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Flock: the world's first Big-Data driven risk analysis tool for drone flights

Flock: the world's first Big-Data driven risk analysis tool for drone flights
Flock:世界上第一个大数据驱动的无人机飞行风险分析工具
批准号:
102991
负责人:
金额:
$8.63万
依托单位:
依托单位国家:
英国
项目类别:
Feasibility Studies
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --
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项目摘要

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中文摘要
翻译
无人机行业正在迅速发展;无人机的使用案例越来越多,从在公园飞行的爱好者到监视,数据收集和包裹递送等商业运营。到2020年,无人机将成为一个价值1270亿美元的产业。然而,无人机也带来了一定程度的风险;从空中坠落到拥挤的地区,环境干扰和公共空间的隐私问题,仅举几例。人们越来越需要能够识别、量化和最小化无人机飞行风险的技术。这正是我们在弗洛克正在建设的,这是这个创新英国赠款将支持的项目。Flock是世界上第一款同类软件:我们的人工智能平台可以真实的跟踪人员、车辆、建筑物、天气系统等的位置,计算无人机在拥挤的城市环境中飞行的最安全飞行路径。我们的软件对保险公司、运营商、政策制定者和UTM至关重要,因为它有助于保护公众免受高空无人机的伤害,同时允许运营商智能地安排和安排航班,以最大限度地降低风险。我们独特的方法是聚合多个数据源,并使用机器学习和路径优化算法来真实的生成最佳飞行路径,使运营商能够当场量化并最大限度地降低飞行风险。该项目汇集了世界领先的专家,设计和构建一项技术,该技术将成为全球无人机安全的事实标准,并使英国成为无人机安全标准的先驱。
英文摘要
The drone industry is growing rapidly; there are an increasing number of use cases for drones, from hobbyists flying in the park, to commercial operations such surveillance, data gathering and parcel delivery. Drones will be a $127 billion industry by 2020. However, drones bring with them a degree of risk; falling out of the sky into congested areas, environmental disturbance and privacy concerns in public spaces, to name a few. There is a growing need for technologies that can identify, quantify and minimise the risk of drone flights. That's exactly what we're building at Flock, and it is the project that this Innovate UK grant will support. Flock is the first software of its kind anywhere in the world: our Artificial Intelligence platform tracks in real time the position of people, vehicles, structures, weather systems and more, calculating the safest possible flight-paths for drones to fly through congested urban environments. Our software is essential for insurers, operators, policy-makers, and UTMs, as it helps to keep the public safe from overhead drones, whilst allowing operators to intelligently schedule and route their flights to minimise risk. Our unique approach is to aggregate multiple data sources and use machine learning and path optimisation algorithms to generate optimal flight paths in real time, allowing operators to quantify and minimise flight risks on the spot. This project brings together world-leading experts to design and build a technology that will become the de-facto standard of drone safety globally, and make the UK a pioneer in drone safety standards.
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国内基金
海外基金
国际心脏研究会第二十三届世界大会(XXIII World Congress ISHR)
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    81942001
  • 项目类别:
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  • 资助金额:
    10万元
  • 批准年份:
    2019
  • 负责人:
    朱毅
  • 依托单位:
相对论中的薄球壳模型及其在宇宙论中的应用
  • 批准号:
    10605006
  • 项目类别:
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  • 资助金额:
    20.0万元
  • 批准年份:
    2006
  • 负责人:
    高思杰
  • 依托单位:
利用结构特性分析和控制动态布尔网络
  • 批准号:
    60574067
  • 项目类别:
    面上项目
  • 资助金额:
    23.0万元
  • 批准年份:
    2005
  • 负责人:
    赵千川
  • 依托单位:
探讨复杂动力网络的同步能力和鲁棒性