News

Problem:
Cargo transportation in Brazil is a bureaucratic and complex activity that, if done irregularly, can result in fines. One of the main risks is inaccuracy and delay, since the current counting method is manual, which generates queues and a loss of efficiency in the process. Furthermore, to weigh the cargo, it is necessary to use extremely expensive scales.
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Solution:
Our solution automates the counting process using computer vision and machine learning, with algorithms that process and interpret images obtained from the vehicle and the cargo through a system of fixed cameras and different viewing angles, precisely and quickly determining the number of items in the load, the number of truck axles, and the estimated weight.
Benefits:
Cargo counting is important for the control of a company or industry. After leaving the production line, products are classified according to the nature of the cargo to be transported and distributed. Regardless of the use of packaging or not, products need to be counted at the time of loading, during the transportation period and, finally, at the time of unloading. This control allows monitoring and inspection in the logistical system, monitoring loss, theft and irregularities in loading. Therefore, a good counting method guarantees more efficiency in this process, avoiding unnecessary costs and losses.

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.


