AI-driven and real-time command and control centre for site equipment in infrastructure projects

现场设备和设备(P&E)，特别是重型土方设备，如挖掘机、推土机和卡车，是建筑项目的主要成本要素，从商业项目的10%到高速公路、铁路线和能源项目等重大基础设施项目的50%不等。P&E是经常涉及项目延误的关键资源，也是造成场内/场外拥堵和空气污染的主要因素(例如，它们贡献了伦敦高达7%的NOx排放)。该财团先前在HS2内进行的研究显示，利用率低至30%；工作包之间的设备要求交叉导致设备重复/冗余三到五倍，现场拥堵导致H&S风险和不必要的超支。长期以来，P&E一直是一个主要盲点。随着未来10年6,000亿GB的公共和私人基础设施投资计划(TIP，2017)，有一个重要的机会来解决这个生产力问题，并开发一个国际领先的基于英国的解决方案。在成功的可行性研究之后，我们测试了从现场P&E收集实时数据并使用机器学习来估计现场设备的生产率，该项目旨在通过开发和测试第一个用于基础设施项目中的现场设备的人工智能驱动的实时指挥和控制中心，将我们的解决方案推进到工业研究阶段。该项目将通过开发新型的数字信息管理、工具、系统和标准“(即通过我们在人工智能支持下的指挥和控制仪表盘)和”分析、基准和度量“(即通过生成建筑土方基准数据)。

Site plant and equipment (P&E), particularly heavy earthmoving equipment such as excavators, bulldozers and trucks represent a major cost element in construction projects ranging from 10% in a commercial project up to 50% in major infrastructure projects such as highways, rail lines and energy projects. P&E are a critical resource that is often involved in project delays, and a major contributor to on/offsite congestion and air pollution (for example, they contribute up to 7% of London's NOx emissions).Previous research by the consortium within HS2 showed that utilisation rates are as low as 30%; crossover of equipment requirements between work packages causing three to five times equipment duplication/redundancy, and site congestion resulting in H&S risks and unnecessary overspend.Site P&E has been a major blind spot for a long time. With £600 billion of public and private infrastructure investment planned over the next 10 years (TIP, 2017), there is a significant opportunity to address this productivity issue and develop an internationally leading UK-based solution.Following the successful feasibility study where we have tested the collection of live data from site P&E and used machine learning to estimate productivity of site equipment, this project aims to advance our solution into the industrial research stage by developing and testing the first of its kind AI-driven and real-time command and control centre for site equipment in infrastructure projects.The project will contribute to the Transforming Construction ISCF Programme through the development of novel "digital information management, tools, systems and standards" (that is through our command and control dashboard supported with AI) and "analytics, benchmarking and metrics" (that is through the generation of construction earthwork benchmark data).