Cutting-Edge Technologies: Driving Sustainability in Hospital Operations
Journal
Machine Learning Methods in Biomedical Field : Computer-Aided Diagnostics, Healthcare and Biology Applications
ISSN
1860-949X
1860-9503
Publisher
Springer Nature Switzerland
Date Issued
2025
Author(s)
Magaña Ocaña, Osvaldo Francisco
Type
text::book::book part
Abstract
Hospitals play a vital role in health but also contribute significantly to environmental harm due to outdated practices and unstandardized sustainability strategies. This chapter identifies the urgent need for standardized, scalable, and tech-driven solutions to address hospital-generated emissions and waste. Through a review of recent literature, it explores how Industry 4.0 technologies—AI, ML, IoT, blockchain, and cloud computing–can enable real-time monitoring, predictive analytics, and secure environmental assessments. These innovations present a global opportunity to harmonize reporting, optimize resource use, and improve operational resilience. The roadmap outlined is designed for administrators, engineers, and policymakers to lead healthcare toward net-zero goals and digital sustainability leadership. © The authors © Springer.
License
Acceso Restringido
How to cite
Magaña Ocaña, O.F., Niembro-García, I.J. (2026). Cutting-Edge Technologies: Driving Sustainability in Hospital Operations. In: Moya-Albor, E., Ponce, H., Brieva, J., Gomez-Coronel, S.L., Torres, D.R. (eds) Machine Learning Methods in Biomedical Field. Studies in Computational Intelligence, vol 1218. Springer, Cham. https://doi.org/10.1007/978-3-031-96328-5_19