Introduction: The expansion of the Brain Center Hospital is expected to increase medical and non-medical waste by 210.38%. Given current limitations in single-use reliance, bin availability, and storage capacity, this study introduces a predictive statistical and spatial framework with IoT-supported monitoring to strengthen sustainable, regulation-compliant waste management.
Methods: Waste generation and patient load data (2018–2024) were analyzed through linear regression, Pearson’s correlation, and Shapiro–Wilk testing, with spatial patterns and hotspots identified using the Shoelace Formula and Kernel Density Estimation.
Results: Waste generation is projected to increase by 210.38% post-expansion, with inpatient medical waste contributing 87.59 kg/day. Patient volumes nearly doubled, showing a very strong correlation with waste generation (r > 0.98). Current infrastructure, including 1,026 waste bins and temporary storage capacity of only 30–150 L, is insufficient to meet future demands. Hotspot analysis identified critical waste-generation areas in the inpatient, ICU, and laboratory units.
Conclusion: Hospital expansion without proportional waste management improvements risks regulatory non-compliance and environmental harm. This study proposes a scalable framework integrating predictive modeling, spatial planning, and IoT-enabled monitoring. The novelty lies in combining statistical forecasting, geospatial analysis, and sustainability-oriented solutions to guide policymakers and healthcare providers. While locally applied, the framework is globally relevant and requires validation in diverse hospital contexts to support resilient and sustainable healthcare systems.