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Data is meaningless without a story. As we continue to produce and collect more data about the world – and infrastructure in particular – it is clear that advanced analytics hold the key to industry transformation.
The market for data science applications in the construction and engineering sector, specifically machine learning (ML) and artificial intelligence (AI), is expected to grow to US$1.8bn by 2023 – more than 35% year-on-year since 2018 (source: Markets and Markets). Having a strong data science capability is essential as we transition to the data-driven industry of the future. Companies in construction and engineering have the benefit of being late bloomers, able to bypass the learning curve to adopt best-in-class technology and processes from the beginning.
Several AI/ML-powered applications and use cases have had a proven impact on businesses, communities and the environment – and can be applied to our industry too. For example, reinforcement learning has been successfully used to teach AI to play videogames. With overburdened supply chains and the rising impact of inflation, this same technology can be used in our industry to optimise production scheduling. Similarly, the model used to forecast changes in Uber demand over time can be adapted to forecast demand in the water industry – helping us manage distribution of this vital resource. Elsewhere, the AI algorithm for object detection in self-driving cars can be used to detect defects in pavements – helping authorities improve the environment for pedestrians.
In addition to taking advantage of proven solutions, we need to continue to value innovations that place us ahead of the curve. Our specialists are working on ways to exploit the digitisation of the built environment at scale and to record our impact and trajectory to net-zero. But this is just the beginning. AI is having a major impact across more and more industries – a trend that will only accelerate as we go forward. Some of this impact will be highly disruptive, and we have to be agile enough to adapt.
To truly harness the power of AI, we combine industry-specific domain knowledge with cutting-edge data science algorithms from across different fields; we call it domain x digital. We need to go one step further than conventional knowledge transfer or multidisciplinary team collaboration by recognising that domain x digital can devise solutions to multisector issues that current approaches are incapable of achieving alone. We need to codify the knowledge so that it is integrated into the computational algorithm and can evolve simultaneously as the machine learns. With our domain knowledge and data science working hand-in-hand, we will be able to solve complex challenges in ways we could not even conceive of before.
Of course, this is easier said than done. This is not a one-person job and will require unswerving support from dedicated, collaborative minds throughout the organisation. This is a truly exciting time to work in this revolutionary field, helping to steer the digital transformation of the built environment.
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