Applications of Robotic Systems and Emerging Technologies in the Collection, Classification, and Treatment of Medical Waste: A Systematic Review

Bonifacio R.F.A. · Journal of Robotics and Control (JRC) (2025) · DOI: 10.18196/jrc.v6i2.25649

Resumen

The growing volume of infectious medical waste represents a critical challenge for public health and environmental protection, demanding more efficient solutions in hospital waste management (MWM). The contribution of this research is to offer a systematic review of advances in robotic systems and emerging technologies, including artificial intelligence, blockchain, Internet of Things (IoT), and drones applied to the collection, classification, and treatment of medical waste. To do this, a search strategy was used in databases (Scopus, Web of Science, IEEE Xplore, among others) between 2019 and 2024, using keywords related to "medical waste," "robotics," "AI," and "blockchain." After applying inclusion and exclusion criteria, 107 studies were selected that report at least partial validations in health settings. The results show that integrating robotic systems with computer vision and deep learning algorithms can improve classification accuracy by more than 90% while reducing the direct exposure of personnel to infectious material. In addition, technologies such as blockchain and IoT strengthen data traceability and security, although economic and regulatory challenges that limit their large-scale adoption persist. In conclusion, robotics and emerging technologies constitute a promising approach to optimize medical waste management. Even so, greater standardization of performance metrics and validations in high-capacity hospitals are required, as well as the active involvement of health authorities to promote their implementation.

Instituciones: Universidad Continental