Reducing Costs Through Engineering Collaboration

whitePaper | October 17, 2022

Engineering calculations are at the heart of civil engineering design. The calculation sheets that accompany a project can provide evidence of the design competency and that the specifications are met. Common building calculations are formalized in design guides, such as Eurocodes, AASHTO, IBC etc. The equations tend to be mathematically simple – only needing basic arithmetic operations on the design parameters – but they still require engineering experience to determine the which, why, and when.

whitePaper | January 20, 2022

Knowledge is any organisation’s biggest asset, but in construction and engineering, the culture of knowledge management is specifically important due to the information-, regulation- and process-saturated nature of the industry.

whitePaper | May 16, 2022

This paper explores the reluctance of developers of cyber-physical systems to embrace digital engineering (DE), how DE methods should be tailored to achieve their stakeholders' goals, and how to measure the effectiveness of DE-enabled workflows.

whitePaper | May 31, 2021

he digital planning, which can now be found in architecture and design offices, at general contractors or via prefabrication, bricklaying robots and GPS-based excavators already on the building site, is characterized by Building Information Modeling (BIM). Yet, BIM is only really an efficient and commercial option if it is paired with the integrated working method.

whitePaper | December 28, 2021

The construction industry is going through a digital revolution that is changing construction sites and in the future is predicted to look drastically different with autonomous machinery and drones, virtual reality and equipment and other digital innovations a common sight. This is not the introduction of technology for technology’s sake but to help the industry deal with some of its key challenges. Electronic Media Services (EMS) through its long history of working with partners in the construction industry knows it has and continues to find change and in particular digital change difficult.

whitePaper | May 12, 2022

Machine learning is powering most of the recent advancements in artificial intelligence including autonomous systems, computer vision, natural language processing, predictive analytics, and a wide range of applications among the seven patterns of AI. However, in order for these systems to be able to create accurate generalizations, these machine learning systems must be trained on data. The more advanced forms of machine learning, especially deep learning neural networks, require significant amounts of data to be able to create models with acceptable levels of accuracy.