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Augmented Reality Visual Assistance (ARVAST) – Augmented Reality and Machine Learning for Error Free Quicker Assembly of Modern Methods of Construction Components

Abstract

MMC has generated substantial interest from the government due to its potential to help meet housing and infrastructure needs that traditional methods have failed to achieve. Many construction companies have incorporated MMC approaches into their delivery offers. However, challenges with MMC remain, especially given the significant range of projects that construction delivery organisations are required to undertake, with variations in the type and size of individual structures. This inconsistency can lead to challenges for the sector. With contractors required to undertake projects with varying MMC needs, there is a limited opportunity for the transfer of knowledge between schemes. This leads to the need for repeated training sessions that consume both time and money and lead to avoidable assembly errors due to a simple lack of knowledge. In addition to this, it is common for companies to use MMC components from different factories/manufacturers, requiring different assembly knowledge accentuating the issue with the constant need for staff training.

Our solution, i.e., ARVAST, will minimize/eliminate the need for repeated trainings and errors from new trainees using augmented-reality (AR) in conjunction with deep learning algorithms, video analytics, big data analytics, natural language processing (NLP) and cloud computing.

Lead Participant

Project Cost

Grant Offer

WHITE FROG PUBLISHING LIMITED £183,587 £ 128,511
 

Participant

GALLIFORD TRY CONSTRUCTION LIMITED £104,308 £ 44,853
J-WADEL SOLUTIONS LTD £350,448 £ 245,314
LEEDS BECKETT UNIVERSITY £24,507 £ 24,507
GLOBAL METHODS OF CONSTRUCTION UK LIMITED £101,106 £ 70,774
UNIVERSITY OF HERTFORDSHIRE HIGHER EDUCATION CORPORATION £274,122 £ 274,122

Publications

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