InDePTH - Intelligent Drones for Ports and Highways Technology

我们对英国基础设施未来的愿景包括由可再生能源提供动力的无人机系统(UAS)机队，以在搜索和救援以及高速公路维护等高成本领域提供更高效的应用和流程，同时减少目前因道路封闭等中断而造成的经济影响。此外，在此类操作中使用UAS可以显著减少它们的碳足迹。这一愿景将在2025年之前大规模实现。深度项目将调查使用自主无人机来实现这一愿景。这架飞机将用于定期测量包括港口和高速公路在内的广泛基础设施产业，以创建数字模型并获得对这些动态环境的详细了解。深度将利用机载传感、数据和图像处理设备来自主无人机，目前以盒式无人机(DIAB)解决方案提供。目前的DIAB产品包括为任务量身定做的传感设备和最少的人工输入和监督，但缺乏端到端和实时数据分析集成。今天的戴铂解决方案需要在任务完成后进行长时间的手动数据卸载，这使得实时分析变得不可能。当前Diab解决方案的另一个限制是数据卸载通常没有与分析软件完全集成，需要使用基于云的数据仓库。该项目旨在快速跟踪数据传输，同时提供增强的接近实时的AI分析。深度将使用RoboK开发的最先进的机器学习(ML)算法来增强无人机数据分析，创建优化的图像处理，旨在为3D数字孪生兄弟建模环境。英国电信将通过探索使用快速可靠的5G和光纤链路以低延迟传输Diab数据，提供安全和快速的数据传输设备。将开发三个演示程序，以支持联合英国港口(ABP)和基尔高速公路的关键用例。由于人员、车辆和货物的不断流动，港口和公路环境变化迅速。对于港口，确定了两个关键用例：深度项目将调查总部基地港口使用无人机改善库存管理的情况，重点是车辆库存；此外，总部基地将在第二个项目演示中使用无人机进行离岸监视和海上行动。第三，在高速公路领域，深度公司将考虑部署无人机来持续评估高速公路的地面质量，为基尔。

Our vision for the future of UK infrastructure encompasses fleets of unmanned aircraft systems (UAS) powered by renewable energy to deliver more efficient applications and processes in high cost areas such as search and rescue and highway maintenance, whilst reducing the economic impact currently caused by interruptions such as road closures. Additionally, using UAS in such operations can significantly reduce their carbon footprint. This vision will be delivered by 2025 at scale.The InDePTH project will investigate the use of autonomous drones to deliver this vision. The aircraft will be used to regularly survey wide infrastructure estates, including ports and highways, to create digital models and obtain detailed insight of these dynamic environments. InDePTH will utilise onboard sensing, data and image processing equipment to autonomous drones, currently available as drone-in-a-box (DIAB) solutions.Current DIAB offerings include mission-tailored sensing equipment and minimal human input and supervision but lack end-to-end and real-time data analytics integration. DIAB solutions today require lengthy manual data offloading after missions, making real-time analytics impossible. Another constraint of current DIAB solutions is that data offloading is typically not fully integrated with analytics software, requiring the use of cloud-based data lakes.The project aims at fast-tracking data transport while providing enhanced AI analytics near real-time. InDePTH will augment the drone data analytics using state-of-the-art machine learning (ML) algorithms developed by RoboK, creating optimised image processing aiming at modelling environments to a 3D digital twin. BT will provide secure and fast data transport equipment by exploring the use of fast and reliable 5G and fibre links to transmit DIAB data with low latency.Three demonstrators will be developed to support critical use cases for Associated British Ports (ABP) and Kier Highways. Port and highway environments change rapidly due to constant movement of people ,vehicles and goods. For ports, two key use cases are identified: InDePTH will investigate the use of UAS to improve inventory management for ABP ports, focusing on vehicle inventory; furthermore, ABP will use drones in their off-shore surveillance and maritime operations in the second project demonstrator. Thirdly, in the highways area, InDePTH will look at deploying UAS to continuously assess the ground surface quality of highways, for Kier.