Workers at construction and mining sites deal with a variety of duties that necessitate surveillance and supervision on a daily basis. They must also ensure that their construction tasks are carried out safely on site. While artificial intelligence and augmented reality are altering the business, computer vision and data annotation have the potential to fix some of the industry’s current problems and revitalize the sector. Some of the major issues in construction and mining include struck‐by accidents, continuous monitoring of unsafe conditions, quality and defect inspection, monitoring of site activities, and more.
Computer vision has enormous potential in the construction and mining industries. It can examine video footage from worksites in real-time, identify poor craftmanship, divergence from standardized work plans, and compare work done against BIM standards, thanks to its object identification and recognition capability. In terms of safety, it can monitor security camera footage and detect hardhats, high visibility vests, work goggles, shoes, and even special protection belts required for workers working at high altitudes. In case it observes the absence of protective gear, PPE compliance breach, or an impending threat, the system can also alert site managers to take action to save lives.
The quality of live stream video footage from construction and mining sites can be examined to find obvious flaws or problems. This early detection of flaws and quality issues can help projects save time, money, and resources. Following that, computer vision can assist in the creation of 3D-built models for progress monitoring, mapping, autonomous robotics, and presentations. This can aid in the planning and execution of construction projects.
Companies can also deploy drones, equipping them with LIDAR and HD cameras for workers and inventory monitoring. By annotating and analyzing the data collected from the drone, managers can track and transform these analytics into valuable insights to optimize the ongoing processes. For instance, computer vision can be leveraged to create spaghetti diagrams, identifying worker movement trajectories. This enables checking for longer travel paths, movement bottlenecks and optimize onsite material storage. Thus reducing the idle time and saving additional delay costs. This can also address the under-utilization of resources, lack of insights on activity, optimal coordination, and real-time intelligence.
Safety of Workers Onsite
Mining engineers and workers can use computer vision to assist reduce accidents and injuries on the job. We can identify failures that will not only damage productivity but also be hazardous or fatal to any workers nearby if enough high-quality data is collected and annotated.
We can utilize Computer Vision and data annotation to forecast other potential dangers in addition to failures by examining patterns in events. This is extremely beneficial because the environment in mining can have a significant impact on equipment functioning and lifespan, which varies substantially based on location.
However, AI can be used for more than only predicting when equipment will fail or which threats would arise. We can also monitor the health and performance of the equipment on a regular basis, which is critical for avoiding unexpected breakdowns and worker hazards.
Reducing Material wastage
Material management is a crucial component of project management since it accounts for the bulk of cost input in building and mining. Improper material management throughout a project might result in significant and needless expenses. Cement, for example, is frequently lost on building sites due to inefficient storage and handling. Workers, in particular, tend to use only resources that are proximate to their work area, resulting in the waste of additional materials kept on higher levels.
With computer vision, you can reduce the amount of material wasted. Tracking items stored on-site can be made easier by annotating data. This will not only assist you in improving project performance by identifying underutilized materials, but it will also assist you in reducing material waste and achieving better cost control over time.
Monitoring using Autonomous vehicles
Companies can undertake remote inspections of their premises and assets using autonomous vehicles or drones. The construction and mining industries have jumped ahead with a raft of technologies now available to make them more efficient, safer, and autonomous, thanks to a slew of new technologies that have emerged in the last ten years, including autonomous vehicles, trains, aircraft, and even autonomous mines.
This allows them to map shallow and deep features at higher resolutions than before, allowing them to have a better grasp of an area’s geology and completely evaluate it before drilling any needless deep holes. Operators have been able to minimize normal site visits by half by utilizing autonomous vehicles to inspect well sites.
Looking Forward
Automation, as well as the application of AI and Machine Learning, may clearly help businesses save money, boost efficiency, and reap a variety of other benefits. What’s holding us back is a lack of excellent data and a vast quantity of it. Companies need high-quality labelled data for training in order to implement these algorithms.
TagX offers data annotation services for machine learning. Having a diverse pool of accredited professionals, access to the most advanced tools, cutting-edge technologies, and proven operational techniques, we constantly strive to improve the quality of our client’s AI algorithm predictions.
Companies are working on scaling the use of AI in mining and construction and with Computer vision becoming a huge industry we can start seeing more use of AI in the mining and construction industry. One that is completely changing from what we’ve traditionally known it to be. TagX can provide services to help you through the process of implementing such systems into your business.
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