can also be used independently depending the environment that they are used in. Senzo exists to bring to the world better point-of-care and at-home testing solutions, in a novel, cost-effective format.

项目概要：

核心团队成员来自英国牛津大学、韩国浦项工科大学。目前项目的研发阶段已结束，处在孵化阶段。因植物反应器平台建设前期投入低，仅需适宜的温室和常规的纯化和检测平台，设备依赖性不强，可在短时间内完成平台的设立，并可在平台建立完成后迅速投入生产以推动相关产品进入中试阶段，具有极强的产业化前景。基于植物的疫苗生产平台跳过了工程化动物细胞长达几个月的筛选和密集劳动阶段，在拿到新型病毒基因后可于几周内完成第一批候选疫苗的生产，具有快速应对新型突发疫情的能力。该团队自主研发的“基于植物生产的‘绿色’疫苗及其佐剂纯化一体化平台“，通过自主研制的天然肽聚糖纳米颗粒（NPN）纯化并展示植物源重组抗原蛋白，将其免疫原性提高500多倍，仅需一棵转化后的本生烟植物便可纯化出足够30人用量的纳米颗粒流感疫苗或者足够300只家禽用量的纳米颗粒禽流感疫苗。该疫苗生产平台广泛适用于包括流感病毒、新冠病毒、艾滋病病毒、埃博拉病毒、呼吸道合胞病毒等在内的多种包膜病毒，接种方式适用于肌注和鼻黏膜接种。

Project Summary:

The core team members are from Oxford University, UK and Pohang University of Technology, Korea.The R&D phase of the project is now complete and is in the incubation phase. The plant-based reactor platform can be set up in a short period of time and can be rapidly put into production after the platform has been established to drive the relevant products into the pilot phase, with strong prospects for industrialisation due to the low upfront investment in the construction of the platform, which only requires a suitable greenhouse and a conventional purification and testing platform, with little equipment dependency.The plant-based vaccine production platform can skip the months-long screening and intensive labour phase of engineered animal cells, and the first batch of vaccine candidates can be produced within a few weeks after the novel virus genes are available, with the ability to respond quickly to new outbreaks. The team's self-developed "integrated platform for the purification of plant-based 'green' vaccines and their adjuvants" purifies and demonstrates plant-derived recombinant antigenic proteins through the development of natural peptidoglycan nanoparticles (NPN), increasing their immunogenicity by more than 500 With the NPN, it is possible to purify enough nanoparticle influenza vaccine for 30 people or enough nanoparticle avian influenza vaccine for 300 poultry with just one transformed native tobacco plant. The vaccine production platform is suitable for a wide range of enveloped viruses, including influenza, neocoronavirus, HIV, Ebola, respiratory syncytial virus, etc., and can be administered by intramuscular injection and nasal mucosal vaccination. 

项目概要：

通过捕获碳排放作为浮游生物养殖场的原料，从而达到以下效益：确保鱼类繁殖和生长的理想条件，以协助减轻鱼类资源的压力；利用部分浮游生物为养鱼场，以减轻野生海洋鱼类的压力；直接减少大气中温室气体二氧化碳的含量，以减缓全球变暖的速度；增加海洋中进行光合作用的浮游生物的数量，这将加速二氧化碳的自然捕获进入海洋食物链，从而间接地进一步减少大气中的二氧化碳数量。

Project Summary:

SEAQuest realizes this and takes a different approach to the problem of food security, global warming and climate change. We seek to productively utilize carbon as a feedstock and reintroduce it into the global environment, rather than just lock away this precious resource which is essential for maintaining the biodiversity of species on the planet. SEAQuest proposes a complete solution by capturing carbon emissions as feedstock for plankton farms, thereby: helping to alleviate the pressure on fish stocks by ensuring ideal conditions for the breeding and growing of fish species; reducing the pressure on wild oceanic fish stocks by utilizing some of the plankton for fish farms; directly reducing the amount of the greenhouse gas, carbon dioxide, in the atmosphere to reduce the rate of global warming; increasing the amount of photosynthesizing plankton in the ocean which will accelerate the natural capturing of carbon dioxide into the oceanic food chain, thus indirectly further reducing the amount of carbon dioxide in the atmosphere.The project will be financed through the proven economic potential of marine farming, as well as with carbon credits due to the reductions in carbon dioxide emissions.

项目概要：

核心团队负责人来自英国萨里大学，研究聚焦于结构健康监测与数字孪生。创业项目计划综合结构工程、人工智能、传感器等多学科交叉方法，为海洋基础设施结构提供数字孪生云平台服务，变革传统基础设施运维的范式。预期成果将提升结构安全性、可靠性和运维效率，降低运维成本，延长使用寿命。此方向在能源产业、海洋经济、创新科技和基础设施等领域拥有较高的战略地位，将为我国实现2030年碳达峰、2060年碳中和的目标提供重要支撑。

Project Summary:

The core team leader is from the University of Surrey and his research focuses on structural health monitoring and digital twin. The project plans to integrate multidisciplinary intersectional approaches such as structural engineering, artificial intelligence, and sensors to provide digital twin cloud platform services for marine infrastructure structures, transforming the paradigm of traditional infrastructure O&M. The expected results will improve structural safety, reliability and O&M efficiency, reduce O&M costs and extend service life. This direction has a high strategic position in the fields of energy industry, marine economy, innovative technology and infrastructure, and will provide important support for China to achieve the goal of carbon peaking by 2030 and carbon neutral by 2060.