Privacy-Preserving Techniques for IoT-Enabled Urban Health Monitoring: A Comparative Analysis ITAI Vol. 1 No. 1 (2017) SAI TEJA BOPPINITI Department of Information Technology saitejaboppiniti01@gmail.com 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. Keywords IoT privacy, urban health monitoring, privacy-preserving techniques, data security, anonymization, encryption, blockchain in healthcare, secure computation, public health technology. Introduction: The rapid integration of Internet of Things (IoT) technologies into urban health monitoring systems heralds a new era of data-driven healthcare in smart cities. As these innovative solutions evolve, concerns about the privacy and security of sensitive health information have become increasingly paramount. This research paper embarks on a comprehensive exploration of privacy-preserving techniques within the realm of IoT-driven urban health monitoring, aiming to address the burgeoning challenges and foster a balance between technological advancements and individual privacy rights. The confluence of IoT and urban health monitoring holds immense potential for revolutionizing healthcare delivery in densely populated urban areas. Real-time data collection and analysis