This is Biltrax Media’s first discourse on ‘Artificial Intelligence (AI) in the Construction Industry’ where we explore innovative AI use cases over the next few weeks.
What exactly is Artificial Intelligence?
Artificial Intelligence (AI) has the ability to perform tasks similar to that performed by human intelligence, such as planning, recognition, and decision making. It works on image recognition algorithms to find out search criteria. Among many other sectors, finance, automotive, transport, healthcare, logistics, industrial manufacturing industries use AI to be more efficient and to provide better services.
According to a 2018 report by the New York-based consulting firm McKinsey & Co, the construction sector was amongst the slowest in adopting innovation in processes and technology. Although the global construction industry is worth more than $10 trillion a year, it remains severely under-digitized. Hence, it not entirely surprising that out of twelve (12) industries, construction came tenth (10) in terms of percentage of firms integrating AI into their businesses.
Adoption of AI in Construction:
As per McKinsey’s report on ‘Artificial Intelligence: Construction Technology’s Next Frontier‘ released in early 2018, the construction industry is in a great position to adopt several use cases already developed & successfully delivered in other industries; some examples of which are as follows.
- Construction Project Planning Optimization derived from Transportation Route Optimization algorithms (Logistics)
- Predicting Constructibility Issues derived from Pharmaceutical Outcomes Predictions algorithms (Pharma)
- Optimizing Material & Inventory Management derived from Retail Supply Chain algorithms (Retail)
- Modular or Prefabrication Construction and 3-D Printing derived through machine learning (Robotics)
- Risk & Safety Management derived from healthcare image recognition algorithms.
Several other specific use cases where AI could be developed for Construction are:
- Refining Quality Control & Managing Claims: Firms can use deep learning techniques to improve quality control, for example, to evaluate drone-collected images in order to compare construction defects with existing drawings.
- Increasing The Retention & Development of Talent: Leaders can tackle the challenge of retaining top talent by applying both unsupervised machine learning algorithms such as Gaussian mixture models, which can divide employees based on the likelihood of attrition, and developing targeted plans to retain them.
- Enhancing Project Monitoring & Risk Management: The use of neural networks like drone-generated images and laser-generated data capturing project progress applications would dramatically reduce decision-making cycles in a construction project.
- Building Commercial Excellence & A Competitive Edge: Firms can project win rate, enhance margins, and ensure project value using supervised and unsupervised learning algorithms and also predict a combination of services that might be most attractive to clients.
- Firm Reputation & Risk Management: Firms can apply machine learning to address market and client concerns. For example, Naïve Bayes algorithms can be used to perform sentiment analysis on a firm’s market perception and inform the launch of targeted, reputation-building efforts needed to preserve its backlog and stock price.
Also, in pre-construction stages such as planning and design, AI can be beneficial. Some of the benefits in other construction stages are as follows:
- In the pre-construction phase, using Computational / Generative Design software like the Building System Planning (BSP) is a great example of advanced AI. Instead of creating a few design alternatives, you can come up with hundreds of alternatives with this kind of software.
- Once construction has begun, AI can be used to handle the duties of project management and control. On most work locations, drones have become a significant instrument. Being able to take pictures and survey sites 24/7 can lead to increased efficiencies, safer conditions and more accuracy all around.
- AI database systems can assist engineers to learn how to build particular projects. For example, if engineers were working on a proposed new building, AI systems could advise on how to construct the building and present a case. These AI software’s can study a construction site during the planning phases and collect sufficient data to generate 3D maps, blueprints, and building plans.
- After the construction of buildings, whether they are used for commercial purposes or it is a development of new houses, AI systems can be used inside the structure. The hotel chain Wynn, for instance, announced in 2016 that by the end of 2017 each room at its Las Vegas hotel would have an Amazon Echo function. These systems are suitable for room elements such as lighting, temperature and any audio-visual facilities in the room.
- Furthermore, AI can be used to design the routing of electrical and plumbing systems in modern buildings, to pursue on-site and real-time interactions between equipment’s, employees and objects.
Thus, with the availability of data, AI-based applications are discovering more utility in construction. Some of the prominent vendors in AI in the construction market are Oracle, Microsoft, IBM, eSUB, Alice Technologies, SAP, Autodesk, Aurora Computer Services, Smartvid.io, and Building System Planning. Construction companies should prioritize investment based on areas where AI can have the greatest effect on the distinctive requirements of their company. Thus, in the short and long term, early movers will set the industry’s direction and profit.
Over the next few weeks, we will elaborate specific use cases covering AI in Construction & feature some cutting edge technologies.
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