Biomedical Microelectromechanical Systems (BioMEMS) serve as a crucial catalyst in enhancing IoT communication security and safeguarding smart healthcare systems. Situated at the nexus of advanced technology and healthcare, BioMEMS are instrumental in pioneering personalized diagnostics, monitoring, and therapeutic applications. Nonetheless, this integration brings forth a complex array of security and privacy challenges intrinsic to IoT communications within smart healthcare ecosystems, demanding comprehensive scrutiny. In this manuscript, we embark on an extensive analysis of the intricate security terrain associated with IoT communications in the realm of BioMEMS, addressing a spectrum of vulnerabilities that spans cyber threats, data manipulation, and interception of communications. The integration of real-world case studies serves to illuminate the direct repercussions of security breaches within smart healthcare systems, highlighting the imperative to safeguard both patient safety and the integrity of medical data. We delve into a suite of security solutions, encompassing rigorous authentication processes, data encryption, designs resistant to attacks, and continuous monitoring mechanisms, all tailored to fortify BioMEMS in the face of ever-evolving threats within smart healthcare environments. Furthermore, the paper underscores the vital role of ethical and regulatory considerations, emphasizing the need to uphold patient autonomy, ensure the confidentiality of data, and maintain equitable access to healthcare in the context of IoT communication security. Looking forward, we explore the impending landscape of BioMEMS security as it intertwines with emerging technologies such as AI-driven diagnostics, quantum computing, and genomic integration, anticipating potential challenges and strategizing for the future. In doing so, this paper highlights the paramount importance of adopting an integrated approach that seamlessly blends technological innovation, ethical foresight, and collaborative ingenuity, thereby steering BioMEMS towards a secure and resilient future within smart healthcare systems, in the ambit of IoT communication security and protection.

Urban mobility systems require continuous monitoring and optimization to address increasing complexity and sustainability demands. This paper introduces UM-DS (Urban Mobility–Digital Shadow), a modular framework that integrates heterogeneous real-time and historical data, such as traffic intensity, incidents, weather, and public transport, into a unified model of urban mobility. UM-DS enables visualization, simulation, and analysis through an extensible dashboard connected to the SUMO simulation engine. Validated in the city of Malaga, the framework supports real-time exploration and temporal playback of traffic conditions, facilitating the development of AI-based forecasting models and multi-agent simulations. Its flexible, city-agnostic architecture allows adaptation to diverse urban contexts, bridging the gap between raw data and intelligent decision making. UM-DS provides a replicable foundation for next-generation smart-city mobility systems, fostering informed, data-driven strategies for sustainable urban transport.