Intelligent site management – how AI improves efficiency and safety?

Artificial intelligence is beginning to revolutionise the way construction sites are managed. Traditional methods based on visual supervision and paper-based review are about to give way to intelligent systems in construction monitoring that verify the progress of the work more quickly and accurately, informing of possible delays at an early stage. But AI on the construction site also identifies many hazards in real time, resulting in improved safety of the works in progress. How does it do that?

Construction site monitoring AI – smart cameras and sensors

Site monitoring is one of the most important challenges faced by managers overseeing construction sites. Traditional methods of tracking the work schedule (individual assessment or using cams for recording without analysis and prediction of site risks) are time-consuming and error-prone. That is why managers use helpful tools that integrate modern technologies in construction, such as advanced cameras and sensors and AI algorithms, which analyse the works at hand in terms of progress and safety.

And so, on-site construction AI enabled drones and robots, as well as state-of-the-art cameras with sensor systems are able to detect delays in work, but they also help to identify unauthorised access to hazardous areas, damage to machinery or the lack of personal protective equipment necessary for certain tasks, for example. Upon detecting faults, the system alerts the relevant people who can take appropriate measures quickly. The systems also help in the real-time analysis of weather conditions that can affect crew safety.

While the above examples prove that AI can play a very important role in construction schedule management, one should remember that the list of benefits of using intelligent construction monitoring can be much longer.

Optimising construction processes with AI

The automation of construction processes is one of the key strengths of artificial intelligence in the construction industry. The use of AI not only allows the optimisation of supply logistics, managing material inventories and reducing wastage, but also helps to use human resources more efficiently. Artificial intelligence is also being used in the analysis and optimisation of construction costs, as it enables the identification of areas where expenditure can be reduced without compromising the quality of the project.

A great example of a holistic approach to optimising construction processes is a project by Intel, which has set its sights on intelligent construction management using solutions from Buildots, a startup specialising in analysing data from construction sites with the use of artificial intelligence. The AI-based system integrates data from 360° cameras mounted on the hard hats of surveillance workers who regularly moved around the construction site and recorded the daily progress of the work on their way. The camera images were automatically compared with the digital BIM model and the detailed construction schedule. This enabled real-time detection of deviations from the plan, precise analysis of progress, and prediction of risks on site and identification of potential delays.

According to the company, the results of implementing this solution were impressive: a four-week reduction in completion time and a 4.3 per cent reduction in costs associated with making corrections.

Safety on site: how does AI reduce risk?

The construction industry has for years been regarded as one of the most dangerous. The Statistics Poland data on accident rates in Poland clearly shows that almost half of all accidents at work are caused by employee’s failure to follow procedures or human errors. This is why the risk prediction on the construction site has been on the radar of artificial intelligence experts from the start.

Intelligent on-site monitoring systems can check in real time whether workers are wearing the mandatory PPE, such as hard hats, reflective waistcoats, goggles or special footwear. They also detect missing harnesses when one works at heights, and immediately send a report to the relevant manager. They also monitor the construction site for danger zones on a constant basis, such as the area where cranes or other machinery are operating. If an unauthorised person enters a restricted zone, the system will automatically send an alert, while it can even stop the machine itself to minimise the risk of an accident.

Structural hazards, which can lead to serious accidents and even structural collapse, are also present at all construction sites. Traditionally, the monitoring of these risks was based on manual surveillance and inspections by workers. Today, thanks to artificial intelligence and IoT (Internet of Things) technology, site safety monitoring is becoming more precise, continuous and automatic. IoT sensors can be installed in various parts of building structures or machinery. Their task is to continuously collect data on vibrations, stresses, overloads or temperatures, and then analyse them and predict potential risks. Example? Detecting vibration and stress in tall scaffolding to prevent structural collapse, or monitoring soil moisture and pressure to avoid landslides during initial construction work. But AI on the construction site more and more frequently involves sensors that monitor the load on cranes to inform us when to reduce the load.

Autonomous machines and robots to support construction management

The automation of construction processes is moving up to the next level through the use of autonomous machines and robots. Alongside drones and robots, there are more and more smart excavators, bulldozers or rollers in the construction industry that are used for autonomously-performed, repetitive tasks such as levelling, paving or preparing foundations. Fitted with GPS systems, LIDAR sensors and AI-based software, they can analyse the terrain, adapting their actions to conditions in real time, and working with a precision that is difficult to expect from a human being.

Masonry robots such as the SAM100 (Semi-Automated Mason), developed by US-based Construction Robotics, are introduced – mainly in the US, for the time being – to construction sites on an increasingly wider scale. They lay bricks with tremendous efficiency – up to several thousand a day, which is several times faster than an experienced bricklayer. Other equipment supports reinforcement, welding or surface painting.

But until the time robot-machines displace humans and conventional machines from the construction site, artificial intelligence will effectively support companies in the predictive maintenance of construction equipment. Intelligent AI systems analyse data from sensors mounted on machines, predicting potential faults before they occur. Example? Caterpillar Inc. It uses AI technologies to monitor the condition of its machines, allowing it to schedule maintenance at the optimum time (choosing the construction phase, when they are not needed), thereby avoiding unplanned and costly downtime. Not only does this approach increase operational efficiency, but also extends the life of the equipment and improves on-site safety.

The future of smart building sites – what lies ahead?

The construction industry of the future is believed to fully integrate intelligent construction monitoring systems and advanced artificial intelligence algorithms that will manage every phase of the construction process, from design to completion. The development of autonomous machines, the use of drones and robots in construction and the introduction of AI systems on the construction site will make it more organised and safer. In the future, smart construction management is predicted to include even greater use of advanced predictive tools to forecast risk and to optimise processes in real time. What’s more, AI will be increasingly integrated with the Internet of Things (IoT), creating a network in which all the on-site equipment and machines will communicate with each other, relaying information on the status of the project, material usage, work progress or machine load and the condition of human resources.