Aquila

Aquila is a new digital tool for monitoring, managing and predicting the performance of plant equipment on site. By combining BIM and 4D scheduling, Aquila will improve construction project productivity and sustainability in real-time.

Reimagining onsite productivity with Aquila
Home / Work / Aquila

Client

Aquila

Location

London, UK

Services

Research, Digital Technologies

Sector

Infrastructure

2 min read

Plant equipment, particularly heavy earthmoving equipment such as excavators, bulldozers and dump trucks represent a major cost element in construction projects ranging from 10% in a commercial project, and up to 50% in major infrastructure projects such as highways, railways and energy projects. This is a large part of a project budget that many contractors are getting wrong and seeing significant amounts of wastage.

Aquila links plant equipment to the project work programme using 4D BIM technology, showing real-time activity to accelerate the understanding of onsite operations. Each vehicle on site will have its own tracking device, linked directly to a digital dashboard, so each vehicle location is known at all times.

This real-time, 4D mapping of plant equipment allows users to review, analyse and report on activity, performance, emissions and location. The built-in machine learning algorithms with Aquila will quickly become initiative to the project, extracting knowledge from the data to optimise the project model for top performance, whilst enabling seamless deployment of the plant equipment for future projects. 

The impacts of climate change are being seen across the globe and the accumulation of wasted energy and carbon emissions as well as greenhouse gases are contributing to the heating of the earth’s surface.  By rapidly cutting emissions we can lessen the risks of dangerous climate change for the future. 

Aquila optimizes plant equipment performance for a smarter, greener future. Designed to fight climate change, Aquila identifies ways to reduce emissions of plant equipment by monitoring output and changing future workflows patterns to be more energy efficient.