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The future is now. How AI in your construction business can make your projects more flexible.

artificial intelligence construction
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The future is now. How AI in your construction business can make your projects more flexible.

The ultimate aim for Artificial Intelligence (AI) in the construction industry is to overcome the industry’s toughest challenges: That is, to turn the mountains of data of historical projects into insights that help run a more efficient and profitable job site. 

With countless data collection points, AI as a tool provides intelligent and reliable solutions to process engineering and design, forecasting and scheduling, workforce safety and training data. 

But how does it all work?

What is Artificial Intelligence and Machine Learning in Construction?

Artificial intelligence (AI) is a technology designed to learn, solve problems and correlate patterns. Machine learning (ML) is a part of the wide-branching field of AI; it uses statistical techniques to learn from data. 

Machines exposed to more data can improve their understanding and insights to improve performance without being explicitly programmed.

This means that it has a wide, far-reaching application due to the minimal training it requires.

ML programs can improve performance by tracking progress and evaluating program data to identify potential schedule risks in construction. 

Algorithms will analyse several inputs from previous project performance, weather conditions, machine activity logs and land volume measurements to generate a risk score and inform relevant stakeholders of potential changes required.  

Enabling civil engineers to fast-track performance and accelerate the project lifecycle.

What is Artificial Intelligence in Design and Planning?

A project’s life cycle begins with the idea, design and process planning. 

It is an incredibly time consuming multilayered process consisting of preliminary research to site analysis, brief development, fee proposal and design development for council approval and planning certification. 

Multiple stakeholders, from designers, engineers, and architects, spend countless hours ensuring a project’s quality, timeframe, and budget. All efforts and workforce dedicated to this phase aim to avoid the risks associated with inaccurate planning and project failure. 

AI provides an iterative approach to improve the design knowledge base and increase time efficiency through generative design. 

Enabled by AI, the generative design provides access to many historic building plans, design alternatives and accumulative insights of years of planning. 

Designers and engineers can use their specific output requirements and tweek input values to form the basis of their projects. The design goals are put as the particular output requirements, whilst cost constraints, materials, location parameters and much more form the input values. 

Using algorithms, all the learnings from each iteration and project completion is used to grow the software’s performance and insights.  

It learns and continually evolves as you feed more data into the system.

With years of inputs and permutations, the generative design enables fast-tracked design, increased quality and cost-efficiency.

What does AI contribute to Project Execution?

Construction sites can be a logistical nightmare. 

With deviations from project plans, budget blow-outs, significant delays, safety incidents, transportation delays, material and labour shortages. They all increase the project’s lifecycle. 

AI development in construction has been centred around overcoming the major hurdles preventing successful project execution. 

With human safety being one of the most significant concerns for industry professionals, developments in AI work to reduce injury and fatality rates. A construction site can sometimes feel like a landmine of potential disaster. 

AI is being relied on to reduce the likelihood of common physical injuries. 

Smart wearables are being designed to measure biometric data to identify changes in temperature and heart rate. Additionally, facial recognition and cameras can detect unsafe work behaviour and nonconformance to procedures. 

With numerous points of data, AI can learn from the onsite activity for construction training projects. 

Inexperience on the field can be deadly. Realist simulations and real-work safety scenarios equip workers with onsite training without the risk. 

Along with safety training, high on the construction risks is the shrinking workforce in the industry. 

The ongoing talent crisis can be supported with the use of ML algorithms. AI gathers data to draw inferences from the existing workforce and the talent pool. Drawing on characteristics of successful employees, ML has the potential to identify potential leaders and at-risk employee departures. 

Data propelled companies can make hiring decisions based on a performance database, minimising time waste associated with onboarding, training and development. 

The boundless potential of AI is slowly being deployed across the industry. 

Data collection from each step in a project’s life cycle grows data intelligence and improves how we do business. With correct execution, AI puts your business ahead of the competition. 

Reach out to the Thrive team to learn more about how our team can integrate your data to power your business – 1300 868 474.

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