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One of the branches of Artificial Intelligence (AI), Computer Vision is a field that studies the processing of real-world images through a computer. The solution captures aspects of an image that would be imperceptible to the human eye, such as the different textures of a plant and the number of leaves it has, even if that amount exceeds the norm. The intention is to allow machines to not only record, but also interpret the obtained image. The processes of this type of technology are divided into four stages. First, the system captures the image, and then processes these images by adjusting and optimizing the acquired visual data. From then on, it is possible for the computer to analyze them, understanding characteristics in a way that is only possible for machines. Finally, these images are transformed into responses, addressing the specific questions that were requested. It is important to note that the vision provided by AI, in addition to identifying and counting objects in just a few minutes, can recognize patterns, such as labels and serial numbers printed on the object. Solutions with Computer Vision are also capable of detecting overheating, as is the case with Deeptrack, a technology that introduces drones to inspect transport carried out by conveyor belts within the mining industry.
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Application in the industry
Increasingly present in various processes of the industrial sector, AI has created several ways to optimize results within organizations, employing technologies that work effectively and bring agility and safety to the work. Betting on disruptive technologies within corporations is one of the ways to achieve exponential business growth, as previously mentioned here. Extremely operational roles, which require the employee to stand for many hours performing the same task, can lead to extreme fatigue. In addition to the physical and mental disorders they acquire, the work also becomes subject to a lack of precision and eventual failures, a process that Computer Vision technologies are capable of solving. Quality control in production lines and cargo counting for transport, for example, can be done quickly and safely, without putting the worker at risk.
Traceability and auditing in the production chain
Not wasting or losing products is certainly among the habits that can lead a company to succeed in its organic expansion. Checking the traceability of the production chain means collecting data regarding the activity being developed, such as counting labels on products, or items delivered to the final recipient. The traceability process happens from obtaining raw materials to product delivery. A management system that has flaws in the traceability system tends to lose control over the product, which may reach the recipient with fewer items, for example. Likewise, traceability allows for an understanding of the process as a whole, which tends to enable the creation of an effective database of documentation and resources used.
Get to know Pix Count
Created by Pix Force, Pix Count enters the market as another example of disruptive technology that solves industry pain points. Created to work as a counting system, the solution is applied to the production line and uses RGB cameras in its process. Once captured, the images are displayed on fixed or mobile devices that generate the item count in up to one minute, with 95% accuracy. Pix Count has been widely used in the cargo counting sector, analyzing and counting products such as pallets and iron bars, and even estimating the weight of the loaded material. On the production lines, the solution works by recognizing patterns and counting items, ensuring greater speed and efficiency in the process as a whole. The idea of working with disruptive technologies like Pix Count comes to address precise industry pain points. Measuring the quality of products laid out on production lines, as well as counting a large number of items to be transported, is a major challenge, especially if done by human labor. By using AI to the benefit of these sectors, work becomes safer, more agile, and more effective. #computervision #ArtificialIntelligence #PixCount #technology #pixforce
Fabio Caraça
Fábio Caraça is the Chief Growth Officer at Pix Force. He leads Pix Force's transformation into a scalable SaaS operation, combining strategic vision, culture, and high-impact execution.
