{"id":1112,"date":"2021-12-14T16:56:00","date_gmt":"2021-12-14T16:56:00","guid":{"rendered":"https:\/\/yardlink.com\/blog\/construction-robots-and-machine-learning"},"modified":"2024-07-29T08:35:18","modified_gmt":"2024-07-29T08:35:18","slug":"construction-robots-and-machine-learning","status":"publish","type":"post","link":"https:\/\/yardlink.com\/blog\/construction-robots-and-machine-learning","title":{"rendered":"Construction Robots And Different Types Of Machine Learning: How AI Is Changing The Industry"},"content":{"rendered":"\t
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AI in construction is rapidly changing the industry from multiple levels. The same can be said for any industry looking to implement various types of machine learning.<\/p>\n\n\n\n

The concept is simple: robots handle certain tasks typically completed by humans. Tasks that could be described as \u2018monotonous\u2019 or \u2018dangerous\u2019 in practice. Moreover, automation of this kind covers planning alongside design, which allows human workers to hone their skills in other areas of the operation.<\/p>\n\n\n\n

This type of technology<\/a> will always be an interesting topic of conversation. After all, AI doesn\u2019t require any real human intervention to operate and complete tasks. It might feel like a concept from the future but there are countless examples of automation in construction set in the modern day.<\/p>\n\n\n\n

Some see it as a negative, others, as a positive in the grand scheme of things.<\/p>\n\n\n\n

Continue reading to discover more about construction robots and the different types of machine learning that are shaping the future of the industry.<\/p>\n\n\n\n

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What Are the Different Types of Machine Learning?<\/h2>\n\n\n\n

To understand the different types of machine learning, the definition of machine learning must be identified.<\/p>\n\n\n\n

Machine learning is the study of computer algorithms that map out key actions through data. In other words, it\u2019s a branch of artificial intelligence, as in it has the capacity to think for itself and act on those thoughts to complete tasks.<\/p>\n\n\n\n

In construction, those tasks could involve creating a 3D model of a building, or handing the manufacturing of certain components at off-site factories to robots.<\/p>\n\n\n\n

There are multiple different subtypes of machine learning, all of which apply to AI in construction in one way or another. With that said, let\u2019s take a look at the different types of machine learning.<\/p>\n\n\n\n

Supervised Learning<\/h3>\n\n\n\n

Supervised learning is one of the more basic types of machine learning and requires a human touch for it to be successful – at least at the beginning.<\/p>\n\n\n\n

In this type of learning the machine algorithm is trained on labeled data which needs to be organised ahead of time by a supervisor. Data that is fed to the model will predict accurate outcomes in time, once it has outgrown the need for training wheels.<\/p>\n\n\n\n

Supervised learning has the capacity to help construction-based businesses solve complex problems at scale. This includes automating certain administrative tasks that revolve around planning and staff management. This is very advantageous for any construction manager, as it saves them time managing their team and preparing their workload.<\/p>\n\n\n\n

Unsupervised Learning<\/h3>\n\n\n\n

Unsupervised learning is the opposite of supervised learning in that it is able to work with unlabelled data. This means the machine can read larger datasets with complete autonomy based on initial training sets.<\/p>\n\n\n\n

Clustering is used by the machine learning algorithm to find unique ways of compressing data sets, discarding anything it deems irrelevant. Unsupervised learning is beneficial as it doesn\u2019t require too much time to set up compared to supervised learning.<\/p>\n\n\n\n

In construction, unsupervised learning has helped with various tasks including data preparation and customer segmentation. Keeping track of employees is essential for any construction company dealing with multiple projects at any given time.<\/p>\n\n\n\n

Reinforcement Learning<\/h3>\n\n\n\n

Reinforcement learning introduces AI to a game-like situation where its goal is to maximise its total. There are rewards and penalties for the actions it performs. Over time, the computer will begin to see a pattern. The algorithm here uses trial-and-error to find its end point.<\/p>\n\n\n\n

The goal of reinforcement learning is to create a sequence of key decisions that a system could then follow. The AI is given no hints as to how it can maximise its winnings in solving the game.<\/p>\n\n\n\n

Reinforcement learning is the most common type of AI associated with machines. Autonomous construction robots, in particular, move independently thanks to reinforcement learning.<\/p>\n\n\n\n

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What Are the Benefits of AI in Construction?<\/h2>\n\n\n\n

AI is innovation manifest, speeding up most of the processes tied to construction from a planning and development stage. It also applies to the machinery used at the actual building stage.<\/p>\n\n\n\n

As a business manager, the idea of AI in construction should appeal to you more than anyone else in the company. After all, with machine learning you can improve multiple areas of your business in one go.<\/p>\n\n\n\n

Automating tasks and streamlining workflow are two of the main benefits that arrive with automation in construction, but this is only the beginning…<\/p>\n\n\n\n

Better 3D Model Builds<\/h3>\n\n\n\n

Machine learning, and all of its different types, is making 3D modelling a lot easier. Buildings all vary in terms of dimensions and other internal factors. Multiple departments will work on these elements before agreeing on a final 3D model of the finished building.<\/p>\n\n\n\n

With construction, there are various sub-teams working on a single project:<\/p>\n\n\n\n