Privacy-Preserving Techniques for IoT-Enabled Urban Health Monitoring: A Comparative Analysis
Abstract
The adoption of IoT technologies in urban health monitoring has revolutionized public health management by enabling real-time data collection, analysis, and decision-making. However, these advancements bring significant challenges in preserving patient privacy and safeguarding sensitive information. This paper provides a comparative analysis of privacy-preserving techniques employed in IoT-driven urban health monitoring systems. Techniques such as data anonymization, encryption, secure multi-party computation, and blockchain-based solutions are evaluated based on effectiveness, scalability, computational efficiency, and usability. The study highlights strengths and limitations across diverse urban health applications, identifying best practices and areas for further improvement. Recommendations are proposed to guide the development and implementation of secure, privacy-centric IoT frameworks for sustainable urban healthcare ecosystems.
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