Affiliate Disclaimer: Some of the links below are affiliate links. As an Amazon Associate, I earn from qualifying purchases.Some of the most important technological developments of the last decade have happened around artificial intelligence, also known as AI. In nearly all areas of our lives, artificial intelligence has improved human efficiency, safety, and accuracy. But what does it have to offer in construction safety?
Machine learning is improving construction safety by analyzing construction sights and projects to identify both the highest risk and most likely safety issues, as well as identifying human failures in safety.The impact of machine learning on construction, particularly construction safety, is a very complex topic, but it’s also very rewarding to understand. Read on to learn more about machine learning, how it works, how it relates to construction, and how it is improving safety.
Machine Learning and Construction SafetyAI is helping construction in many ways, but perhaps the most important one is ensuring that those working on construction sites, as well as those who will operate in the space after construction, are kept safe. From environmental monitoring to building safety, machine learning and artificial intelligence are changing construction safety.
Physical Risk ManagementOne of the most important things a worksite can do is improve the safety of those building the project. With artificial intelligence and machine learning, supervisors and project planners can the materials, tools, and design of the project and understand which parts of the project will be the most dangerous, as well as how a team can help to mitigate this risk the most. Similarly, artificial intelligence can identify what job on the worksite carries the highest degree of risk and can help develop training programs to mitigate this risk. Machine learning, in particular, is helping improve workforce safety as more information is provided regarding safety outcomes. If AI is able to learn that its safety recommendation was wrong, it will be better able to process the data and improve safety solutions in the future. That said, here are a few notable ways machine learning comes in handy in physical risk management in construction projects:
Machine Learning Is Helping Spot Potential HazardsOne of the most important ways machine learning is being used to improve safety in the construction industry is by helping to identify. Most notably, machine learning algorithms analyze data sets and look for patterns, providing information you can use to identify potential hazards on a construction site. For example, if the data shows more accidents on construction sites with a certain type of scaffolding, the machine learning system can flag that as a potential hazard. This information can then be used to improve safety on future construction sites.
Robotics Is Helping With Bricklaying and WeldingRobotics is also being used to help with some dangerous tasks. For example, robots can now help with and welding. This is important because these are two of the most dangerous tasks on a construction site. Using robotics to help with these tasks will help improve safety on future construction sites. The robots can be programmed to follow safety protocols, and they can be monitored by machine learning algorithms.
Computer Vision Is Making Scaffolding SaferScaffolding is one of the most common pieces of equipment on a construction site, and it’s also one of the most dangerous. Many accidents in the construction industry are caused by scaffolding. However, is now being used to make scaffolding safer. For instance, you can use machine learning algorithms to inspect scaffolding for potential hazards. You can then use this information to make changes to the scaffolding and improve safety.
Environmental SafetyArtificial intelligence is also making drastic improvements in maintaining a safe environment for workers to operate in. Many construction projects today offer unique challenges with dangerous work conditions caused by environmental factors. In , for example, artificial intelligence is helping those working within the exclusion zone understand where it’s safe to work and which places they should avoid. AI is also ensuring the safety of workers in harsher climates. It can be used to combat dehydration and heat exhaustion in arid environments, and to calculate the risk that comes with working in cold and icy environments. Here’s a rundown of a few ways this technology helps in environmental safety:
Drones Are Helping to Survey and Map SitesOne of the ways machine learning is being used to improve safety in the construction industry is by helping to and map construction sites. Construction companies then use this data to create 3D models of job sites, which helps reduce accidents. For example, construction workers can use the 3D model to plan the safest route when carrying materials to and from the construction site. They can also use drones to inspect the construction site for potential hazards.
Machine Learning Is Predicting Weather PatternsWeather is one of the most important factors in construction. If the weather is bad, it can delay construction projects or even cause accidents. Machine learning is now being used to predict weather patterns. This information can then be used to improve safety on future construction sites. For example, if the data shows a high chance of a storm, the construction site can be shut down for the day.
Worker SafetyPerhaps the most important way AI is improving construction safety is by ensuring that workers observe important ergonomic and safety practices. Artificial intelligence was used throughout the COVID-19 pandemic to ensure that workers were not exposing themselves or others to the disease, and, if exposure did occur, track those who were positive to limit spread. Machine learning helps ensure that everything a worker does, even in their smallest movements, is protected from harm, by predicting it before it happens and suggesting solutions. AI can also identify workers ignoring or breaking safety regulations, and has monitored the workforce writ large to see if certain safety training or materials are missing. Here are some specific ways in which machine learning is improving worker safety:
Algorithms Are Helping Monitor Safety PerformanceMachine learning is being used to monitor. Many different safety metrics can be tracked on a construction site, including the number of accidents, injuries, and the number of near-misses. You can use machine learning algorithms to track these safety metrics and use this information to improve safety on future construction sites. For example, if the data shows a high rate of accidents on a construction site, the machine learning system can flag that as a potential hazard. This information can then be used to make changes to the construction site to improve safety.
Virtual Reality Helping in Safety TrainingAccording to a 2013 study published in the Construction Management and Economics Journal , one of the most exciting ways machine learning is being used to improve safety in the construction industry is by helping to create. These simulations can be used to train construction workers on how to work on a construction site safely. For example, if there is a new type of scaffolding that the company will use on a construction site, workers can train in a virtual reality simulation before they ever set foot on the site. This will ensure that they are familiar with the scaffolding and know how to use it safely.
AI and Machine Learning in ConstructionOne of the biggest achievements of AI in construction has been an increase in safety, but its contributions go way beyond that.
Project Planning and Resource ManagementThere are many moving parts to any project, and it can be hard to keep track of all of them. Artificial intelligence and machine learning help determine what exactly is needed to complete a construction project, allowing for better planning and cost management. Similarly important is the ability of AI to limit cost overruns. Most major construction projects AI accesses huge databases to assess how much a project will likely cost, and can determine the risk of a project running over budget. Machine learning lets AI use data from previous projects to understand cost management and predict with greater accuracy the degree of error that may occur.
Project DesignOne of the greatest contributions of AI in project design is its ability to visualize models and change them in real-time as adjustments are made. Artificial intelligence is able to apply physics and statistical analysis to building design. This way, designers can know exactly what each piece of the construction puzzle is doing, allowing for more adaptability.
Machine learning only makes these processes more precise, allowing builders and designers to understand the structural integrity of a project as it’s being built.