Artificial Intelligence Based System for Sorting and Detection of Organic and Inorganic Waste

Solid waste management has become a global challenge today due to its constant increase in waste and inadequate classification, which leads to serious environmental problems. The research objective is to develop a system based on artificial intelligence (AI) for the classification and detection of organic and inorganic waste. In terms of its approach, it is quantitative with a pre-experimental and applied design. The population was made up of 1,298 images as a data collection technique for observation. Furthermore, the implementation of this system has shown significant improvements in its key indicators: precision, detection speed, and reduction of errors in the tests carried out, obtaining an increase in precision of 11.52%, 23.61% in detection speed and a reduction in 24.13% error rate. Finally, this research highlights the importance of AI in environmental sustainability by promoting much more efficient waste management and thus promoting ecological awareness in educational environments and for students to value the importance of recycling and sustainability. Finally, this research concludes that AI-based systems are a viable and scalable solution to address all the challenges associated with waste management.

@article{Meza2025,
  title     = {Artificial Intelligence Based System for Sorting and Detection of Organic and Inorganic Waste},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {5},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Angel Jair Castañeda Meza and Nicol’s Alexander Lopez Haro and Rosalynn Ornella Flores-Castañeda},
  doi       = {10.14569/IJACSA.2025.0160509},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160509}
}