Why we need more AI to deal with our crumbling infrastructures

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Why we need more AI to deal with our crumbling infrastructures

Do you remember the Genoa bridge that collapsed a few months ago? What if we could have avoided this tragedy by using AI…

For a $10 trillion industry, technology remains a surprisingly small part of the construction business, especially when it comes to AI.

Indeed, construction firms are behind the curve in implementing artificial intelligence solutions and while its customers are increasingly sophisticated, it remains severely under-digitized.

Moreover, the construction industry struggles with a labor shortage and declining productivity, artificial intelligence helps to fill in the gaps.

Despite proven high return on investment (ROI) and widespread management interest in AI solutions, few construction companies currently have the capabilities — including the personnel, processes, and tools — to implement them.

However, things are changing…

Indeed, some specific industries, such as manufacturing or transportation have started the process of breaking down the barriers between one another and operating more as ecosystems — increasing the threat of competition from market entrants that have not traditionally been capital project players. The suppliers of the construction firms are already using AI…

Similarly, building information modeling (BIM) applications can also integrate with AI. Unlike the data generated by computer-aided design (CAD), which represent flat shapes or volumes and 2D drawings consisting of lines, BIM data represent the reality of the built structure. AI is set to evolve from BIM, by enhancing the overall design process and further improving the outcomes.

This new way of digitizing the construction world is superior in operational terms, and the structure of its data is ideal for analytical purposes and the application of Machine Learning techniques.

The construction industry, long a technology laggard, is hiring data scientists to boost efficiency and help an industry in which construction workers are killed on the job five times more often than other laborers.

It appears that the industry must invest in AI. Construction firms are not reluctant to invest. Statista.com is projecting a 27% increase in construction spending in the coming years. Simultaneously, the construction labor force is shrinking. Therefore, construction professionals will need to leverage AI to keep up with demand.

The use of artificial intelligence in the construction industry can be divided into four clear categories: planning, administrative, construction, and post-construction.

Once the structure is built, AI is still around. In fact, most new builds have AI woven integrated inside design of the building. Indeed, in the US, $1.5 billion was invested by companies in the area of AI implementation for buildings in 2016. AI remains in place in the form of integrated features within the structure of the building.

Drones, scanners, wearables and other construction management apps are adding to the mountain of data collected as a by-product of their use. However, AI needs a certain critical mass of data to deliver on its promise so scale will matter; as such, construction firms will need a significant amount of data to train an AI algorithm. Therefore, the largest companies are likely to benefit more, particularly in the short term.

It is possible that an external third party enters and leverages data to train its models — a scenario that would likely result in improvement across the industry as a whole but limited competitive advantage for individual firms — but this seems unlikely given the enormous restrictions on data sharing and data ownership.

Small-to-mid-sized firms will not have enough data scale to compete, unless the industry has a shared database.

Existing players could be upended by new entrants with radically different approaches and technologies. As a result, established players will have to adapt, just to remain relevant competitors in the game.

There are more and smarter buildings in existence around the world, buildings fitted with sensors that report their performance in real-time.

By exploiting the various data sets, AI will be able to compare how buildings perform, the energy and water they consume, how they move, what temperature the rooms are being conditioned to, and a host of other metrics, assessing the outcomes of the different solutions used and then, based on those findings, it can inform and refine the design for the next project.

Real-time video feeds are already being analyzed with AI to optimize visitor circulation in museums and to improve the spatial design of office layouts. But just think of the impact such techniques could have if one were able to further extract meaningful data and apply it on all building types or else on a much bigger scale, on a community or city level.

In the future, AI can work alongside workers, helping to speed construction, make quicker decisions, and reduce costs and injuries.

Why we need more AI to deal with our crumbling infrastructures

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