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Abstract

The research focused on reducing environmental pollu
tion through an assistant for the classification of solid waste. 
With this, three specific objectives were raised: analyze the 
technologies to be used, evaluate the different design alter
natives and develop an assistant classification system using 
computational learning. The methodology was divided into 
three stages,the creation of the prototype, the design of 
the waste detection system and the development of the 
software. The first stage focused on the design of the initial 
hardware and software. In the second, models were imple
mented for the detection and classification of waste. In the 
third stage, an interface was developed to manage the sys
tem. The results showed that technologies such as compu
ter vision are effective for waste classification. On the other 
hand, different design alternatives were evaluated, giving 
priority to precision and speed. Finally, a functional proto
type was built. This research highlights the importance of 
new technologies and environmental education for waste 
management. The findings suggest that the implementa
tion of this type of systems can help reduce waste in landfills 
and oceans by promoting a culture of recycling. To conclude, 
the auxiliary system developed proved to be a useful tool for 
reducing environmental pollution. The union with advanced 
technologies is a necessary path to promote sustainable 
practices and protect the environment. Future researchers 
are recommended to continue with similar projects and 
educational programs to increase the positive impact.