Intelligent Data & Environmental Analytics (IDEA)

点击翻译按钮获取中文摘要

Qflow is the first machine learning powered tool for predicting environmental impacts during engineering and operational works. Environments around railway works, stations and depots are currently at risk of dangerous air quality levels, noise pollution, inefficient resource consumption and local disruption to passengers and stakeholders. Many of these impacts can be avoided through access to real-time data and understanding the causes of these key risks. Over £6bn per year is spent trying to tackle these environmental impacts by the construction industry in the UK, through programme delays and cleaning up when things go wrong in relation to mis-managed environmental risks. This is also mirrored in the rail sector, through station upgrade works and operations, railway engineering and depot operation. A new software for monitoring and forecasting these risks based on data collected at source has demonstrated technical feasibility in the building sector, recognized and awarded by multiple industry bodies including the Royal Academy of Engineering, NCE Techfest, LWARB and the Major of London’s Clean Tech campaign. This project will focus on creating a real-time platform for gathering environmental data and analyzing this against programme activities to predict upcoming exceedances. It will be delivered in partnership between Qflow and Skanska Costain Strabag JV (SCSJV), with High Speed 2 (HS2) acting as the project demonstrator, where the southern sections on the new HS2 route between Euston station and West Ruislip will be used to demonstrate how machine learning can be applied to predict critical environmental risks; to enable a safer, cleaner way of working and preventing disruption to local communities and passengers. “SCSJV are interested in pursuing a commercial agreement for using Qflow in order to minimize impacts on the local environment and communities. We are therefore keen to work with Qflow to trial a new way of monitoring and managing our activities.” Following project testing, the opportunity exists to deploy the Qflow system onto multiple other sections along the HS2 route, and enter other contracts involved with station upgrade works. The project will be used to validate technical feasibility in a live railway environment, as well as develop the longer term commercial model for expansion into the rail sector.