AI is being used in the construction industry to develop more environmentally friendly and cost-effective projects by helping to avoid safety concerns, labour shortages, or mistakes during scheduling or ordering. AI can analyse vast amounts of data, at a rate and accuracy far beyond the scope of humans, and offer enhanced data visibility and insights. With a huge range of AI tools being introduced into the market, let's look at how AI can lead to quicker, more accurate, and precise decisions within the construction industry!
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Artificial Intelligence covers any effort to enable computers to match or even surpass human intelligence. This includes recognising patterns, learning from data or pre-set algorithms, and 'understanding' language and images. Machine Learning, a subset of AI, allows programs to learn and uncover insights from data. Another faction of ML, ‘Deep Learning’ is used to figure out common elements between data sets using 'neural networks'- the ability for algorithms to make connections between data in a similar way to the human brain.
In construction, algorithms can be trained on ‘Big Data’, (decades worth of project data) to recognise patterns in budgets, ideal scenarios, and potential pitfalls, helping the program to 'learn' and provide detailed recommendations. These technologies are becoming increasingly useful for improving efficiency, analysing images, identifying design errors, predicting project needs, and managing large data sets.
AI systems analyse vast data from multiple sources to help managers in making informed decisions, particularly decisions concerning budget. By analysing huge amounts of past project data, AI can forecast how long each project phase will last, plus aid in scheduling and ordering supplies. AI predicts cost by considering factors like project size, contract type, and even project manager competence.
AI can help streamline key aspects of project planning including:
AI empowers general contractors to analyse real-time changes quickly, exploring multiple potential routes in the construction timeline. For example, AI can calculate the advantages and costs of different variables, like adding more labour or equipment, leading to improved scheduling and resource management, without sacrificing the quality of labour or materials.
AI’s ability to ‘read’ architectural designs and plans allows for increasingly accurate assistance in noting potential safety shortfalls in the designs, enhancing logistics, and generating alternatives. They can suggest design changes to enhance energy efficiency, material usage, and more efficient and sustainable designs. Different AI programs can even model what-if scenarios and compare different versions of a design, all while assessing the project's estimated costs.
AI-powered surveillance systems on construction sites can identify safety hazards and alert workers to potential risks. These AI-capable video systems can detect when workers are not wearing proper safety gear or are in unsafe areas. AI also streamlines incident reporting through sensors, cameras, and IoT (Internet of Things) devices, gathering real-time data and logging any incidents. The ability to log this data also provides better training and reporting, to avoid future incidents.
At the time of writing, AI solutions can automate about 40% of the sales process workload by predicting material needs and automatically ordering supplies, reducing waste and delays. With the ability to track everything from the amount of supplies needed to the best routes for supplies to travel, AI is helping cut down the frustration and delays associated with transporting the supplies for large projects.
While there is a fair way to go until we see robots pulling on a high vis and getting on the tools, better network connections and AI are enhancing real-time analysis and adaptability to unforeseen site conditions. This means we're not too far off robots that can respond to unexpected changes and challenges on construction sites. Currently, robots powered by AI are being put to work for tasks that are either repetitive or pose a safety risk, like laying bricks, welding, or 3D printing building parts and can be done while stationary.
Sustainability is a growing concern within the construction industry, with some reports claiming the industry is responsible for up to 50% of climate change. As such, introducing systems to reduce waste, increase efficiency and allocate resources is a key part of the mission to reduce harmful consequences.
However, AI usage within the construction industry is not without its challenges. One of the biggest challenges in using AI in construction today is that AI is only as good as the information you give it. The variability and quality of data used to train AI systems can result in biased or incomplete answers, although this is changing as more uniform reporting is introduced. However, human oversight is still crucial, particularly as AI systems can replicate existing biases and might not fully grasp the complexity of real-world scenarios.
Construction has traditionally relied on manual processes, complex scheduling, and intensive labour, often encountering challenges such as delays, cost overruns, and safety concerns. AI's integration into construction is a game-changer, offering unparalleled efficiencies and insights. While its challenges are noteworthy, its potential to revolutionise the industry is undeniable.
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