Faster and Higher-Precision Mobile Mapping through AI

通过AI实现更快、更高精度的移动地图绘制。这一挑战与海克斯康的信念一致，即铁路行业的真正现代化在于自动化行业内常见的各种工作流程。为了应对铁路专业人员面临的日常挑战，海克斯康一直在探索并开始开发移动地图的概念：在火车上安装一个传感器，在正常的轨道速度下捕获定性数据，可用于之后的不同分析。潜在的应用是无穷无尽的！海克斯康是硬件和软件解决方案开发的先驱和市场领导者，这些解决方案已经使移动地图的一些潜力得以释放。“Pegasus:Two”传感器捕获高质量的点云数据，而“Rail:Factory”软件用于释放捕获数据的潜力。毫不奇怪，Pegasus:Two和Rail:Factory目前已经在全球铁路行业的几个生产环境中使用。移动地图是一个不断改进的过程：我们在硬件和软件方面都在努力改进。硬件不断改进，以便在赛道上骑行时捕捉更多细节；Rail:Factory通过不断增强其功能和开发新功能来改进。在这个项目中，我们的目标是通过深入使用人工智能（AI）来实现性能和结果的重大改变。目前，Rail:Factory已经能够在一定程度上对结构和对象进行分类。在这场竞赛中，我们关注的创新将是增加我们软件的智能。我们将训练软件，以获得比目前可以发现的粗略类别更详细的分类。当我们实现这一目标时，移动地图的潜力将大大增加。与能够捕捉更多细节的更强大的传感器携手并进，智能软件利用捕捉到的数据，从长远来看，可以迅速发现任何潜在的风险，如桥梁受损、路堤塌陷或铁轨附近的植被被侵占，并主动向维护团队发出信号。在海克斯康，我们相信移动地图的未来就在那里：快速捕获数据，不会造成任何延迟或危及任何人的生命，同时快速利用捕获的数据，使用这些数据的自动化过程有助于铁路人员发现最紧迫的问题，确定优先级并保持高质量的铁路基础设施

Faster and Higher-Precision Mobile Mapping through AI. This challenge is in line with Hexagon's belief that a true modernisation of the rail industry lies in automating the various workflows that are common within the industry. To deal with the daily challenges that rail professionals are facing, Hexagon has been exploring and started developing the concept of mobile mapping: a sensor is installed on a train and at normal track speed qualitative data is captured which can be used for different analysis afterwards. The potential applications are endless! Hexagon is a pioneer and market leader in the development of both hardware and software solutions which already allow some of this potential of mobile mapping to be unlocked. The "Pegasus:Two" sensor captures high qualitative point cloud data whereas the "Rail:Factory" software is used to unlock the potential with the data that is captured. Not surprisingly both Pegasus:Two and Rail:Factory are currently already used in several production environments within the Rail Industry across the globe. Mobile mapping is a process that is subject to continuous improvement: both in our hardware and software we strive to improve. The hardware is continuously improved to capture more details while riding on the track; Rail:Factory is improved by continuously enhancing its capabilities and developing new features. For this project we aim to make a major step change in performance and outcome through in depth use of Artificial Intelligence (AI). Currently Rail:Factory is already able to classify structures and objects to a certain extent. The innovation we'll focus on during this competition will be to increase the intelligence of our software. We will train the software to derive more detailed classifications than the rough categories which currently can be discovered. When we achieve this there will be a major increase in the potential of mobile mapping. Hand-in-hand with more powerful sensors which can capture more detail, the intelligent software that uses the captured data can in the long run swiftly detect any potential risks like a damaged bridge, slumping embankment or encroaching vegetation near the tracks and signal this pro-actively to the maintenance teams. At Hexagon we believe the future of mobile mapping lies exactly there: data is captured swiftly and without causing any delays or putting any lives at risk, while quickly utilising the data as captured, automated processes using this data assist the Rail personnel to detect the most imminent problems, to prioritise and to maintain a highly qualitative rail infrastructure