Dhwani Patel, Vaibhav Sharma, and Rajeev Agrawal
Department of Mechanical Engineering Malaviya National Institute of Technology Jaipur (Rajasthan), India-302017
Abstract
Healthcare waste management is vital for protecting public health and the environment, yet traditional methods often fall short in handling increasing waste volumes. This study investigates how artificial intelligence can transform Healthcare waste management to enhance efficiency. Through a literature review of 58 papers, 21 challenges and 12 enablers were identified. Using Multi-Criteria Decision-Making Techniques—TOPSIS and DEMATEL—the study prioritized these factors and analysed their interrelationships. Key challenges include inadequate procurement and inventory management, lack of supply chain transparency, and poor logistics optimization. Critical enablers are real-time monitoring, IoT-based sensors, cloud platforms, and data analytics, which support smarter, more sustainable waste handling. The findings highlight that successfully implementing AI requires overcoming technical, organizational, and regulatory barriers while leveraging key technologies. This study provides valuable insights for healthcare administrators and policymakers aiming to modernize Healthcare waste management systems, offering a roadmap for safer, more efficient, and resilient Healthcare waste management through AI integration.
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